Address : Room No. CS-203
IIT Hyderabad
Kandi, Sangareddy-502285
Telangana (State), India.
Phone : +91 - 94917 12312 (Mobile)
040- 2301 6352(Off)
Fax : +91 – 40 – 2301 6003
Skype : chalavadikm
Email : ckm[at]cse.iith.ac.in
Website : www.iith.ac.in/~ckm/

C Krishna Mohan

Professor
Department of Computer Science and Engineering
Former Dean of Public and Corporate Relations   

Brief Biography

Dr. C. Krishna Mohan is currently a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Hyderabad (IIT Hyderabad), India. He has been with IIT Hyderabad since 2009. He worked as Dean of Public and Corporate Relations, IIT Hyderabad, from Jan 2020 till Jan 2022. He was also the Head of the Department of Computer Science and Engineering, IIT Hyderabad, from May 2010 till October 2014. Before joining IIT Hyderabad, he was a senior faculty member at the National Institute of Technology Karnataka, Surathkal (NITK Surathkal). He received his M.Tech from NITK Surathkal and Ph.D. from the Indian Institute of Technology Madras (IIT Madras).

Prof Krishna Mohan heads Visual Learning and Intelligence Lab (VIGIL) at IIT Hyderabad working in the research areas of video content analysis, computer vision, machine learning, deep learning. He is a two time recipient of Excellence in Teaching Award, in recognition of distinguished teaching in the years 2018 & 2021 at IIT Hyderabad. Also, he received the Faculty Research Excellence Award in 2024 at IIT Hyderabad. He has published more than 150 papers in peer-reviewed international journals and conference proceedings. He has guided several Ph.D. (19), Masters (58), and Undergraduate (56) students. He has successfully carried out several projects with industry, government agencies, and academia.

Dr. C. Krishna Mohan was a Member of the Board of Governors (BOG), IIT Hyderabad, from June 2020 to December 2021 and Member of the Board of Governors (BOG), IIIT Kottayam from July 2022. Also, he is a Member of the Board of Directors, IIT Hyderabad Technology Research Park from September 2020 and a Member of the Board of Directors, i-TIC which is Technology Business Incubator (TBI) at IIT Hyderabad from September 2020. He is a Senate Member of IIT Hyderabad from November 2010. Also, he served as Senate Member of IIT Tirupati from September 2019 to April 2022, and IIITDM Kurnool from May 2019 to May 2021. He serves as a reviewer for several reputed international conferences and IEEE journals and is a Senior Member of IEEE, Member of ACM, AAAI Member, Life Member of ISTE, Fellow of IEI, IETE, and TAS. In 2023-2024, he was awarded with the prestigious Fulbright-Nehru International Education Administrators Seminar fellowship.

-<<< RESEARCH IMPACT >>>-

Prof. C. Krishna Mohan's research is centered on advanced Representation Learning techniques, with a strong emphasis on Image and Video Content Analysis, Intelligent Transportation Systems, and Edge-deployable Artificial Intelligence. His work seamlessly integrates core machine learning methodologies with real-world problem-solving, enabling the development of scalable, data-efficient solutions for complex spatio-temporal data analysis. A central theme of his research is the design of robust representation learning techniques tailored for video understanding and image-based scene interpretation. In the domain of intelligent transportation systems (ITS), Prof. Mohan has led the development of cutting-edge AI solutions for traffic monitoring, vehicle re-identification, pedestrian behavior analysis, and anomaly detection. These systems are engineered to operate under real-time constraints, enabling efficient and low-latency deployment through Edge AI in scenarios such as autonomous navigation and on-device video analytics. In parallel, his ITS research also plays a pivotal role in enabling smart city infrastructure by providing scalable AI-driven tools for urban traffic optimization, public safety monitoring, and incident detection. By harnessing data from live surveillance feeds and embedded sensors, his work facilitates critical applications in geospatial intelligence, environmental monitoring, and urban planning. Prof. Mohan's ability to translate deep representation learning into practical, deployable, and impactful AI systems positions him at the forefront of applied artificial intelligence. His contributions continue to shape the evolution of edge-intelligent systems and domain-aware learning across both academia and industries.

I. Representation Learning for Urban Mobility and Implementation

Research in representation learning has played a pivotal role in advancing urban mobility solutions, especially in the context of complex and unstructured traffic environments prevalent in Indian cities. These efforts have led to the development of AI-driven models capable of accurately detecting critical traffic violations, such as helmetless riding, abrupt lane changes, and potential collision trajectories, while also predicting risky behaviors in dynamic traffic conditions. These systems enable real-time decision-making in resource-constrained and cost-sensitive urban settings. As part of the Indo-Japanese M2Smart (link) (Multimodal Mobility Smart City) Project, intelligent mobility solutions have been conceptualized and deployed through a collaborative framework involving academic and industrial stakeholders. The project covers the full AI pipeline from multimodal data acquisition via traffic cameras and environmental sensors to scalable system-level implementations for intersection monitoring, smart parking, and dynamic traffic management. Field deployments, including testbeds on the IIT Hyderabad campus and a 30 km segment of National Highway NH-65, serve as real-world validation environments for building sustainable and data-driven smart city infrastructure. Additionally, the advancements in representation learning for intelligent transportation have been deployed in real-world settings, notably in Ahmedabad and Hyderabad cities in India, where AI-powered traffic monitoring systems, including helmet detection, chain snatching detection and accident prediction modules, are operational. This work on detecting street-level crimes such as snatch theft using real-world surveillance footage marks a significant advancement in urban safety analytics and has garnered widespread attention in the media.

• Societal Impact

The project has contributed to safer and more efficient urban transportation by enabling real-time detection of traffic violations, accident prediction, and intelligent monitoring. These AI-driven systems support improved traffic management and enforcement, helping authorities respond more effectively to road incidents. With deployments in cities like Ahmedabad and Hyderabad, the solutions are actively enhancing public safety and urban mobility.


• Open-Source Datasets and Codes

  1. SkyEye Dataset: This is the first aerial dataset for monitoring intersections with mixed traffic and lane-less behavior. Around 1 hour of video each from 4 intersections, namely, Paldi (P), Nehru bridge - Ashram road (N), Swami Vivekananda bridge - Ashram road (V), and APMC market (A) in the city of Ahmedabad, India. [link]
  2. EyeonTraffic (EoT) Dataset: The EyeonTraffic (EoT) dataset is a large-scale aerial traffic dataset specifically curated to study traffic states in mixed, lane-less urban environments. It comprises three hours of high-resolution aerial videos recorded at three busy intersections in Ahmedabad, India—Paldi, Nehru Bridge, and APMC Market captured using a DJI Phantom 4 Pro drone at 50 FPS in 4K resolution. [link]
  3. IITH Helmet 1 & IITH Helmet 2 Datasets: This dataset is collected from the surveillance network at the Indian Institute of Technology Hyderabad, India (IITH) campuS. It is a 2-hour surveillance video dataset which is collected at 30 frames per second. This second dataset is acquired from the CCTV surveillance network of Hyderabad city in India. It is a 1.5 hour video which is collected at 25 frames per second. [link]
  4. Snatch 1.0 Dataset: This is a real-world surveillance video dataset curated to study the rare and complex activity of snatch thefts. It consists of 816 video clips, each 10 seconds long, extracted from over 4.5 hours of CCTV footage recorded by the Hyderabad Traffic Police [link]
  5. IITH Accident Dataset: This is a surveillance video dataset curated for real-world road accident detection. Collected from the Hyderabad City CCTV surveillance network, the dataset comprises videos recorded at 30 FPS, capturing a variety of challenging conditions including daylight, high sunlight, and nighttime scenarios [link]
  6. IT Hyderabad Open-Air Parking Dataset: The dataset comprises 24 hours of continuous video data captured from an open-air off-street parking area at IIT Hyderabad, using a Hikvision Exir mini bullet camera installed at a height of 25 meters.
  7. AIWD6 (Adverse Intermediate Weather Driving) Dataset: This is A large-scale dataset encompassing six specific transitional weather states, sunny to rainy, rainy to sunny, sunny to foggy, foggy to sunny, cloudy to rainy, and rainy to cloudy, generated across three time intervals using a Variational Autoencoder (VAE) based data interpolation technique. [link]

• Patents

  1. C. Krishna Mohan, Dinesh Singh, C. Vishnu, and Debaditya Roy. "Method and system for real time detection of traffic violation by two-wheeled riders", Indian Patent Office, Official journal No. 18/2019, Application no. 201741038813, May 03, 2019
  2. Debaditya Roy, Dinesh Singh, C. Vishnu, and C. Krishna Mohan. "Method and system for detection of crime events in surveillance videos", Indian Patent Office, Official journal No. 21/2019, Application no. 201741041239, May 24, 2019
  3. C. Krishna Mohan, Dinesh Singh, C. Vishnu, and Debaditya Roy. "Method and system for detection of accident in traffic surveillance video", Indian Patent Office, Official journal No. 31/2019, Application no. 201841003604, Aug. 02, 2019
  4. Kondapally Madhavi, K Naveen Kumar, C Krishna Mohan, Sobhan Babu,“System And Method For Performing Adaptive Object Detection In An Autonomous Vehicle System”, Indian Patent Office, Application no. 202541001505, Jan, 07, 2025
  5. Kondapally Madhavi, K Naveen Kumar, C Krishna Mohan, Sobhan Babu,“System and method for generating weather transition data for autonomous vehicle training”, Indian Patent Office, Application no. 202541000718, Jan, 03, 2025

• Handbook

  • Handbook of Multimodal Transport for Smart City (Link)
  • Summary of Handbook (Link)

• Media Links

  1. Satreps (M2Smart) Project - V6 NEWS
    Open on YouTube (Link)
  2. Business Today
    Article (July 24, 2018)
    Don't take off your helmet — Business Today (Link)
  3. The Economic Times
    Article on AI to catch bikers without helmets
    IIT-Hyderabad develops AI to catch bikers without helmets — Economic Times (Link)
  4. The Times of India
    Coverage on AI-enabled software for helmet detection
    IIT-Hyderabad develops AI-enabled software to catch bike riders without helmet — Times of India (Link)
  5. The Hindu
    Article discussing electronic surveillance and future changes
    Electronic surveillance may see a marked change in future — The Hindu (Link)
  6. The Better India
    Feature on IIT Hyderabad's AI module
    IIT-Hyderabad AI module for helmet detection — The Better India (Link)
  7. Analytics India Magazine
    Industry coverage highlighting the AI system
    IIT-Hyderabad develops new AI-based system to catch bikers without helmets — Analytics India Magazine (Link)

II. Edge-AI for Mobile Platforms

A key focus of this research has been translating advances in representation learning into real-world, on-device AI solutions for mobile platforms. In collaboration with OPPO R&D India, two commercially deployed systems were developed, showcasing the potential of Edge-AI (link) in enhancing user experience through efficient and intelligent mobile applications. The first solution is a real-time AI-based video bokeh system that delivers high-quality background defocus effects in mobile video streams. It leverages optimized deep learning models for human segmentation and blur rendering, specifically tailored for the computational constraints of mobile hardware. The second solution addresses image management by enabling intelligent retrieval and filtering of similar, duplicate, and low-quality images. Using deep embeddings and mobile-optimized models, the system allows for real-time image clustering and quality assessment, improving photo organization and storage efficiency. Both solutions exemplify how cutting-edge AI research can be successfully deployed on edge devices, bridging academic innovation with industry-grade mobile AI applications.

