Hi!

I am a third year PhD student in the Machine Learning Department at Carnegie Mellon University, advised by Prof. Jeff Schneider. My research interests broadly include reinforcement learning and bayesian optimization. My current research involves developing active decision making algorithms in multi-agent systems for robotics search and tracking applications under realistic sensing, communication and resource considerations while modeling motion and detection uncertainty.

Previously, I graduated from the Indian Institute of Technology Kharagpur with a combined Bachelors (Hons.) and Masters Dual Degree in Computer Science and Engineering. I was advised by Prof. Pabitra Mitra for my undergraduate thesis.

Publications and Manuscripts

Cost Aware Asynchronous Multi-Agent Active Search
Arundhati Banerjee, Ramina Ghods, Jeff Schneider
In Submission, 2021.

Decentralized Multi-Agent Active Search for Sparse Signals
Ramina Ghods, Arundhati Banerjee, Jeff Schneider
UAI 2021. | arxiv

Artificial neural network for identification of short-lived particles in the CBM experiment
Arundhati Banerjee, Ivan Kisel, Maksym Zyzak
Special Issue: Learning to Discover, International Journal of Modern Physics A (IJMPA), 2020. | paper

DeepTagRec: A Content-cum-User Based Tag Recommendation Framework for Stack Overflow
Suman Kalyan Maity, Abhishek Panigrahi, Sayan Ghosh, Arundhati Banerjee, Pawan Goyal, Animesh Mukherjee
ECIR 2019. | paper

Workshop presentations

Cost Aware Asynchronous Multi-Agent Active Search
Arundhati Banerjee, Ramina Ghods, Jeff Schneider
WiML Un-Workshop @ ICML 2021 | poster

Multi-Agent Active Search and Rescue
Ramina Ghods, Arundhati Banerjee, William Durkin and Jeff Schneider
3rd Robot Learning Workshop : Grounding Machine Learning Development in the Real World @ NeurIPS 2020 | poster

Teaching

Introduction to Machine Learning (10-701)
Teaching Assistant
Carnegie Mellon University, Spring 2021