Our research group works on various fundamental algorithms and applications of machine learning with a focus on Computer Vision. Our problems of interest are focused on Responsible AI, and we work on Explainable AI, Active Learning, and Meta-learning topics under various Govt. of India-funded projects such as DRDO, ISRO, and DST.
Our primary goal is to solve complex, real-world problems by applying the core fundamentals of Computer Vision and Artificial Intelligence. We aim to build efficient models that can be used to address real-time challenges in computer vision and AI. By mastering these technologies, we strive to create practical, impactful solutions that can be implemented globally. We believe that AI should be accessible to everyone, and our goal is to ensure that data-driven insights are used effectively to address pressing challenges around the world.
At the Center for AI in Computer Vision, we are committed to narrowing the gap between theoretical research in machine learning and its practical applications in real-world scenarios. Our focus is on leveraging cutting-edge AI technologies to tackle complex problems across various domains. Our research and development efforts aim to create intelligent systems that not only advance the field but also make a meaningful impact on society.
Our multidisciplinary research spans several key areas:
Computer Vision: Advancing techniques in visual recognition and scene understanding to enable machines to interpret and interact with the visual world.
Machine Learning & Deep Learning: Designing and training intelligent systems that learn from data to perform tasks with accuracy, efficiency, and adaptability.
Responsible & Explainable AI: Ensuring our technologies are transparent, fair, and accountable. We develop AI systems that stakeholders can understand, trust, and govern.
October 2025:
Our paper “Replay to Remember (R2R): An Efficient Uncertainty-driven Unsupervised Continual Learning Framework Using Generative Replay” by Sriram Mandalika and Harsha Vardhan has been accepted at the 28th European Conference on Artificial Intelligence (ECAI 2025).
October 2025:
Four papers from our lab have been accepted for publication in the 10th International Conference on Computer Vision and Image Processing (CVIP 2025), to be held from December 10–13, 2025, at the Indian Institute of Technology Ropar, Punjab, India.
April 2025: Our work named "PRIMEDrive-CoT: A Precognitive Chain-of-Thought Framework for Uncertainty-Aware Object Interaction in Driving Scene Scenario" is accepted at The 7th IEEE/CVF CVPR Precognition Workshop! to be held in conjunction with CVPR 2025 in Nashville, US. Congratulations, Sreeram and Lalitha!
October 2024: "RESEARCHER ON THE RISE:" Dr. Athira Nambiar got featured in the October’24 issue of IEEE Biometric Council Newsletter (page 37, Volume 051, Archived Newsletters).
December 2024: Two papers on Sonar simulator dataset "S3Simulator" and Explainable Active learning framework "SegXAL" are presented at ICPR 2024. Congratulations to Kamal Basha and Sriram Mandalika !
Aug 2024: The Scientific Computing (SC) Panel, Naval Research Board, DRDO meeting and outreach programme was held at SRMIST on 12th August 2024. The event featured a series of addresses from leaders in Defense and Academia.
Sep 2023: Our paper “Adapt-FuseNet: Context-aware Multimodal Adaptive Fusion of Face and Gait Features using attention techniques for Human Identification,” got the “IAPR Best Biometrics Student Paper Award” in IEEE International Joint Conference on Biometrics, Ljubljana, Slovenia, 25-28 September 2023. Congratulations Ashwin and Thejaswin !
At the Center for AI in Computer Vision, we carry out cutting-edge research at the intersection of Artificial Intelligence and Computer Vision, addressing complex challenges in high-stakes domains such as medicine, defense, and space exploration. Our research spans several subfields, each with the potential to transform industries and society as a whole.
Their funding and collaboration enable us to push the boundaries of AI and computer vision technology.
We are grateful for their support in advancing this field.