• Societal Impact

The collaborative projects between Prof. C. Krishna Mohan and OPPO R&D India have received widespread national and international recognition across prominent media platforms. The innovative outcomes, particularly in the areas of mobile AI for video bokeh enhancement and intelligent image management. Recognized by government agencies like the Ministry of Human Resource Development and the Department of Science and Technology, the work demonstrates how academic-industry partnerships can drive meaningful advancements in AI and 5G technologies, enhancing everyday mobile experiences at scale.


• Media Links

• IIT Hyderabad-OPPO Partnership in Advancing AI and 5G-Enabled Technologies

  1. The Hindu (Link)
  2. Financial Express (Link)
  3. The Hans India (Link)
  4. NDTV (Link)
  5. Outlook India (Link)
  6. Business Standard (Link)
  7. Economic Times Telecom (Link)
  8. National Geographic TV Channel’s Superfactories (Link)
  9. Acknowledged by Government Bodies - Ministry of Human Resource Development (Link)

Research Supervision

  • PhDs Graduated - 19    PhDs Ongoing - 2

PhD Alumni

  1.

Mettu Srinivas {Website} 2014

Supervisor : Prof. C Krisha Mohan

Area of Research : Medical Image Processing

Thesis Title : Classification of Medical Data Based on Sparse Representation Using Dictionary Learning Link

Current Affiliation : Assistant Professor, NIT Warangal

  2.

N Pattabhi Ramaiah {Website} 2015

Supervisor : Prof. C Krisha Mohan

Area of Research : Biometrics

Thesis Title : De-duplication of Person’s Identity Using Multimodal Biometrics Link

Current Affiliation : Researcher, Canny Quest Intl. Fz LLC, Dubai

  3.

Avula Tirupathi Rao {Website} 2016

Supervisor : Prof. C Krisha Mohan

Area of Research : Biometrics

Thesis Title : Efficient Approaches for Fingerprint and Palmprint Recognition Link

Current Affiliation : Researcher, Reliance Jio Infocomunications Ltd

  4.

Earnest Paul Ijjina {Website} 2017

Supervisor : Prof. C Krisha Mohan

Area of Research : Human Action Recognition

Thesis Title : Efficient Approaches for Human Action Recognition using Deep Learning Link

Current Affiliation : Assistant Professor, NIT Warangal

  5.

Shyju Wilson {Website} 2018

Supervisor : Prof. C Krisha Mohan

Area of Research : Action Recognition in Sports

Thesis Title : Design of Compact and Discriminative Dictionaries Link

Current Affiliation : Assistant Professor, IIIT Guwahati

  6.

Debaditya Roy {Website} 2018

Supervisor : Prof. C Krisha Mohan

Area of Research : Action Recognition

Thesis Title : Representation Learning For Action Recognition Link

Current Affiliation : Assistant Professor, Indian Institute of Technology Kharagpur

  7.

Dinesh Singh {Website} 2018

Supervisor : Prof. C Krisha Mohan

Area of Research : Scalable Machine Learning

Thesis Title : Scalable and Distributed methods for Large Scale Visual Computing Link

Current Affiliation : Assistant Professor, Indian Institute of Technology Mandi

  8.

Nazil Perveen {Website} 2020

Supervisor : Prof. C Krisha Mohan

Area of Research : Facial Expression Recognition

Thesis Title : Learning Representations For Spontaneous Facial Expression Recognition

Current Affiliation : Research Associate, Manchester University, United Kingdom

  9.

Rajesh Reddy Datla 2021

Supervisor : Prof. C Krisha Mohan

Area of Research : Remote Imagery Analysis

Thesis Title : Representations for scene classification and segmentation in remote sensing imagery

Current Affiliation : Scientist-SF , Advanced Data processing Research Institute (ADRIN), ISRO, Dept.of Space, Govt.of India

 10.

Subhrajit Nag 2022

Supervisor : Prof. C Krisha Mohan

Co-supervisor : Dr. Sparsh Mittal, IIT Roorkee

Area of Research : Light-weight DNNs

Thesis Title : Efficient Deep Learning Models for Real-World Visual Computing Applications

Current Affiliation : Data Scientist in AI R&D - Aisin Tokyo Research Center , Japan

 11.

Prudhviraj Jeripothula 2022

Supervisor : Prof. C Krisha Mohan

Area of Research : Semantic Description of Video Activities

Thesis Title : Towards Effective Visual-Textual Representation for Vision to Language Tasks

Current Affiliation : Research consultant in TCS R&D, India

 12.

Rasna Azeez 2022

Supervisor : Prof. C Krisha Mohan

Area of Research : Geospatial Image Analysis

Current Affiliation : Sr. Technology Manager in Carrier, Hyderabad, India

 13.

Y. Sravani 2022 {Website}

Supervisor : Prof. C Krisha Mohan

Area of Research : Fine-grained Action Recognition

Thesis Title : Understanding human actions through interaction modeling

 14.

Sharma J 2022

Supervisor : Prof. C Krisha Mohan

Area of Research : Aerial imagery analysis

Thesis Title : Methods for Effective Classification and Captioning in Remote Sensing Images

Current Affiliation : Assistant professor at National Institute of Technology, Raipur

 15.

C Nagaraju 2023

Supervisor : Prof. C Krisha Mohan

Area of Research : Distributed Learning

Thesis Title : Communication Efficient Distributed Learning with Improved Convergence

Current Affiliation : Associate Professor at BVRIT college for women, Hyderabad, India

 16.

K Naveen Kumar 2024

Supervisor : Prof. C Krisha Mohan

Area of Research : Federated Learning

Thesis Title : Navigating Adversarial Attacks and Defense Mechanisms in Federated Learning : A Dual Perspective Approach

Current Affiliation : Postdoctoral Associate, MBZUAI, UAE

 17.

Damalla Rambabu 2025

Supervisor : Prof. C Krisha Mohan

Area of Research : Zero-Shot Learning and Remote Sensing

Thesis Title : Zero-Shot Learning Approaches for Enhanced Remote Sensing Scene Classification Representations

Current Affiliation : Assistant Professor at ICFAI University

 18.

Mrinmay Sen 2025

Supervisor : Prof. C Krisha Mohan

Co-supervisor : Dr. A Kai Qin, Swinburne University of Technology, Australia

Area of Research : Optimization in federated learning

Thesis Title : Accelerating Training of Centralized and Federated Learning Using Approximated Hessian Curvature

Current Affiliation : Senior Research Engineer at Videonetics Pvt Ltd

 19.

Kin Cho Win 2025

Supervisor : Prof. C Krisha Mohan

Co-supervisor : Dr. Zahid Akhtar, SUNY Polytechnic Institute

Area of Research : Facial Expression Recognition

Thesis Title : Robust and Generalizable Representation Learning for Facial Expression Recognition in the Wild

Current Affiliation : Lecturer, Myanmar Institute of Information Technology (MIIT), Myanmar

 19.

