Professor · Computer Science & Engineering · University of Nevada, Reno

Sushil J. Louis

Director, Evolutionary Computing Systems Lab (ECSL)

I work in Genetic Algorithms, Evolutionary Computing and their applications to AI, Machine Learning, and Optimization. My lab builds simulation-based adaptive training systems for naval operators, autonomous surface vessel path planners, cybersecurity training games, and evolves AI for real-time strategy games. We investigate interaction design for controlling large numbers of heterogeneous, semi-autonomous agents.



Nevada AI Research Institute (NAIRI)

I explain how AI works and help Nevada organizations use AI responsibly to advance research, education, economic development, and public benefit. I am especially interested in how we can use AI to accelerate scientific discovery and innovation. My unnofficial web page for NAIRI with current AI projects at UNR, funding opportunities, and other news.

Contact

📍 WPEB 409 · UNR, Reno NV 89557

📞 (775) 784-4315

✉️ sushil@unr.edu


ECSL Lab

ecsl.cse.unr.edu

youtube.com/@ecsllab


Education

Ph.D., Indiana University, 1993

M.S. / B.S., Delhi University


Publications

Google Scholar ↗

Recent Publications List

Evolutionary Computing Systems Lab
Evolutionary Computing Systems Lab (ECSL)
Directed by Dr. Sushil J. Louis · Department of Computer Science & Engineering · University of Nevada, Reno
ecsl.cse.unr.edu  ·  youtube.com/@ecsllab

Evolutionary Computing Systems Lab · ECSL

Current Research Projects Adaptive training · Autonomous navigation · Game AI · Cybersecurity

Ship bridge VR simulation

Featured · ONR-Funded

Adaptive Training for Nautical Rules of the Road

We designed and built a ship driving simulation trainer that uses knowledge tracing to adapt scenario difficulty in real time. A comparative study showed adaptive training is statistically significantly more effective (p < 0.0001), with 73% of students preferring it. The system trains naval officers on COLREGs — the international rules governing ship encounters — with scenarios set in Singapore and San Diego.

Read the paper →
Velocity obstacle cones for autonomous ship navigation

Autonomous Navigation

VORRT-COLREGs: Velocity Obstacles for Autonomous Surface Vessels

VORRT-COLREGs combines velocity obstacles (VO) with rapidly-exploring random trees (RRT) to plan COLREGs-compliant trajectories for autonomous surface vessels in dynamic multi-ship environments. Published in IEEE Robotics and Automation Letters.

IEEE paper →
TAISER cybersecurity training game lobby

Serious Games · Cybersecurity

TAISER: Cybersecurity Training Game

TAISER is a multiplayer Unity-based cybersecurity training game where human and AI players take WHITEHAT or BLACKHAT roles defending or attacking a city network. A CyberAI teammate provides real-time firewall rule recommendations to guide player learning.

Target angle recognition serious game

Serious Games · Naval Training

Serious Game for Target Angle Recognition

A simulation-based game for training Naval Surface Warfare Officers to rapidly identify target angle — the bearing of a ship relative to an observer. Combines realistic 3D ship rendering with adaptive difficulty. Presented at IEEE CoG 2024.

IEEE paper →
StarCraft II RTS micro co-evolution

Game AI · Evolutionary Computing

Co-evolving RTS Micro in StarCraft II

Using potential field-based co-evolutionary algorithms to develop sophisticated unit micro for StarCraft II. Recent work investigates NEAT-based neuroevolution and multi-objective approaches for generalizable, emergent combat tactics.

More ECSL projects →
UAV mesh network topology visualization

Evolutionary Computing · Networks

Evolving Dynamically Reconfiguring UAV Mesh Networks

Genetic algorithms evolve dynamic topologies for UAV-hosted mesh networks, optimizing communication coverage and reliability under changing conditions. Presented at IEEE Congress on Evolutionary Computation, 2020.

See publication →

Ph.D. students interested in game AI, adaptive training, or autonomous systems: contact me  ·  ecsl.cse.unr.edu

Selected Recent Publications

Latest Papers See Google Scholar for the full list

2025
Evaluating Adaptive Training for Nautical Rules of the Road
A. Dutta & S.J. Louis · Lecture Notes in Computer Science, vol. 15812 (Springer) · ONR N00014-22-1-2122
Link →
2024
A Serious Game for Target Angle Recognition
K. DiArchangel & S.J. Louis · IEEE Conference on Games (CoG 2024), pp. 1–4
IEEE →
2022
VORRT-COLREGs: A Hybrid Velocity Obstacles and RRT Based COLREGs-Compliant Path Planner for Autonomous Surface Vessels
R. Dubey & S.J. Louis · IEEE Robotics and Automation Letters
IEEE →
2020
Evolving Dynamically Reconfiguring UAV-hosted Mesh Networks
R. Dubey, S.J. Louis, et al. · IEEE Congress on Evolutionary Computation (CEC 2020)
Scholar →
2019
Comparing Three Approaches to Micro in RTS Games
R. Dubey, S.J. Louis, A. Gajurel, S. Liu · IEEE CEC 2019, pp. 777–784
Scholar →
2018
Neuroevolution for RTS Micro
A. Gajurel, S.J. Louis, D. Mendez, S. Liu · IEEE Conference on Computational Intelligence and Games (CIG)
Scholar →
2016
Evolving Effective Micro Behaviors in Real-Time Strategy Games
S. Liu, S.J. Louis, C. Ballinger · IEEE Transactions on Computational Intelligence and AI in Games
IEEE →