Lokesh Das

Overview

Dr. Lokesh Das’s current research focuses on developing novel algorithms for the next-generation traffic control system for autonomous vehicles utilizing modern deep learning and vehicle-to-everything (V2X) communication technologies to reduce traffic congestion and enhance traffic efficiency and safety. Dr. Das’s research extensively uses modern reinforcement learning algorithms to provide novel solutions to complex problems in real-world traffic environments.

Academic Interests and Expertise

Education:

• Ph.D. in Computer Science, University of Memphis, 2024
• MS in Computer Science, University of Memphis, 2022

Specialization:

• Intelligent Transportation Systems
• Machine Learning, Deep Learning, Reinforcement Learning

Areas of Research Interest

• Intelligent Transportation Systems
• Connected and Autonomous Vehicles
• Vehicle-to-Everything (V2X) Communication
• Reinforcement Learning
• Deep Learning
• Computer Vision
• Speech Emotion Recognition
• Cybersecurity for Autonomous Vehicles

Areas of Teaching Interest

• CS 898 Deep Learning (Fall 2024)

Publications

1. Yadavalli, Sushma Reddy, Lokesh Chandra Das, and Myounggyu Won. “RLPG: Reinforcement Learning Approach for Dynamic Intra-Platoon Gap Adaptation for Highway On-Ramp Merging. International Conference on Intelligent Robots and Systems (IROS), 2023
2. Abbasi, Jibran Ali, Navid Mohammad Imran, Lokesh Chandra Das, and Myounggyu Won. “Watchped: Pedestrian crossing intention prediction using embedded sensors of smartwatch. International Conference on Intelligent Robots and Systems (IROS), 2023
3. Das, Lokesh Chandra, Dipankar Dasgupta, and Myounggyu Won. “Intelligent Adaptive Electric Vehicle Motion Control for Dynamic Wireless Charging.” 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2023.
4. Das, Lokesh Chandra, and Myounggyu Won. “Saint-acc: Safety-aware intelligent adaptive cruise control for autonomous vehicles using deep reinforcement learning.” International Conference on Machine Learning (ICML), 2021
5. Das, Lokesh, and Myounggyu Won. “D-ACC: Dynamic Adaptive Cruise Control for Highways with Ramps Based on Deep Q-Learning.” IEEE International Conference on Robotics and Automation (ICRA), 2021
6. Das, Lokesh Chandra, Muhammed Tawfiqul Islam, and Syed Faisal Hasan. “A Generalized Internet of Things (IoT) Framework for Serving Multiple Applications.” International Conference on Internet Applications, Protocols and Services (NETAPPS2015), 2015

Professional Experience

• Assistant Professor, School of Computing, Wichita State University, Wichita, KS, 8/2024 – Present
• Software Engineer, Samsung R&D Institute Bangladesh Ltd, 03/2017 – 04/2018

Awards and Honors

• Carnegie R1 Doctoral Fellowship, University of Memphis (2019 – 2021)
• Graduate Student Association Travel Grant, University of Memphis (2023)
• College of Arts and Science Travel Grant, University of Memphis (2023)
• IROS Travel Grant (2023)

Areas of Service

Referee:

• IEEE Robotics and Automation Letters (April-22, Sep-22, Sep-23)
• IEEE Symposium Series on Computational Intelligence (SSCI)
• IEEE Congress on Evolutionary Computation (ECE)
• IEEE International Conference on Intelligent Transportation Systems (ITSC) 2024

Additional Information

Membership:

• IEEE

Research:

Dr. Das is looking for multiple Ph.D. students to join his research group. Students with strong programming skills in Python and a solid background in machine learning are encouraged to contact Dr. Das at lokesh.das@wichita.edu with their CVs.