K Aveen Dayal 2025

Co-supervisor : Prof. C Krisha Mohan

Area of Research : Domain Adaptation, Domain Generalization and Multimodal A

Thesis Title : Adaptability and Generalizability of Deep Learning Models

Current Affiliation : Senior Multimodal AI Researcher, Dolby Research, Bangalore

PhDs Ongoing

Peketi Divya

Area of Research : Biomedical Image Analysis using Federated Learning

Udaya Kumar Ambati

Area of Research : Domain Adaptation in Medical Image Analysis

  • MTechs Graduated - 58   MDS Graduated - 16   MTechs Ongoing - 6

MTechs Graduated

S No.
 Name of the Student Thesis Title
1.
 K Jenni (2011) Content Based Image Retrieval by Preprocessing Image Database
2.
 Ch Sharath (2014) Matching Kernel for Variable Length Patterns of Human Activity Classification
3.
 J Srikanth (2014) Scene Segmentation and Classification
4.
 Tony Basil (2014) Features for Detection of Heart Arrhythmias
5.
 Kalla Srinivas (2015) Detection of Abnormal Events in Surveillance Videos
6.
 E Harish (2015) Face Recognition from Real Time Videos Using Stacked Autoencoder
7.
 Neeraj Kumar (2015) Content Based Image Retrieval for Big Visual Data
8.
 Kunal Dahiya (2016) Detection of Abnormal Events in Surveillance Videos
9.
 Vidhi Rani K (2016) Heirarchical Background Subtraction Algorithm for Foreground
10.
 Guguloth Suresh (2017) Reducing Convergence Time of Data-Parallel Approach for Distributed Neural Network
11.
 Lokesh Janghel (2017) Investigation of Siamese CNN for Person Detection and Re-Identification
12.
 Bedanta Das (2019) Action Localization in Videos
13.
 Challapalli Phanindra Revanth (2021) Object Detection on aerial imagery
14.
 Akhil Kumar Reddy Bhavanam (2021) Few-shot object detection via fine tuning
15.
 Vinay Prakash (2021) Few-shot object detection via fine tuning
16.
 Amey Nitin Bahulkar (2021) Adversarial attacks on autonomous vehicles
17.
 Sreeragh A R (2021) Improvements to semantic segmentation
18.
 Malipatel Indrakaran Reddy (2021) Attention guided compositional action recognition
19.
 Shri Vinayaka Pandi Nataraja Karayalar (2021) A comparative study of various techniques for image from text
20.
 Raman Kishore (2021) Attention based temporal modeling techniques for action recognition
21.
 GSD Sanjay Bharat (3 year) (2021) Multi Object Tracking And Segmentation In Surveillance Videos
22.
 Abhinav Singh (2021) Multi-scale Attention for Person Re-Identification
23.
 Vishal Kumar (2021) Semantic Segmentation Using Triplet Feature Network
24.
 Sachin Goyal (2021) Real-Time and online Multiple Object Tracking
25.
 Abhijith Girin N V (3 year) (2021) Fetal Heart Segmentation and Video Summarization
26.
 Uday Kumar (3 year) (2022) Computer Vision for Autonomous Vehicles
27.
 Sai Harsha (3 year) (2022) Traffic Congestion Prediction
28.
 Shivangi Parashar (2022) AI based Diagnosis of Liver Cancer
29.
 Durvasula V K M Rishab (2022) Object Detection on 3D Point Cloud Data
30.
 Anushka Joshi (2022) Computer Vision for Earth Science
31.
 Pooja H (2022) Action Recognition
32.
 Saurabh Joshi (2022) Multi Object Tracking In Military Surveillance Applications Using Computer Vision
33.
 Ankit Chandra (2022) Object Detection on Remote Sensing Images
34.
 Rajeev Sharma (2022) 3D Object Detection and Tracking using Point Cloud Data
35.
 Raj Surana (2022) Object Segmentation and Tracking for Autonomous Vehicles
36.
 Vineel Abhinav (3 year) (2022) Improving Instance Segmentation on Remote Sensing Aerial Images
37.
 Prasanna Kumar (2023) 3D Object Detection using Point Clouds
38.
 Sashank Jerri (2023) Model Fusion in Federated Learning for Medical Image Segmentation
39.
 Raguru Sai Sandeep (2023) Heterogenous Model Fusion in Federated Learning for Medical Analysis
40.
 Jaya Mohan (2023) LiDar and Camera Fusion in Autonomous Vehicle
41.
 Lakshmi Gayathri Gudipudi (2023) 3D Object Tracking using Point Clouds
42.
 Anant Mittal (2023) 3D Object Detection
43.
 P. Sharma (3 year) (2024) 3D Object Detection in Autonomous Vehicles using LIDAR Data
44.
 Ayush Kumar (2024) Causal Instance Segmentation in Adverse Weather Conditions
45.
 Shrusti (2024) Unsupervised Domain Adaptation
46.
 Manan Darji (2024) Federated Learning in Autonomous Vehicle Technology
47.
 Ahmed Abdullah (2024) Causal Semantic Segmentation in Adverse Weather Conditions
48.
 Morey Piyush Prabhakar (2025) Unsupervised Domain Adaptation for Pediatric Brain Tumor Segmentation
49.
 Suryansh Gautam (2025) Personalized Federated Learning for Breast Cancer Prediction
50.
 Patel Bhargav Piyushkumar (2025) Ensuring Privacy and Security in Small Language Model
51.
 Vellala Naga Saran (2025) Test Time Adaptation in Medical Imaging Analysis
52.
 Sourav Mazumdar (2025) Ensuring Privacy and Security in Small Language Model
53.
 Shukla Yash Mukeshkumar (2025) Towards Secure and Private Large Language Models for Modelling Clinical Notes
54.
 Shagun Sharma (2025) Multi-Target Unsupervised Domain Adaptation
55.
 Popat Raj Rameshkumar (2025) Achieving Privacy and Security in Vision Language Models for Medical Imagings
56.
 KR Anuraj (2025) Enchanced Aerial Object Detection for Millitary Application
57.
 Hrishikesh Hekme (2025) Accelerating Real-Time ML Inference for Autonomous Vehicles
58.
 Sanket Shivajirao Deone (2025) Enhancing Context-Aware Visual Question Answering for Autonomous Driving with Uncertainty Estimation

MDS Graduated

S No.
                     Name                     Thesis Work
1.
 Shri Vinayaka Pandi Nataraja Karayalar A comparative study of various techniques for image from text
2.
 Raman Kishore Attention based temporal modeling techniques for action recognition
3.
 Mohammad Shariq Khan Anomalous Action Recognition (Object Detection/Tracking + SlowFast Networks)
4.
 Anuran Banerjee Quantization of Deep Learning
5.
 Durga Prasad Chappidi Federated Object Detection
6.
 Kantesh Biswas Trajectory Prediction using TimeSeries Data
7.
 Shaurya Dwivedi FishEye Video Generation Task (CycleGAN)
8.
 Vivek Menon Video Analytics in Aerial Imagery
9.
 Partha Sarathi Chakraborthy Enhancing memory transformers for medical report generation
10.
 Aravinda Babu Maguluri Autonomous Vehicle Technology
11.
 Sayantan sarkar Autonomous Vehicle Technology
12.
 Parikshit Mukherjee Novel feature extractors for medical image multi label classification using SSL
13.
 Sanjeev Sharma Personalized federated learning using Hypernetworks
14.
 Kushboo Zero Shot Learning Using Mutually Semantic Distillation Network for Aerial Imagery Classification
15.
 Mohan Nayak Domain Adaptation for Pneumonia Classification
16.
 Subrat Mishra Domain Adaptation for Medical Image Analysis
17.
 Sourav Mazumdar Classification and forecasting of traffic congestion-under mds last rows

MTechs Ongoing

S No. Name of the Student Thesis Title
1. Kshitij Shrivastava Restoring Progressive Images in Adverse Weather Condition via Histogram Transformer
2. Sanskriti Agarwal Federated learning under distribution shifts with uncertainty aware aggregation
3. Aashish Singh Vision Language Modelling for Autonomous Vehicles
4. Laveena Herman Autonomous Navigation Applications using various Deep Learning Models
5. Metta Rajesh Krishna Multi Modal Vision Language Understanding for Autonomous Driving Scenarios
6. Arunkumar C Kudarihal Designing Vision-Language LLM Agents for Complex Visual Reasoning Tasks



  • BTech Graduated - 56

Collaborations

  • Prof. Nazmus Sakib, Kennesaw State University ,USA
  • Prof. Vijayakumar B, Carnegie Mellon University, USA
  • Prof. Ramesh Jain, University of California, Irvine, USA
  • Prof. Leonid Mestetskiy, Moscow State University, Moscow, Russia
  • Prof. Masaki Ito, University of Tokyo, Tokyo, Japan
  • Prof. Atsushi Fukuda, Nihon University, Tokyo, Japan
  • Tsutomu Tsuboi, Nagoya Electrical, Nagoya, Japan
  • Prof. Linga Reddy Cenkeramaddi, ACPS Group, UiA, Campus Grimstad, Norway.
  • Prof. Yen Wei Chen, College of Information Science and Engg., Ritsumeikan University, Japan
  • Navchetan Awasthi, University of Amsterdam, Netherlands
  • Dr. Zahid Akhtar, State University of New York Polytechnic Institute, USA
  • Swinburne University of Technology, Australia
  • Deakin University, Australia

-<<< PUBLICATIONS>>>-

Book

  1. S.S. Iyengar , Seyedsina Nabavirazavi , Yashas Hariprasad , Prasad HB , C. Krishna Mohan, "Artificial Intelligence in Practice", Theory and Application for Cyber Security and Forensics, 2025. ISBN 978-3-031-89326-1 ISBN 978-3-031-89327-8 https://doi.org/10.1007/978-3-031-89327-8

Book Chapters [3]

  1. Earnest Paul Ijjina and C. Krishna Mohan, "Human behavioural analysis using evolutionary algorithms and deep learning", Hybrid Intelligence for Image Analysis and Understanding, John Wiley, UK, pp. 165-186, 2017. ISBN101119242924, ISBN13 9781119242925
  2. Shyju Wilson, C. Krishna Mohan, and K. Srirama Murthy, "Event Based Sports Videos Classification using HMM Framework", Computer Vision in Sports, Springer International Publishing, pp. 229-244, 2014. DOI: 10.1007/978-3-319-09396-3_11
  3. C. Krishna Mohan, "Handbook of Multimodal Transport for Smart City" (Link)

Journals []

