Nilaksh

I am a final year dual degree (bachelors + masters) student at Indian Institute Of Technology, Kharagpur, majoring in Electronics and Electrical Communication Engineering with a specialization in Vision. I'm also minoring in Computer Science. Currently I am working on vision-based RL with Prof. Saumik Bhattacharya for my master's thesis.

Previously, I was a research intern at CLAIRE, EPFL, where I worked on multi-objective RL under Prof. Caglar Gulcehre. I was also a research intern at FRPG where I worked on multi-task adaptive RL under Prof. Aamir Ahmad. I was also fortunate to work with Prof. Shishir Kolathaya, RBCCPS IISc, on barrier function inspired reward shaping. I have also studied uncertainty quantification and explainability under Dr. Moloud Abdar.

At IIT Kharagpur I've worked on NLP and formal language with Prof. Aritra Hazra, and on defense against SSL backdoor attacks with Prof. Somesh Kumar for my bachelor's thesis.

Email  /  CV  /  Scholar  /  Github  /  LinkedIn

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Research Interests

I'm interested in reinforcement learning, computer vision, efficient deep learning and robotics. I hope to work on research problems that deeper my current understanding of these subjects, while also prompting me to think in new ways.

Publications

Towards Adversarial Robustness And Backdoor Mitigation in SSL
Nilaksh*, Aryan Satpathy*, Dhruva Rajwade*, Somesh Kumar
Accepted at IEEE International Conference on Acoustics, Speech, and Signal Processing, 2025
arXiv / code

Defense against backdoor attacks on Self-Supervised Learning in frequency space.

Adaptive Reinforcement Learning for Robot Control
Yu Tang Liu, Nilaksh, Aamir Ahmad
Accepted at IEEE International Conference on Intelligent Robots and Systems (IROS), 2024
paper / code

A novel adaptive agent that leverages transfer learning techniques to dynamically adapt policy in response to different tasks and environmental conditions

Barrier Functions Inspired Reward Shaping for Reinforcement Learning
Nilaksh, Abhishek Ranjan, Shreenabh Agrawal, Aayush Jain, Pushpak Jagtap, Shishir Kolathaya
IEEE International Conference on Robotics and Automation (ICRA), 2024
paper / code

A novel safety-oriented reward-shaping framework inspired by barrier functions, offering simplicity and ease of implementation across various environments and tasks.

Projects

Automated Geometry Problem Solver
Research Project, 2022
code

A solver for SAT level geometry problems that uses a domain adapted BART transformer to predict correct geometric theorem sequences.

TinyCompiler: a compiler for BASIC
Personal Project, 2023
code

A simple compiler written in C++ that compiles a BASIC like language to C code. Produces the abstract syntax tree (AST) of the source for optimizations.

NSES: Natural Selection Evolution Simulator
Term Project, 2020
code

Simulates natural selection in a small world by mutating rudimentary genes and using a simple genetic algorithm. Conforms to the Lotka–Volterra predator–prey model.


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