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Our AI research aims to build and evaluate intelligent systems that perceive, reason and act in complex environments while remaining transparent, fair, and aligned with human values.
The Lab-in-Charge leads our research mission to develop intelligent AI systems by focussing on three research domains. This lab provides a platform for young students to test novel ideas and build their own professional identity in a collaborative, decentralized environment.
This lab focuses on three dimensions namely: a. simulated robotics and reinforcement learning, b. perception and ethical Intelligence, and c. knowledge representation and reasoning. By leveraging simulated robotics and reinforcement learning, we develop agents capable of acting in complex environments. Through the second dimension, we integrate computer vision, natural language processing, and ethical AI. This enables us to have intelligent systems which can understand the world while remaining fair, transparent, and aligned with human values. Towards knowledge representation and reasoning, we design representation and reasoning mechanisms that allow AI systems to infer and make context-aware decisions.
It is a research domain that facilitates the modeling and analysis of complex decision-making problems within simulated environments. Its generic and adaptable nature supports applications across multiple sectors, including assistive robotics, autonomous systems, etc. Furthermore, it provides an effective framework for testing theoretical advancements in reinforcement learning and their integration with frontier deep learning techniques, ultimately leading to more efficient, robust, and adaptive approaches.
This domain emphasizes the development of AI systems that not only achieve high performance but also maintain transparency, fairness, explainability, and ethical accountability. In our lab, we explore this direction through a variety of real-world and emerging use cases, allowing us to investigate diverse perception-driven challenges across domains. By combining advances in machine perception, trustworthy AI, and ethical intelligence, we aim to design adaptive systems that can make reliable and socially responsible decisions in complex environments.
While modern deep learning approaches excel at pattern recognition and data-driven learning, they often lack interpretability, logical consistency, contextual understanding, and robust reasoning capabilities. In our lab, we investigate how symbolic reasoning, ontologies, knowledge graphs, commonsense reasoning, and logical inference mechanisms can complement modern deep learning techniques to build more trustworthy, explainable, and human-aligned AI systems.
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Lab Member
Position: Ph.D Research Scholar
Domain: Perception and Ethical Intelligence
Lab Member
Position: Ph.D Research Scholar
Domain: Perception and Ethical Intelligence
Lab Member
Position: M.Tech Student
Domain: Simulated Robotics and Reinforcement Learning
Lab Member
Position: M.Tech Student
Domain: Simulated Robotics and Reinforcement Learning
Lab Member
Position: M.Tech Student
Domain: Knowledge Representation
Lab Member
Position: M.Tech Student
Domain: Knowledge Representation
Lab Member
Position: B.Tech Student
Domain: Simulated Robotics and Reinforcement Learning
Lab Member
Position: B.Tech Student
Domain: Simulated Robotics and Reinforcement Learning
Past Member
Currently: Software Engineer at TrieDatum Inc.
Past Member
Currently: Quality Engineer at LTIMindtree
Past Member
Currently: Joined M.Tech programme at Tezpur University
Past Member
Currently: Joined M.Tech programme at Tezpur University
Past Member
Currently: Project Assistant at IIT Guwahati
Grants and institutional support powering our research.
The Lab-in-Charge has been awarded the Young Faculty Research Grant from Gauhati University, in recognition of early-career research excellence and ongoing contributions to AI and intelligent systems.
Selected for the prestigious ANRF-PAIR Grant (Category B) under the Hub–Spoke model (Hub: IIT Guwahati, Spoke: Gauhati University). The Lab-in-Charge shall be acting as Co-Principal Investigator on this collaborative research initiative.
T Dutta, R Dutta, R Bhattacharyya
International Conference on Artificial Intelligence and Emerging Technology…
A J Sarma, R Bhattacharyya
Accepted at IEEE GCON
N Sarmah, R Bhattacharyya
Accepted at International Journal of Data Science and Analytics
G Duwarah, N Sarmah, R Bhattacharyya
Accepted at International Conference on Applied Artificial Intelligence], Springer CCIS proceedings (Scopus indexed)
G Duwarah, N Sarmah, R Bhattacharyya
Accepted at International Conference on Applied Artificial Intelligence], Springer CCIS proceedings (Scopus indexed)
Have a query or interested in collaboration? Reach out to us.