  1. G Swetha, Rajeshreddy Datla, Sobhan Babu, C Krishna Mohan, "CPL-PL: Contrapositive Learning-Based Pseudo-Labeling for Semi-Supervised Scene Classification in Remote Sensing Images", IEEE Geoscience and Remote Sensing Letters, vol. 22, pp. 1-5, 2025, (Impact Factor = 4.4) [Link]
  2. Aveen Dayal, S Shrusti, Linga Reddy Cenkeramaddi, C Krishna Mohan, Abhinav Kumar, "Leveraging Mixture Alignment for Multi-Source Domain Adaptation", IEEE Transactions on Image Processing, vol. 34, pp. 885-898, 2025, (Impact Factor = 10.8) [Link]
  3. K Naveen Kumar, C Krishna Mohan, and Linga Reddy Cenkeramaddi, "Federated Learning Minimal Model Replacement Attack Using Optimal Transport: An Attacker Perspective", IEEE Transactions on Information Forensics and Security, vol. 20, pp. 478-487, 2025, (Impact Factor = 6.3) [Link]
  4. K Naveen Kumar, C Krishna Mohan, Linga Reddy Cenkeramaddi, and Navchetan Awasthi, "Minimal Data Poisoning Attack in Federated Learning for Medical Image Classification: An Attacker Perspective", Artificial Intelligence In Medicine (Elsevier), vol. 159, pp. 103024, 2024, (Impact Factor = 6.1) [Link]
  5. Anushka Joshi, Balasubramanian Raman, and C Krishna Mohan, "Real-Time Earthquake Magnitude Prediction Using Designed Machine Learning Ensemble Trained on Real and CTGAN Generated Synthetic Data", Geodesy and Geodynamics Journal (Elsevier), vol. 16, pp. 350-368, 2024, (Impact Factor = 8.0) [Link]
  6. K. Naveen Kumar, Debaditya Roy, Thakur Ashutosh Suman, Chalavadi Vishnu, C. Krishna Mohan, "TSANet: Forecasting Traffic Congestion Patterns from Aerial Videos using Graphs and Transformers", Pattern Recognition (Elsevier), vol. 155, pp. 110-117, 2024, (Impact Factor = 8.0) [Link]
  7. Rajeshreddy Datla, Nazil Perveen, C Krishna Mohan, "Learning scene-vectors for remote sensing image scene classification", Neurocomputing (Elsevier), vol. 587, pp. 157-167, 2024, (Impact Factor = 5.779) [Link]
  8. Rajeshreddy Datla, G Swetha, C Gayathri, "EGANet: Elevation-guided attention network for scene classification in panchromatic remote sensing images", Neural Computing and Applications (Springer), vol. 36, pp. 18215-18262, 2024, (Impact Factor = 6.0) [Link]
  9. Yenduri Sravani, Chalavadi Vishnu, and C Krishna Mohan, "Adaptive temporal aggregation for table tennis shot recognition", Neurocomputing (Elsevier), vol. 587, pp. 127-137, 2024, (Impact Factor = 5.779) [Link]
  10. K Naveen Kumar, C Krishna Mohan, Linga Reddy Cenkeramaddi, "The Impact of Adversarial Attacks on Federated Learning: A Survey", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 46, no. 5, pp. 2672-2691, 2023, (Impact Factor = 24.314) [Link]
  11. Peketi Divya, Yenduri Sravani, Chalavadi Vishnu, C Krishna Mohan, Yen Wei Chen, "Memory Guided Transformer with Spatio-Semantic Visual Extractor for Medical Report Generation", IEEE Journal of Biomedical and Health Informatics, vol. 28, no. 5, pp. 3079-3089, 2024, (Impact Factor = 7.7) [Link]
  12. Madhavi Kondapally, K Naveen Kumar, Chalavadi Vishnu, and C Krishna Mohan, "Towards a Transitional Weather Scene Recognition Approach for Autonomous Vehicles", IEEE Transactions on Intelligent Transportation Systems, vol. 25, pp. 5201-5210, 2023, (Impact Factor = 8.5) [Link]
  13. Anushka Joshi, Linga Reddy Cenkeramaddi, Balasubramanian Raman, C Krishna Mohan, Linga Reddy Cenkeramaddi, "A new machine learning approach for estimating shear wave velocity profile using borelog data", Soil Dynamics and Earthquake Engineering (Elsevier), vol. 177, pp. 108424, 2023, (Impact Factor = 4.0) [Link]
  14. Soumya. A, Krishna Mohan C, and Linga Reddy Cenkeramaddi, "Recent Advances in mmWave-Radar-Based Sensing, Its Applications, and Machine Learning Techniques: A Review", MDPI Sensors Journal (MDPI Sensors), vol. 23, pp. 8901, 2023, (Impact Factor = 3.9) [Link]
  15. Rambabu Damalla, Rajeshreddy Datla, Chalavadi Vishnu, C Krishna Mohan, "Self-supervised embedding for generalized zero-shot learning in remote sensing scene classification", Applied Remote Sensing (SPIE), vol. 17, pp. 032405-032405, 2023, (Impact Factor = 1.568) [Link]
  16. Anushka Joshi, Balasubramanian Raman, C Krishna Mohan, Linga Reddy Cenkeramaddi, "Application of a New Machine Learning Model to Improve Earthquake Ground Motion Predictions", Natural Hazards (Springer), vol. 120, pp. 729-753, 2023, (Impact Factor = 3.7) [Link]
  17. Sai Harsha Yelleni, Kumari Deepshikha, Srijith P.K, Krishna Mohan Chalavadi, "Monte Carlo DropBlock for Modelling Uncertainty in Object Detection", Pattern Recognition (Elsevier), vol. 146, pp. 110003, 2023, (Impact Factor = 8) [Link]
  18. G Swetha, Rajeshreddy Datla, C Vishnu, C Krishna Mohan, "M2-APNet: A multimodal deep learning network to predict major air pollutants from temporal satellite images", Applied Remote Sensing (SPIE), vol. 18, pp. 012005-012005, 2023, (Impact Factor = 1.568) [Link]
  19. Suresh Samudrala, C Krishna Mohan, "Semantic Segmentation of Breast Cancer Images Using DenseNet with Proposed PSPNet", Multimedia Tools and Applications (Springer), vol. 83, pp. 46037-46063, 2023, (Impact factor = 3.6) [Link]
  20. Anushka Joshi, Chalavadi Vishnu, C Krishna Mohan, Balasubramanian Raman, "XGBoost model for early prediction of earthquake magnitude from waveform data", Earth System Science (Springer), vol. 133, pp. 5, 2023, (Impact factor = 2.0) [Link]
  21. Chalavadi Vishnu, Linga Reddy Cenkeramaddi, C Krishna Mohan, Jayesh Khandelwal, "EVAA - Exchange Vanishing Adversarial Attack on LiDAR Point Clouds in Autonomous Vehicles", IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 032405-032405, 2023, (Impact factor = 8.2) [Link]
  22. Chalavadi Vishnu, Vineel Abhinav, Debaditya Roy, Sobhan Babu, and C. Krishna Mohan, "Improving Multi-agent Trajectory Prediction using Dynamic Traffic States on Interactive Driving Scenarios", IEEE Robotics and Automation Letters, vol. 8, no.5, pp. 2708-2715, 2023, (Impact factor = 5.2) [Link]
  23. Aveen Dayal, M. Aishwarya, S. Abhilash, C Krishna Mohan, Abhinav Kumar, Linga Reddy Cenkeramaddi, "Adversarial Unsupervised Domain Adaptation for Hand Gesture Recognition using Thermal Images", IEEE Sensors Journal, vol. 23, pp. 3493-3504, 2022, (Impact factor = 4.323) [Link]
  24. Anushka Joshi, Chalavadi Vishnu, Krishna Mohan, "Early detection of earthquake magnitude based on stacked ensemble model", Asian Earth Sciences (Elsevier), vol. 8, pp. 100122, 2022, (Impact factor = 3.0) [Link]
  25. Onkar Susladkar, Gayatri Deshmukh, Subhrajit Nag, Ananya Mantravadi, Dhruv Makwana, Sujitha Ravichandran, Sai Chandra Teja R, Gajanan H Chavhan, C Krishna Mohan, and Sparsh Mittal, "ClarifyNet: A High-Pass and Low-Pass Filtering Based CNN for Single Image Dehazing", Systems Architecture (Elsevier), vol. 132, pp. 102736, 2022, (Impact factor = 4.5) [Link]
  26. Subhrajit Nag, Dhruv Makwana, Sai Chandra Teja R, Sparsh Mittal, and C Krishna Mohan, "WaferSegClassNet - A Light-weight Network for Classification and Segmentation of Semiconductor Wafer Defects", Computers in Industry journal (Elsevier), vol. 142, pp. 1-10, 2022, (Impact factor = 11.245) [Link]
  27. Dhruv Makwana, Subhrajit Nag, Onkar Susladkar, Gayatri Deshmukh, Sai Chandra Teja R, Sparsh Mittal, C Krishna Mohan, "ACLNet: An Attention and Clustering-based Cloud Segmentation Network", International Journal of Remote Sensing, vol. 13, no. 9, pp.865-875, 2022, (Impact factor = 3.531) [Link]
  28. Prudviraj Jeripothula, Chalavadi Vishnu, C Krishna Mohan, "AAP-MIT: Attentive Atrous Pyramid Network and Memory Incorporated Transformer for Multi-Sentence Video Description", IEEE Transactions on Image Processing, vol. 31, pp. 5559-5569, 2022, (Impact factor = 10.6) [Link]
  29. Chalamala Srinivasa R., K Naveen Kumar, Singh Ajeet, Saibewar Aditya, and C Krishna Mohan, "Federated learning to comply with data protection regulations", CSI Transactions on ICT (Springer Nature), vol. 10, pp.47-60, 2022 [Link]
  30. Prudviraj Jeripothula, Chalavadi Vishnu and C Krishna Mohan, "M-FFN: Multi-Scale Feature Fusion Network for Image Captioning", Applied Intelligence (Springer), vol. 52, pp. 1-21, 2022, (Impact factor = 5.019) [Link]
  31. Chalavadi, Vishnu, Prudviraj Jeripothula, Rajeshreddy Datla, Sobhan Babu Ch. and C Krishna Mohan, "mSODANet: A Network for Multi-Scale Object Detection in Aerial Images using Hierarchical Dilated Convolutions", Pattern Recognition (Elsevier), vol. 126, pp. 108548, 2022, (Impact factor = 8) [Link]
  32. Prudviraj Jeripothula, Yenduri Sravani, and C. Krishna Mohan, "Incorporating attentive multi-scale context information for image captioning", Multimedia Tools and Applications (Springer), vol. 82, pp. 1-21, 2022, (Impact factor = 3.6) [Link]
  33. Yenduri, Sravani, Nazil Perveen, Vishnu Chalavadi, and C. Krishna Mohan, "Fine-grained action recognition using dynamic kernels", Pattern Recognition (Elsevier), vol. 122, pp.108282, 2021, (Impact factor = 8.0) [Link]
  34. Chalavadi Vishnu, Rajeshreddy Datla, Debaditya Roy, Sobhan Babu, and C. Krishna Mohan, "Human Fall Detection in Surveillance Videos using Fall Motion Vector Modeling", IEEE Sensors Journal, vol. 21, no. 15, pp. 17162-17170, 2021, (Impact factor = 4.325) [Link]
  35. Deepak, K., Chandrakala, S. and C. Krishna Mohan, "Residual spatiotemporal autoencoder for unsupervised video anomaly detection", Signal, Image and Video Processing (Springer), vol. 15, no. 1, pp.215-222, 2021, (Impact factor = 2.3) [Link]
  36. Debaditya Roy, Tetsuhiro Ishizaka, C Krishna Mohan, Atsushi Fukuda, "Detection of Collision-Prone Vehicle Behavior at Intersections using Siamese Interaction LSTM", IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 4, pp. 3137-3147, 2020, (Impact factor = 8.5) [Link]
  37. Rajeshreddy Datla, C Krishna Mohan, "A novel framework for seamless mosaic of Cartosat-1 DEM scenes", Computers & Geosciences (Elsevier), vol. 146, pp. 104619, 2020, (Impact factor = 4.4) [Link]
  38. Nazil Perveen, Debaditya Roy and C Krishna Mohan, "Facial Expression Recognition in Videos using Dynamic Kernels", IEEE Transactions on Image Processing, vol. 29, pp. 8316-8325, 2020, (Impact factor = 10.6) [Link]
  39. Inayathullah Ghori, & Debaditya Roy, Renu John, and C Krishna Mohan, "Echocardiogram Analysis using Motion Profile Modeling", IEEE Transactions on Medical Imaging, vol. 39, no. 5, pages 1767-1774, 2019, (Impact factor = 10.6) [Link]
  40. D. Roy, S. R. M. K and C. K. Mohan, "Unsupervised Universal Attribute Modelling for Action Recognition", IEEE Transactions on Multimedia, vol. 21, no. 7, pp. 1672-1680, 2018, (Impact factor = 7.3) [Link]
  41. Dinesh Singh and C. Krishna Mohan, "Deep spatio-temporal representation for detection of road accident using stacked autoencoder", IEEE Transactions on Intelligent Transportation Systems, vol. 20, no. 3, pp. 879-887, 2019, (Impact factor = 8.5) [Link]
  42. Nazil Perveen, Debaditya Roy, and C. Krishna Mohan, "Spontaneous expression recognition using universal attribute model", IEEE Transactions on Image Processing, vol. 27, no. 11, pp. 5575-5584, 2018, (Impact factor = 10.6) [Link]
  43. Debaditya Roy and C. Krishna Mohan, "Snatch Theft Detection in Unconstrained Surveillance Videos Using Action Attribute Modeling", Pattern Recognition Letters (Elsevier), Vol. 108, 2018, Pages 56-61, 2018, (Impact factor = 5.1) [Link]
  44. Shyju Wilson and C. Krishna Mohan, "An information bottleneck approach to optimize the dictionary of visual data", IEEE Transactions on Multimedia, vol. 20, no. 1, pp. 96-106, 2018, (Impact factor = 7.3) [Link]
  45. Earnest Paul Ijjina and C. Krishna Mohan, "Human action recognition in RGB-D using motion sequence and deep learning", Pattern Recognition (Elsevier), vol. 72, pp. 504-516, 2017, (Impact factor = 8) [Link]
  46. Shyju Wilson and C. Krishna Mohan, "Coherent and non-coherent dictionaries for action recognition", IEEE Signal Processing Letters, vol.24, no.5, pp.698-702, 2017, (Impact factor = 3.9) [Link]
  47. Dinesh Singh, Debaditya Roy, and C. Krishna Mohan, "DiP-SVM : Distribution preserving kernel support vector machine for big data", IEEE Transactions on Big Data, vol.3, no.1, pp.79-90, 2017, (Impact factor = 7.2) [Link]
  48. Dinesh Singh and C. Krishna Mohan, "Graph formulation of video activities for abnormal activity recognition", Pattern Recognition (Elsevier), vol. 65, pp. 265-273, 2017, (Impact factor = 8) [Link]
  49. Earnest Paul Ijjina and C Krishna Mohan, "Classification of human actions using pose-based features and stacked auto encoder", Pattern Recognition Letters (Elsevier), vol. 83, pp. 268- 277, 2016, (Impact factor = 5.1) [Link]
  50. Debaditya Roy, M. Srinivas, and C. Krishna Mohan, "Sparsity-inducing dictionaries for effective action classification", Pattern Recognition (Elsevier), vol. 59, pp. 55-62, 2016, (Impact factor = 8) [Link]
  51. Earnest Paul Ijjina and C. Krishna Mohan, "Human action recognition using genetic algorithms and convolutional neural networks", Pattern Recognition (Elsevier), vol. 59, pp. 199-212, 2016, (Impact factor = 8) [Link]
  52. Earnest Paul Ijjina and C. Krishna Mohan, "Hybrid deep neural network model for human action recognition", Applied Soft Computing (Elsevier), vol. 46, pp. 936-952, 2016, (Impact factor = 8.7) [Link]
  53. M. Srinivas, R. Ramu Naidu, C.S. Sastry, and C. Krishna Mohan, "Content based medical image retrieval using dictionary learning", Neurocomputing (Elsevier), vol. 168, Pages 880-895, 2015, (Impact factor = 6) [Link]
  54. M. Srinivas, Tony Basil, and C. Krishna Mohan, "Adaptive learning based heartbeat Classification", Bio-Medical Materials and Engineering, vol. 26, no. 1, pp. 49-55, 2015, (Impact factor = 1.234) [Link]
  55. N. Pattabhi Ramaiah and C. Krishna Mohan, "Iris classification based on sparse representations using online dictionary learning for large-scale de-duplication applications", SpringerPlus (Springer), vol. 4, no. 1, pp.238, 2015 [Link]
  56. C. Krishna Mohan and B. Yegnanarayana, "Classification of sport videos using edge-Based features and autoassociative neural network models", Signal, Image and Video Processing (Springer), vol. 4, no. 1, pp. 61-73, 2008, (Impact factor = 2.3) [Link]
  57. A. Tirupathi Rao, N. Pattabhi Ramaiah and C. Krishna Mohan, "Fingerprint Recognition on Various Authentication Sensors", Journal of Electronic Science and Technology (ScienceDirect), vol.12, no.1, pp. 139-143, 2014 [Link]
  58. N. Pattabhi Ramaiah and C. Krishna Mohan, "De-duplication Complexity of Fingerprint Data in Large-scale Applications", Journal of Electronic Science and Technology (ScienceDirect), vol.12, no.2 pp. 1-5, 2014 [Link]

