CV

Education

• Ph.D., Electrical and Computer Engineering — Vanderbilt University, Nashville, TN (Aug 2021 – Jul 2026, Expected)
  • Advisor: Prof. Abhishek Dubey, Institute for Software Integrated Systems
• B.Tech., Electronics and Communication Engineering — Heritage Institute of Technology, Kolkata, India (Aug 2016 – Jun 2020)

Research Experience

• Graduate Research Assistant — Institute for Software Integrated Systems, Vanderbilt University (Jan 2021 – Present)
  • Lead Researcher, Nissan V2X Collaboration: Architected a hierarchical control framework combining MILP and Multi-Agent RL to coordinate 50+ distributed energy assets; achieved >10% cost reduction over baselines
  • CARTA Transit Electrification: Led optimization modeling for Chattanooga’s electric bus fleet; formulated a Stackelberg game for charging scheduling that reduced operational costs by 6% and GHG emissions by 10 tons
  • Developed open-source tools (E-Transit-Bench, MoveOD) enabling scalable simulation of city-scale transit and energy systems
• Research Intern (Connected Energy & Data Analytics) — Nissan North America Inc., Santa Clara, CA (Jun 2023 – Sep 2023)
  • Designed a cost-optimization pipeline for V2B power flows, achieving 15% reduction in peak demand charges
  • Analyzed 50k+ vehicle telematics records to model user behavior and flexibility
  • Co-developed the OPTIMUS digital twin for benchmarking demand-response strategies
• Undergraduate Researcher — Jadavpur University, Kolkata, India (May 2018 – Jun 2020)
  • Designed low-cost, portable IoT systems for environmental sensing (Air Quality Monitoring) and automation
  • Awarded Best Paper at I3SET 2019 for a QCM-sensor integration on an 8-bit microcontroller

Industry Experience

• NextGen Leaders Fellow (Energy Systems) — OpenMinds Inc. (May 2025 – Jan 2026)
  • Collaborating with Carrier and CenterPoint Energy to deploy battery-enabled heat pump controllers for dynamic load shaping
  • Developing analytic frameworks to quantify trade-offs between grid reliability constraints and operational flexibility
• Assistant Systems Engineer — TATA Consultancy Services, Kolkata, India (Sep 2020 – Aug 2021)
  • Optimized enterprise dashboards using Angular (20% faster load times) and automated backend scheduling pipelines

Teaching

• Graduate Teaching Assistant — Embedded Systems Lab, Vanderbilt University (Fall 2021)
  • Instructed undergraduates in C++ fundamentals through hands-on labs culminating in building logic-based code-controlled cars

Technical Skills

• Languages: Python, C++, SQL, Java, JavaScript, MATLAB, LaTeX
• Optimization & AI: CPLEX, Gurobi, PyTorch, TensorFlow, Scikit-learn, RLlib, MPC, MDP formulations
• Big Data & Tools: PySpark, Docker, Git, AWS (EC2/S3), SUMO (Traffic Sim), GridLAB-D
• Hardware & Maker: VLSI Design, 3D Printing, RC Plane/Drone Construction, Embedded Systems, Microcontroller Programming
• Web: D3.js, React

Publications

P-V2B: A Neuro-Symbolic Framework for Leveraging User Persistence in Vehicle-to-Building Charging

R. Sen, F. Liu, J. P. Talusan, A. Pettet, Y. Suzue, A. Mukhopadhyay, and A. Dubey, P-V2B: A Neuro-Symbolic Framework for Leveraging User Persistence in Vehicle-to-Building Charging, 17th ACM/IEEE International Conference on Cyber-Physical Systems, 2026.

CONSENT: A Negotiation Framework for Leveraging User Flexibility in Vehicle-to-Building Charging under Uncertainty

R. Sen, F. Liu, J. P. Talusan, A. Pettet, Y. Suzue, M. Bailey, A. Mukhopadhyay, and A. Dubey, CONSENT: A Negotiation Framework for Leveraging User Flexibility in Vehicle-to-Building Charging under Uncertainty, 2026.

MoveOD: Synthesizing Origin-Destination Commute Distribution from US Census Data

R. Sen, A. Dubey, A. Mukhopadhyay, S. Samaranayake, and A. Laszka, MoveOD: Synthesizing Origin-Destination Commute Distribution from US Census Data, 2025.

Online Decision-Making Under Uncertainty for Vehicle-to-Building Systems

R. Sen, Y. Zhang, F. Liu, J. P. Talusan, A. Pettet, Y. Suzue, A. Mukhopadhyay, and A. Dubey, Online Decision-Making Under Uncertainty for Vehicle-to-Building Systems, 2025.