Conferences []

  1. K Naveen Kumar, Ranjeet Ranjan Jha, C Krishna Mohan, Ravindra Babu Tallamraju, “Fortifying Federated Learning Towards Trustworthiness via Auditable Data Valuation and Verifiable Client Contribution”, Accepted in IEEE Computer Vision and Pattern Recognition Conference (CVPR), pp. 4999-5009, 2025 [Link]
  2. Khin Cho Win, Zahid Akhtar, and C. Krishna Mohan, “Orthogonality-Aware Projection-Based Feature Enhancement for Fine-Grained Facial Expression Recognition in the Wild”, Accepted in International Conference on Machine Vision (ICMV), 2025
  3. Peketi Divya, C Krishna Mohan, Sumanth Yenduri, Sobhan Babu, "FSF3A: Federated Spatial Feature Alignment and Adaptive Aggregation for Heterogeneous Brain Tumor Segmentation", Accepted in British Machine Vision Conference, 2025
  4. Khin Cho Win, Zahid Akhtar, and C. Krishna Mohan, “CFE-FER: Channel-Guided Feature Enhancement for Robust Facial Expression Recognition”, Accepted in International Conference on Machine Vision (ICMV), 2025
  5. Khin Cho Win, Zahid Akhtar and C Krishna Mohan, “"CE-KD: Class-Wise Expert-based Knowledge Distillation for Facial Expression Recognition", Accepted in IEEE International Conference on Advanced Visual and Signal-Based Systems (AVSS), 2025
  6. Khin Cho Win, Zahid Akhtar, and C. Krishna Mohan, “Does Hard-Negative Contrastive Learning Improve Facial Emotion Recognition?”, Accepted in International Conference on Machine Vision and Applications (ICMVA), pp. 162–168, 2024 [Link]
  7. A Soumya, C Krishna Mohan, Linga Reddy Cenkeramaddi, “PointBi-FPN: An Extension to Point Pillars for LiDAR 3D Object Detection in Autonomous Vehicles Using Bi-Directional Feature Pyramid Network”, Accepted in International Conference TENCON, IEEE, pp. 1950-1953, 2024. [Link]
  8. Soumya A, C Krishna Mohan, Linga Reddy Cenkeramaddi, “High Precision Single Shot Object Detection in Automotive Scenarios”, in 19th International Conference on Computer Vision Theory and Applications (VISAPP), pp. 604-611, 2024. [Link]
  9. Khin Cho Win, Zahid Akhtar, C Krishna Mohan, “Robust Facial Emotion Recognition System via De-Pooling Feature Enhancement and Weighted Exponential Moving Average”, Accepted in International Conference TENCON, IEEE, pp. 116-119, 2024. [Link]
  10. Ishu Priya, C Krishna Mohan, “FL-PSeC: Federated Learning-Pseudo Labeled Medical Image Segmentation with Personalized Class Balancing Semi-supervised Approach”, Accepted in International Conference on Pattern Recognition (ICPR), pp. 227-241, 2024. [Link]
  11. Kondapally Madhavi, K Naveen Kumar, C Krishna Mohan, “Object Detection in Transitional Weather Conditions for Autonomous Vehicles”, Accepted in International Joint Conference on Neural Networks (IJCNN), IEEE, pp. 1-8, 2024. [Link]
  12. Damalla Rambabu, Swetha G, Datla Rajesh Reddy, Vishnu Chalavadi, C Krishna Mohan, “RSZero-CSAT: Zero-Shot Scene Classification in Remote Sensing Imagery Using a Cross Semantic Attribute-Guided Transformer”, Accepted in International Joint Conference on Neural Networks (IJCNN), IEEE, pp. 1-8, 2024. [Link]
  13. Aveen Dayal, Rishabh Lalla, Vineeth Balasubramanian, Linga Reddy Cenkeramaddi, C Krishna Mohan, Abhinav Kumar, “Improving Unsupervised Domain Adaptation: A Pseudo-Candidate Set Approach”, Accepted in European Conference on Computer Vision (ECCV), pp. 127-144, 2024. [Link]
  14. K Naveen Kumar, Reshmi Mitra, C Krishna Mohan, “Revamping Federated Learning Security from a Defender's Perspective: A Unified Defense with Homomorphic Encrypted Data Space”, Accepted in IEEE Computer Vision and Pattern Recognition Conference (CVPR), pp. 24387-24397, 2024. [Link]
  15. K Naveen Kumar, C Krishna Mohan, Aravind Machiry, “Precision Guided Approach to Mitigate Data Poisoning Attacks in Federated Learning”, Accepted in ACM Conference on Data and Application Security and Privacy (ACM CODASPY), pp. 233-244, 2024. [Link]
  16. Aveen Dayal, Vimal K B, Linga Reddy Cenkeramaddi, C Krishna Mohan, Abhinav Kumar, Vineeth N. Balasubramanian, “Margin-based Adversarial Learning for Domain Generalization”, in Proc. on Int. Conf. on Neural Information Processing Systems (NeurIPS), pp. 58938-58952, 2023. [Link]
  17. Peketi Divya, Vishnu Chalavadi, C. Krishna Mohan, Yen Wei Chen, "FLWGAN: Federated Learning with Wasserstein Generative Adversarial Network for Brain Tumor Segmentation", in Int. Joint Conf. on Neural Networks (IJCNN), IEEE, pp. 1-8, 2023. [Link]
  18. Soumya. A, Linga Reddy Cenkeramaddi, Chalavadi Vishnu, and Krishna Mohan C, "Multi-Class Object Classification using Deep Learning Models in Automotive Object Detection Scenarios"; in the 16th Int. Conf. on Machine Vision (ICMV), pp.48-55, 2023. [Link]
  19. Soumya. A, Linga Reddy Cenkeramaddi, Chalavadi Vishnu, Yash Vinod, and Krishna Mohan C, "Multi-Target Classification using Deep Learning Models for Automotive Applications", in the 11th Int. Conf. on Control, Mechatronics, and Automation (ICCMA), pp.31-36, 2023. [Link]
  20. G Swetha, Rajeshreddy Datla,C Vishnu,C Krishna Mohan, “MS-VACSNet: A Network for Multi-scale Volcanic Ash Cloud Segmentation in Remote Sensing Images”, in 18th Int. Conf. on Machine Vision and Applications (ICMVA), pp.1-6, 2023. [Link]
  21. Mrinmay Sen, C Krishna Mohan, Kai Qin, “FopLAHD: Federated optimization using Locally Approximated Hessian Diagonal”, in Int. Conf. Big Data Analytics (BDA), pp. 235-245, 2023. [Link]
  22. Mrinmay Sen, C Krishna Mohan, Kai Qin, "Federated Optimization with Linear-time approximated Hessian diagonal", in Int. Conf. on Pattern Recognition and Machine Intelligence (PReMI2023), pp. 106-113, 2023. [Link]
  23. P Harinadha, C. Krishna Mohan, “Leaf Based Tomato Plant Disease Detection Using Generated Images from WGP-ESR GAN”, in IEEE Int. Conf. on Data Science and Network Security (ICDSNS-2023), pp. 1-6, 2023. [Link]
  24. Suresh Samudrala, C. Krishna Mohan, “MRI Brain Tumor Detection and Classification Using U-NET CNN,” in IEEE Int. Conf. on Data Science and Network Security (ICDSNS-2023), pp. 1-5, 2023. [Link]
  25. P Harinadha, C. Krishna Mohan, “Tomato Plant Leaf Disease Detection Using Transfer Learning-based ResNet110”, in IEEE Int. Conf. on Data Science and Network Security (ICDSNS-2023), pp. 1-8, 2023. [Link]
  26. Swetha G, Rajesh Datla, C Krishna Mohan, “MS-VACSNet: A Network for Multi-scale Volcanic Ash Cloud Segmentation in Remote Sensing Images”, in Int. Conf. on Machine Vision Applications, pp. 1-6, 2023. [Link]
  27. Mrinmay Sen, C Krishna Mohan, A Kai Qin, “Federated Optimization with Linear-time approximated Hessian diagonal”, in Int. Conf. on Pattern Recognition and Machine Intelligence, pp. 106-113, 2023. [Link]
  28. C. Nagaraju, Mrinmay Sen, C. Krishna Mohan, "Handling Data Heterogeneity in Federated Learning with Global Data Distribution", in Int. Conf. on Image Processing and Vision Engineering (IPVE), pp. 121-125, 2023. [Link]
  29. Nagaraju C, Ramesh Yenda and Krishna Mohan C, “A Data Parallel Approach for Distributed Neural Networks to Achieve Faster Convergence”, in Int. Conf. on Machine Vision (ICMV 2023), pp. 380-389, 2023. [Link]
  30. Sharma J, Rajesh Reddy Datla, Yenduri Sravani, Chalavadi Vishnu, and C Krishna Mohan. "Aircraft type recognition in remote sensing images using mean interval kernel", in International Conference on Image Processing and Vision Engineering, pp. 166-173,2022 [Link]
  31. Sharma J, P. Divya., V. Chalavadi., C. L. Reddy., B. H. Shekar., and Krishna Mohan C. "Deformable and structural representative network for remote sensing image captioning", in International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications.(VISAPP, 2022). SciTePress, pp. 56-64, 2022.[Link]
  32. Sharma J, Peketi Divya, Sravani Yenduri, Shekar B H and C Krishna Mohan, “Structural Representative Network for Remote Sensing Image Captioning”, in International Conference on Machine Vision (ICMV), pp. 519-527, 2022.[Link]
  33. Yenduri Sravani, C Vishnu, and C Krishna Mohan., "Fine-grained action recognition using attribute vectors", in 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP), pp. 134-143 2022 [Link]
  34. Yenduri Sravani, Vishnu Chalavadi, and C. Krishna Mohan. "STIP-GCN: Space-time interest points graph convolutional network for action recognition", in International Joint Conference on Neural Networks (IJCNN), pp. 1-8. IEEE, 2022 [Link]
  35. Sravani Yenduri, Chalavadi Vishnu, and C. Krishna Mohan. , "Adaptive spatial and temporal aggregation for table tennis shot recognition", in International Conference on Machine Vision (ICMV), pp. 132-139, 2022 [Link]
  36. Dandpati Kumar Bhargav, Sai Chandra Teja R, Sparsh Mittal, C Krishna Mohan and Biswabandan Panda, "Inferring DNN layer-types through a hardware performance counters based side channel attack", in AIMLSystems, pp. 1-7, 2021 [Link]
  37. Subhrajit Nag, Yash Khandelwal, Sparsh Mittal, C Krishna Mohan, and A. Kai Qin., "ARCN: A Real-time Attention-based Network for Crowd Counting from Drone Images", in IEEE India Council International Conference (INDICON 2021). , pp. 1-6. IEEE, 2021 [Link]
  38. Rajeshreddy Datla, Chalavadi Vishnu, and C. Krishna Mohan. , "A multimodal semantic segmentation for airport runway delineation in panchromatic remote sensing images", in Int. Conf. on Machine Vision (ICMV 2021), Vol. 12084, pp. 46-52, 2021 [Link]
  39. Rajeshreddy Datla, Chalavadi Vishnu, and C. Krishna Mohan. , "A framework to derive geospatial attributes for aircraft type recognition in large-scale remote sensing images", in Int. Conf. on Machine Vision (ICMV 2021), Vol. 12084, pp. 172-179, 2021 [Link]
  40. Rajeshreddy Datla, Chalavadi Vishnu, and C. Krishna Mohan., "Scene Classification in Remote Sensing Images using Dynamic Kernels", in Proc. of Int. Joint Conf. on Neural Network (IJCNN 2021), pp. 1-8. IEEE, 2021 [Link]
  41. Jeripothula Prudviraj, Chalavadi Vishnu, and C. Krishna Mohan., "Attentive Contextual Network for Image Captioning", in Int. Joint Conf. on Neural Network (IJCNN 2021), pp. 1-8. IEEE, 2021 [Link]
  42. Debaditya Roy, K Naveen Kumar, C. Krishna Mohan, "Defining Traffic States using Spatio-Temporal Traffic Graphs", in IEEE Intelligent Transport Systems Conference (ITSC), pp. 1-6. IEEE, 2020 [Link]
  43. Dinesh Singh, C. Vishnu, C. Krishna Mohan, "Real-Time Detection of Motorcyclist without Helmet using Cascade of CNNs on Edge-device", in. IEEE Intelligent Transport Systems Conference (ITSC), pp. 1-8. IEEE, 2020 [Link]
  44. Nandan Kumar Jha, Rajat Kumar Saini, Bedant Das, Sparsh Mittal, C Krishna Mohan, "ULSAM: Ultra-Lightweight Subspace Attention Module for Compact Convolutional Neural Networks", in Proc. IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1627-1636, 2020 [Link]
  45. Nazil Perveen and C. Krishna Mohan, "Configural representation of facial action units for spontaneous facial expression recognition in the wild", in 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP), pp. 93-102, 2020 [Link]
  46. Nazil Perveen, C. Krishna Mohan, and Yen. Wei Chen, "Quantitative Analysis of Facial Paralysis Using GMM and Dynamic Kernels", in 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP), pp. 173-184, 2020 [Link]
  47. Debaditya Roy, Tetsuhiro Ishizaka, C. Krishna Mohan, and Atsushi Fukuda, "Vehicle Trajectory Prediction at Intersections using Interaction based Generative Adversarial Networks", IEEE Intelligent Transportation Systems Conference (ITSC), Auckland, New Zealand, pp. 2318-2323. DOI: 10.1109/ITSC.2019.8916927 2019 [Link]
  48. Dinesh Singh and C. Krishna Mohan, "Projection-SVM: Distributed Kernel Support Vector Machine for Big Data using Subspace Partitioning", IEEE International Conference on Big Data (Big Data), Seattle, WA, USA, pp. 74-83. DOI: 10.1109/BigData.2018.8622478, 2018 [Link]
  49. Dinesh Singh, Abhijeet Bhure,  Sumit Mamtani and C. Krishna Mohan, "Fast-BoW: Scaling Bag-of-Visual-Words Generation", British Machine Vision Conference (BMVC), p.287, Sep 3-6, 2018 [Link]
  50. Debaditya Roy, C. Krishna Mohan, and K. Sri Rama Murty, "Action recognition based on discriminative embedding of actions using Siamese networks", 2018 IEEE International Conference on Image Processing (ICIP), Athens, Greece. Oct. 7-10, 2018 [Link]
  51. C. Vishnu, Dinesh Singh, C. Krishna Mohan and Ch. Sobhan Babu, "Detection of Motorcyclists without Helmet in Videos using Convolutional Neural Network", Proc. IEEE International Joint Conference on Neural Network (IJCNN), Anchorage, Alaska, USA, pp. 3036-3041, May 14–19, 2017 [Link]
  52. Debaditya Roy, K. Sri Rama Murty and C. Krishna Mohan, "Action-vectors: Unsupervised Movement Modelling for Action Recognition", IEEE International Conference on Acoustics, Speech, and Signal Processing, (ICASSP), New Orleans, USA, pp. 1602-1606, March 05-09, 2017 [Link]
  53. Dinesh Singh, C. Vishnu, and C. Krishna Mohan, "Visual Big Data Analytics for Traffic Monitoring in Smart City", IEEE International Conference on Machine Learning and Applications (ICMLA), Anaheim, California, USA, pp. 886-891, Dec. 18-20, 2016 [Link]
  54. Nazil Perveen, Dinesh Singh and C. Krishna Mohan, "Spontaneous Facial Expression Recognition: A Part Based Approach", IEEE International Conference on Machine Learning and Applications (ICMLA), Anaheim, California, USA, pp. 819-824, Dec. 18-20, 2016 [Link]
  55. Dinesh Singh and C. Krishna Mohan, "Distributed Quadratic Programming Solver for Kernel SVM using Genetic Algorithm", IEEE Congress on Evolutionary Computation (IEEE CEC), Vancouver, Canada, pp. 152-159, July 24-29, 2016 [Link]
  56. Kunal Dahiya, Dinesh Singh and C. Krishna Mohan, "Automatic Detection of Bike-riders without Helmet using Surveillance Videos in Real-Time", International Joint Conference on Neural Networks (IJCNN), Vancouver, Canada, pp. 3046-3051, July 24-29, 2016 [Link]
  57. M. Srinivas, Debaditya Roy and C. Krishna Mohan, "Discriminative feature extraction of X-ray images using deep convolutional neural networks", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, China, pp. 917-921, March 20-25, 2016 DOI: 10.1109/ICASSP.2016.7471809 [Link]
  58. M. Srinivas and C. Krishna Mohan, "Classification of medical images using edge based features and sparse representation", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, China, pp. 912-916, March 20-25, 2016. DOI: 10.1109/ICASSP.2016.7471808 [Link]
  59. A Tirupathi Rao, N. Pattabhi Ramaiah and C. Krishna Mohan, "Nearest neighbor minutia quadruplets based fingerprint matching with reduced time and space complexity", IEEE International Conference on Machine Learning and Applications (ICMLA), Miami, Florida, pp. 378-381, Dec. 2015. DOI: 10.1109/ICMLA.2015.124 [Link]
  60. M. Srinivas and C. Krishna Mohan, "Multi-level classification: A generic classification method for medical data sets", IEEE International Conference on E-health Networking, Application   Services (Healthcom), Boston, USA, pp. 262-267, Oct 2015. DOI: 10.1109/HealthCom.2015.7454509 [Link]
  61. N. Pattabhi Ramaiah, N. Srilatha, C. Krishna Mohan, "Sparsity-based iris classification using iris fiber structures", IEEE International Conference of Biometrics Special Interest Group (BIOSIG), Darmstadt, Germany, pp. 1-4, Sept. 2015. DOI: 10.1109/BIOSIG.2015.7314621 [Link]
  62. Debaditya Roy, K. Murty, and C. Krishna Mohan, "Feature selection using deep neural networks", IEEE International Joint Conference on Neural Networks (IJCNN), Tempe, Miami, USA, pp. 1-6, July 2015. DOI: 0.1109/IJCNN.2015.7280626 [Link]
  63. M. Srinivas, R. Bharath, Pachamuthu Rajalakshmi and C. Krishna Mohan, "Sparseland model for speckle suppression of B-mode ultrasound images", IEEE National Conference on Communication (NCC), IIT Bombay, India, pp. 1-6, Mar. 2015. DOI: 10.1109/NCC.2015.7084842 [Link]
  64. Debaditya Roy, M. Srinivas, and C. Krishna Mohan, "Sparsifying dense features for action classification", ACM International Conference on Perception and Machine Intelligence (PerMIn), ISI Kolkata, India, pp. 211-217, Feb. 2015. DOI: 10.1145/2708463.2709047 [Link]
  65. 13. N. Pattabhi Ramaiah, Earnest Paul Ijjina, C. Krishna Mohan, "Illumination invariant face recognition using convolutional neural networks", IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES), Calicut, India, pp. 1-4, Feb. 2015. DOI: 10.1109/SPICES.2015.7091490 [Link]
  66. Earnest Paul Ijjina, and C. Krishna Mohan, "Human action recognition based on motion capture information using fuzzy convolution neural networks", IEEE International Conference on Advances in Pattern Recognition (ICAPR), ISI Kolkata, India, pp. 1-6, Jan. 2015. DOI: 10.1109/ICAPR.2015.7050706 [Link]
  67. Earnest Paul Ijjina and C. Krishna Mohan, "Facial expression recognition using kinect depth sensor and convolutional neural networks", IEEE International Conference on Machine Learning and Applications (ICMLA), Detroit, USA, pp. 392-396, Dec. 2014 [Link]
  68. Earnest Paul Ijjina and C. Krishna Mohan, "One-shot periodic activity recognition using convolutional neural networks", IEEE International Conference on Machine Learning and Applications (ICMLA), Detroit, USA, pp. 388-391, Dec. 2014. DOI: 10.1109/ICMLA.2014.69 [Link]
  69. Earnest Paul Ijjina and C. Krishna Mohan, "Human action recognition based on recognition of linear patterns in action bank features using convolutional neural networks", IEEE International Conference on Machine Learning and Applications (ICMLA), Detroit, USA, pp. 178-182, Dec. 2014. DOI: 10.1109/ICMLA.2014.33 [Link]
  70. Earnest Paul Ijjina and C. Krishna Mohan, "Human action recognition based on MOCAP information using convolution neural networks", IEEE International Conference on Machine Learning and Applications (ICMLA), Detroit, USA2014. DOI: 10.1109/ICMLA.2014.30 [Link]
  71. N. Pattabhi Ramaiah and C. Krishna Mohan, "Enhancements to latent fingerprints in forensic applications", 19th IEEE International Conference on Digital Signal Processing (DSP), Hong Kong, pp. 439-443, Aug. 2014. DOI: 10.1109/ICDSP.2014.6900702 [Link]
  72. M. Srinivas, Debaditya Roy, and C. Krishna Mohan, "Learning sparse dictionaries for music and speech classification", 19th IEEE International Conference on Digital Signal Processing (DSP), Hong Kong, pp. 673-675, Aug. 2014. DOI: 10.1109/ICDSP.2014.6900749 [Link]
  73. M. Srinivas and C. Krishna Mohan, "Medical images modality classification using multi-scale dictionary learning", 19th IEEE International Conference on Digital Signal Processing (DSP), Hong Kong, pp. 621-625, Aug. 2014. DOI: 10.1109/ICDSP.2014.6900739 [Link]
  74. Shyju Wilson, M. Srinivas and C. Krishna Mohan, "Dictionary based action video classification with action bank", 19th IEEE International Conference on Digital Signal Processing (DSP), Hong Kong, pp. 597-600, Aug. 2014. DOI: 10.1109/ICDSP.2014.6900734 [Link]
  75. M. Srinivas, Debaditya Roy, and C. Krishna Mohan, "Music genre classification using On-line dictionary learning", IEEE International Joint Conference on Neural Networks (IJCNN), Arlington, USA, pp. 1937-1941, July 2014. DOI: 0.1109/IJCNN.2014.6889516 [Link]
  76. N. Pattabhi Ramaiah and C. Krishna Mohan, "De-duplication Complexity of Fingerprint Data in Large-scale Applications", Journal of Electronic Science and Technology, (JEST), vol.12, no.2 pp. 1-5, June 2014 [Link]
  77. A. Tirupathi Rao, N. Pattabhi Ramaiah and C. Krishna Mohan, "Fingerprint Recognition on Various Authentication Sensors", Journal of Electronic Science and Technology, (JEST), vol.12, no.1, pp. 139-143, March 2014 [Link]
  78. A. Tirupathi Rao, N. Pattabhi Ramaiah, Ahmed Babu I.A.S, and C. Krishna Mohan, "Biometrics in e-governance and academia using hand-held fingerprint terminals", Elsevier International Conference on Advances in Communication, Network, and Computing (CNC), Chennai, India, pp. 653-658, Feb. 2014 [Link]
  79. N. Pattabhi Ramaiah, and C. Krishna Mohan, "De-noising slap fingerprint images for accurate slap fingerprint segmentation", IEEE International Conference on Machine Learning and Applications and Workshops (ICMLA), vol. 1, Honolulu, Hawaii, pp. 208-211, Dec. 2011. DOI: 10.1109/ICMLA.2011.52 [Link]
  80. N. Pattabhi Ramaiah, and C. Krishna Mohan, "ROI-based tissue type extraction and volume estimation in 3D brain anatomy", International Conference on Image Information Processing (ICIIP), Shimla, India, pp. 1-5, Nov. 2011. DOI: 10.1109/ICIIP.2011.6108941 [Link]
  81. N. Pattabhi Ramaiah, and C. Krishna Mohan, "De-duplication of photograph images using histogram refinement", IEEE Recent Advances in Intelligent Computational Systems (RAICS), Trivandrum, India, pp. 391-395, Sep. 2011. DOI: 10.1109/RAICS.2011.6069341 [Link]
  82. M. Srinivas, and C. Krishna Mohan, "Efficient clustering approach using incremental and Hierarchical clustering methods", International Joint Conference Joint on Neural Networks (IJCNN), Barcelona, Spain, pp. 1-7, July 2010. DOI: 10.1109/IJCNN.2010.5596666 [Link]
  83. C. Krishna Mohan, N. Dhananjaya, and B. Yegnanarayana, "Video shot segmentation using late fusion techniques", International Conference on Machine Learning and Applications (ICMLA), San Diego, USA, pp. 267-270, Dec. 2008. DOI: 10.1109/ICMLA.2008.88 [Link]
  84. C. Krishna Mohan and B. Yegnanarayana, “Event-Based Sports Videos Classification Using HMM Framework,” Indian International Conference on Artificial Intelligence (IICAI), Pune, India, pp. 559-564, Dec. 2007 [Link]
  85. C. Krishna Mohan, N. Dhananjaya, Suryakanth V. Gangashetty, and B.Yegnanarayana, "Sports video classification using autoassociative neural network models", International Conference on cognitive and neural systems (ICCNS), Boston, USA, pp. 30, May 2006
  86. Vakkalanka Suresh, C. Krishna Mohan, R. Kumara Swamy, and B. Yegnanarayana, "Combining multiple evidence for video classification", IEEE International Conference on Intelligent Sensing and Information Processing (ICISIP), Bangalore, Dec 2005 [Link]
  87. Vakkalanka Suresh, C. Krishna Mohan, R. Kumara Swamy, and B. Yegnanarayana, "Content-Based video classification using support vector machines", Interntational Conference on Neural Information Processing (ICONIP), Calcutta, India, pp. 726-731, Nov. 2004. DOI: 10.1007/978-3-540-30499-9_111 [Link]