Reinforcement Learning-based Approach for Vehicle-to-Building Charging with Heterogeneous Agents and Long Term Rewards

F. Liu, R. Sen, J. P. Talusan, A. Pettet, A. Kandel, Y. Suzue, A. Mukhopadhyay, and A. Dubey, Reinforcement Learning-based Approach for Vehicle-to-Building Charging with Heterogeneous Agents and Long Term Rewards, 2025.

Grid-Aware Charging and Operational Optimization for Mixed-Fleet Public Transit

R. Sen, A. Sivagnanam, A. Laszka, A. Mukhopadhyay, and A. Dubey, Grid-Aware Charging and Operational Optimization for Mixed-Fleet Public Transit, in 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), 2024.

OPTIMUS: Discrete Event Simulator for Vehicle-to-Building Charging Optimization

J. P. Talusan, R. Sen, A. K. Ava Pettet, Y. Suzue, L. Pedersen, A. Mukhopadhyay, and A. Dubey, OPTIMUS: Discrete Event Simulator for Vehicle-to-Building Charging Optimization, in 2024 IEEE International Conference on Smart Computing (SMARTCOMP), 2024.

Calibrating real-world city traffic simulation model using vehicle speed data

S. Khaleghian, H. Neema, M. Sartipi, T. Tran, R. Sen, and A. Dubey, Calibrating real-world city traffic simulation model using vehicle speed data, in 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 2023.

BTE-Sim: Fast simulation environment for public transportation

R. Sen, T. Tran, S. Khaleghian, M. Sartipi, H. Neema, and A. Dubey, BTE-Sim: Fast simulation environment for public transportation, 2022 IEEE International Conference on Big Data, 2022.

E-Transit-Bench: Simulation Platform for Analyzing Electric Public Transit Bus Fleet Operations

R. Sen, A. K. Bharati, S. Khaleghian, M. Ghosal, M. Wilbur, T. Tran, P. Pugliese, M. Sartipi, H. Neema, and A. Dubey, E-Transit-Bench: Simulation Platform for Analyzing Electric Public Transit Bus Fleet Operations, in Proceedings of the Thirteenth ACM International Conference on Future Energy Systems, New York, NY, USA, 2022, pp. 532–541.

Microcontroller Based Sensor-Array Data Acquisition System for Electronic Nose

N. Debabhuti, R. Sen, A. Sengupta, S. Sengupta, P. Sharma, B. Tudu, N. Bandyopadhyay, and R. Bandyopadhyay, Microcontroller Based Sensor-Array Data Acquisition System for Electronic Nose, in 2020 IEEE Calcutta Conference (CALCON), 2020.

Development of the data acquisition system and GUI for QCM sensor based system

N. Debabhuti, A. Sengupta, P. Sharma, R. Sen, B. Tudu, and R. Bandyopadhyay, Development of the data acquisition system and GUI for QCM sensor based system, in 2020 IEEE Calcutta Conference (CALCON), 2020.

Development of an android platform for monitoring QCM sensor-array based Electronic Nose

N. Debabhuti, A. Sengupta, R. Sen, A. Ghosh, S. Banerjee, P. Sharma, B. Tudu, N. Bandyopadhyay, and R. Bandyopadhyay, Development of an android platform for monitoring QCM sensor-array based Electronic Nose, in 2020 IEEE Applied Signal Processing Conference (ASPCON), 2020.

Low-Cost Air Pollution Monitoring Device Based on Air Quality Index

R. Bajaj, R. Sen, A. Sengupta, A. Sen, S. Karmakar, S. Ghosh, V. Kumar, B. Tudu, N. Bandyopadhyay, and R. Bandyopadhyay, Low-Cost Air Pollution Monitoring Device Based on Air Quality Index, in 2020 IEEE Applied Signal Processing Conference (ASPCON), 2020.

Honors & Awards

• Best PhD Forum Poster Award — ACM/IEEE ICCPS 2025 (Irvine, CA)
• Best Paper Award Finalist — AAMAS 2025 (Detroit, MI) — Top 5% of submissions
• 2nd Place, Best Poster Competition — INFORMS 2025 Annual Meeting
• OpenMinds NextGen Leader 2025 — Energy & Climate leadership cohort
• Russell G. Hamilton Scholar — Vanderbilt University
• Best Paper Award — I3SET 2019

Service & Leadership

• Treasurer — ECE Student Association, Vanderbilt University
• Student Chair — IEEE Heritage Branch (organized technical fests with 1000+ attendees)
• Reviewer — IEEE ITSC, ACM e-Energy