Workshops [6]

  1. K. Madhavi, K. Naveen Kumar, and C. Krishna Mohan, "TransWardX: An Explainable Black-box Object Detection Attack for Autonomous Driving in Transitional Weather Conditions", in Pattern Recognition. ICPR vol 15619, pp. 275-290, Springer, Cham. doi:10.1007/978-3-031-88223-4_20, 2024. [Link]
  2. K. Naveen Kumar, Digvijay S. Pawar, and C. Krishna Mohan. "Open-air Off-street Vehicle Parking Management System Using Deep Neural Networks: A Case Study", In Proc. 14th IEEE Int. Conf. on COMmunication Systems & NETworkS (COMSNETS), pp. 800-805, doi: 10.1109/COMSNETS53615.2022.9668364, 2022. [Link]
  3. K Naveen Kumar, C Vishnu, Reshmi Mitra, C Krishna Mohan, "Black-box Adversarial Attacks in Autonomous Vehicles", in IEEE Applied Imagery Pattern Recognition (AIPR), pp. 1-7, 2020. [Link]
  4. Earnest Paul Ijjina and C. Krishna Mohan, "View and illumination invariant object classification based on 3D color histogram using convolutional neural networks", IEEE 12th Asian Conference on Computer Vision (ACCV), Workshops, Singapore, pp. 316-327, Nov. 2014. DOI: 10.1007/978-3-319-16628-5_23 [Link]
  5. Earnest Paul Ijjina and C. Krishna Mohan, "Human action recognition using action bank features and convolutional neural networks", IEEE 12th Asian Conference on Computer Vision (ACCV), Workshops, Singapore, pp. 328-339, Nov. 2014. DOI: 10.1007/978-3-319-16628-5_24 [Link]

-<<< PROJECTS>>>-


Consultancy Projects


Project Demo


M2Smart: Smart Cities for Emerging Countries Based on Sensing, Network, and Big Data Analysis of Multimodal Regional Transport System
Duration : 5 years

Vehicle Detection

Vehicle Counting

Vehicle Segmentation

Vehicle Tracking

Vehicle Detection on Hyderabad Traffic

Smart Parking System

Road Scene Analysis

Road Segmentation

Mobile Edge Computing: Optimized Video Bokeh and Image Deduplication OPPO India R & D, Hyderabad

Image Deduplication

Video Bokeh

Facial Engagement Classification through Face Detection on Semi-supervised Data
I'm Beside You (IBY - Japan)

Real-time Road Hazard Detection
Hyundai GMobis, Hyderabad

Real-Time Aerial Tracker on Embedded Hardware Deployed on Ballistic Systems
Research Center Imarat (RCI), DRDO, Hyderabad

Multi-stage Aerial Tracking

Tracking Results

Tracking Results

Tracking Results

Autonomous Vehicle Technology

Segmentation of VRU

Depth Estimation

Collision Prediction

Road Scene Analysis

Multi-Vehicular Tracking

Road Segmentation

Industrial Application of Anamoly Detection in Fine-grained Actions
Cogknit, Bangalore

AI-based Weather Forecasting using Live Camera, Radar and Satellite Data,
Weathernews Inc. Chiba, Japan

Precipitation Nowcast

Cloud Classification Timeline

Cloud Classification and Detection

Cloud Representation

Volcanic Ash Detection

Deity - Meity (MHRD) Design and Development of Facial Paralysis Quantitative Analysis Model for Clinical Assessment

Content Driven Advertisement Placement and Insertion

Complex Action Inference

Action Localization

Video Description

Video Understanding

Action Localization

Semantic Description of Video Activities

-<<< EXPERIENCE>>>-

Academic Experience


S No.
 Designation Institute Start Date End Date
1.
 Professor (HAG) IIT Hyderabad Sep 04, 2024 Till date
1.
 Professor IIT Hyderabad Sep 04, 2018 Sep 03, 2024
2.
 Associate Professor IIT Hyderabad July 16, 2014 Sep 03, 2018
3.
 Assistant Professor IIT Hyderabad Nov 04, 2009 July 15, 2016
4.
 Associate Professor NIT Surathkal Oct 30, 2006 Nov 03, 2009
5.
 Selection Grade Lecturer NIT Surathkal Oct 30, 2003 Oct 29, 2006
6.
 Senior Lecturer NIT Surathkal Oct 30, 1998 Oct 29, 2003
7.
 Lecturer NIT Surathkal Sep 04, 1992 Oct 29, 1998
8.
 Programmer NIT Surathkal Sep 04, 1991 Sep 03, 1992

Administrative Experience

S No.
 Designation Institute Start Date End Date
1.
 Board of Governors (BOG) IIT Hyderabad June 3, 2020 Dec 31, 2021
2.
 Dean (Public and Corporate Relations) IIT Hyderabad Jan 03,2020 Till date
3.
 Head - Dept. of Computer Sci. & Engg. IIT Hyderabad May 11, 2011 Oct 31, 2014
4.
 Associate Head - Dept. of Computer Sci. & Engg. IIT Hyderabad Apr 27, 2010 May 10, 2011
5.
 Senate Member IIT Hyderabad Nov, 2010 Till date
6.
 Central Assistant Public Information Officer IIT Hyderabad Nov 8, 2012 Mar 29, 2016
7.
 Central Public Information Officer IIT Hyderabad Mar 30, 2016 Till date
8.
 Senate Member IIT Tirupati Sep 9, 2019 Aug, 2021
9.
 Senate Member IIITDM Kurnool May 19, 2019 May 18, 2021
10.
 Chairman, Faculty & Staff Grievance Committee IIT Hyderabad Sep 23, 2019 July 5, 2022
11.
 Member, Board of Directors IIT Hyderabad Technology Research Park Sep 27, 2020 Till date
12.
 Member, Board of Directors IIT Hyderabad i-TIC Foundation Sep 27, 2020 Till date
13.
 Chairman - Disciplinary Action Committee (DAC) IIT Hyderabad Dec 08, 2020 July 7, 2022
14.
 Member, Board of Governors IIIT Kottayam July 01, 2022 Till date
15.
 Member, Technical Advisory Committee for Patent Acquisition Collaborative Research & Technology Development (PACE) Program of Department of Scientific & Industrial Research (DSIR) September 14, 2021 March 31, 2026
16.
 Co-opted Member, SERB-PAC committee Biomedical and Health Science (BHS) August, 2022 Till date
17.
 Member, Police Technology Missions sub-committee : Imagery Intelligence (IMINT) and Signal Intelligence (SIGINT) Ministry of Home Affairs Government of India October, 2022 Till date
18.
 Contact coordinate of experts in the field of Drone Techniques Union Public Service Commission (UPSC), New Delhi June, 2023 Till date

Governing Body / Academic Council


S No.
 Designation Institute Start Date End Date
1.
 Member of Advisory Committee CBIT Hyderabad Apr 2021 Till Date
2.
 Member - Governing Body BVRIT Hyderabad July 2015 Till date
3.
 Member of Academic Council Malla Reddy University Hyd Jan 2021 Till date
4.
 Member - Governing Body AITAM Tekkali July 2016 Till date
5.
 Member of Governing Body Sreyas Institute of Engineering and Technology Dec 2020 Till date
6.
 Member of Academic Council, AITAM Tekkali July 2013 Dec 2015
7.
 Member, Governing Body Gokaraju Rangaraju Institute of Engineering and Technology April 2022 Till date
8.
 UGC nominee on the governing body Kommuri Pratap Reddy Institute of Technology September 2022 Till date
9.
 Editorial Member KirIITH April, 2023 Till date
10.
 Member, Academic Council Ramachandra College of Engineering, Eluru June, 2023 Till date
11.
 Expert committee member to evaluate the existing academic programmes Cochin University of Science and Technology June, 2023 Till date

Board of Studies (BOS) Member


S No.
 Institute Start Date End Date
1.
 JNTU Hyderabad June 2012 June 2019
2.
 JNTU Anantapur June 2013 June 2016
3.
 JNTU Kakinada June 2012 Till Date
4.
 VNRVJIET Hyderabad July 2011 Till Date
5.
 Vardhaman College of Engg. Hyderabad Aug 2014 Till Date
6.
 Anurag Group of Institutions, Hyderabad May 2016 Till Date
7.
 JBIET Hyderabad June 2015 Till Date
8.
 MRCE Hyderabad Oct 2011 Till Date
9.
 RVR & JC College of Engg. Guntur Oct 2015 Till Date
10.
 VJIT Hyderabad June 2017 June 2019
11.
 SJCE Mysore Aug 2012 Till Date
12.
 NEC Kovilpatti Oct 2019 Till Date
13.
 PDA Engg. College, Gulbarga, Karnataka Oct 2019 Till Date
14.
 School of CSE, Kerala University of Digital Sciences, Innovation and Technology (KUDSIT), Kerala Mar 2021 Till Date
15.
 School of Computer Engineering, Kalinga Institute of Industrial Technology, Odisha Mar 2021 Till Date
16.
 VIT AP Amaravathi Jan 2021 Till Date
17.
 Bonam Venkata Chalamayya Engineering College, Odalarevu, AP Jan 2021 Till Date
18.
 Methodist college of Engineering and Technology Sep 2021 Till Date
19.
 Mizoram University from 15-9-2021 to 14-09-2024 Sep 2021 Sep 2024
20.
 D.J. Sanghvi College of Engineering April 2022 Till Date

Institution-Building

  • Established Visual Intelligence and Learning Group (VIGIL) at IIT Hyderabad
  • Established CSE Dept. teaching and research labs
  • Involved in various academic activities like designing fractal curriculum for the CSE department
  • Delivered several invited talks in various institutions, conferences, and workshops
  • Served as TPC member for several conferences
  • Established three NKN-virtual classrooms as the IITH Nodal officer
  • Involved in outreach initiatives through TEQIP, CSE Dept open day, BoS activities, workshops for schools


-<<< SERVICES>>>-

Professional Bodies

  • Senior Member, IEEE
  • Member, ACM and AAAI
  • Life Member, ISTE (Indian Society For Technical Education)
  • Fellow of IEI, Fellow of IETE, and Fellow of TAS

Journal Reviewer

  • IEEE Transactions : Image Processing, Multimedia, Big Data, Intelligent Transport Systems, Signal Processing Letters
  • Elsevier : Pattern Recognition, Pattern Recognition Letters, Neuro Computing
  • Springer : Signal, Image and Video Processing

Awards / Recognitions

  • Excellence in Research Award, in recognition of distinguished research in the year 2024 at IIT Hyderabad.
  • Awarded Fulbright-Nehru International Education Administrators Seminar fellowship for the year 2023-2024.
  • In recognition of his works on detection of crime events in surveillance videos and traffic analytics, selected as a member of police technology missions sub-committee: Imagery intelligence (IMINT) and signal intelligence (SIGINT),Ministry of Home Affairs, Government of India.
  • In recognition to the academic credentials, appointed as Senate Member in IIT Tirupati & member of Board of Governors (BOG) in IIIT Kottayam
  • Best oral presentation for a manuscript entitled “A multimodal semantic segmentation for airport runway delineation in panchromatic remote sensing images”, at the 14th International Conference on Machine Vision (ICMV 2021), Italy.
  • Runner up in the National Level Project Competition of Innovation in Manufacturing Processes (IMP 2021) by CKM Vigil Pvt. Ltd. organized by the National Frontiers of Engineering Symposium (NATFOE-2021)
  • Recipient of Excellence in Teaching Award, in recognition of distinguished teaching in the years 2018 and 2021 at IIT Hyderabad.
  • Awarded Visiting Researcher Fellowship. Carnegie Mellon University, Pittsburg, 2007.
  • Awarded Visiting Researcher Fellowship. University of California, Irvine, 2013.
  • Visiting Professor position at Nihon University, Japan.
  • Certification of recognition from DRDO RCI Director.
  • Certification of recognition from DRDO ANURAG Director.
  • Mr. Earnest Paul Ijjina, PhD Student has won First Prize at the 6th IDRBT Doctoral Colloquium (held during Dec 8-9, 2016) for his work on "Human Action Recognition Using Deep Learning". First prize carries a prize money of Rs 1.5 Lakh along with a certificate.
  • Mr. Dinesh Singh, PhD Student has won First Prize at the 8th IDRBT Doctoral Colloquium (held during Dec 7, 2018) for his work on "Graph formulation of video activities for abnormal activity recognition". First prize carries a prize money of 1 Lakh INR along with a certificate.
  • Appointed as co-opted member of the SERB-PAC committee in Biomedical and Health science (BHS).
  • Area Co-Chair for Syntax and Semantics in ICON2023.


International Conference Organization

  • Member, Local Organizing Committee, International Conference “Interspeech 2018” held during September 2-6, 2018 at Hyderabad International Convention Centre (HICC) Hyderabad.
  • General Chair - IEEE International Conference on Integrated Intelligence and Communication Systems (ICIICS) - 2023.
  • Steering Committee - IEEE International Conference on Network, Multimedia and Information Technology (NMITCON) - 2023.

Workshops / Training Programs Conducted

  • Co-Coordinator, Three days workshop on “HAHTIUS - Harnessing AI for Healthcare” held during 16-18 December, 2024 at IIT Hyderabad.
  • Coordinator, Three days workshop on “INCAPS - 2nd Indo-Norway Workshop on Smart Sensing, Communication and Machine Learning for Autonomous and Cyber Physical Systems” held during 14-16 October, 2022 at IIT Hyderabad.
  • Coordinator, One week TEQIP workshop on “Deep Learning for Visual Computing (WDLVC)” held during 20-25 June, 2016 at IIT Hyderabad.
  • Coordinator, Two Days workshop on “Neural Networks and Deep Learning” held during 20-21 January, 2016 at BHEL HRD & ATE (Corporate R & D), Hyderabad.
  • Coordinator, One week MHRD sponsored short term training programme on “Signal, Image and Speech Processing” held during 8-13 September, 2008 at NITK Surathkal.