Sol Zilberman

Sol Zilberman

PhD Student in Computer Science

Michigan State University

Research

My research focuses on assurance for learning-enabled safety-critical systems (e.g., autonomous vehicles).

Research Topics:

  • Evolutionary Computation
  • Trustworthy Autonomous Vehicles
  • Deep Learning
  • Reinforcement Learning
  • High Assurance Computing
  • Game Theory
  • Computer Graphics
  • Adaptive Systems

Publications

"No Free Lunch" when using Large Language Models to Verify Self-Generated Programs

Sol Zilberman, and Betty H.C. Cheng

4th International Workshop on Artificial Intelligence in Software Testing, AIST 2024, Toronto, Canada, May 28, 2024, (IEEE), May 2024

[Paper]

SafeDriveRL: Combining Non-cooperative Game Theory with Reinforcement Learning to Explore and Mitigate Uncertainty for Autonomous Vehicles

Kenneth Chan, Sol Zilberman, Nick Polanco, Joshua E. Siegel, and Betty H.C. Cheng

19th IEEE/ACM Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2024, Lisbon, Portugal, April 15-16, 2024, (ACM), April 2024

[Paper]

Anunnaki: A Modular Framework for Developing Trusted Artificial Intelligence

Michael Austin Langford, Sol Zilberman, and Betty H.C. Cheng

ACM Transactions on Autonomous and Adaptive Systems, (ACM), March 2024

[Paper]

Teaching

CSE 435 - Software Engineering (Fall 2024, Fall 2025)
CSE 325 - Computer Systems (Spring 2024, Spring 2025)
CSE 231 - Introduction to Programming (Fall 2023, Summer 2024)

Education

Doctor of Philosophy, Computer Science

(Expected 2026)

Michigan State University

Advisor: Dr. Betty H.C. Cheng

Awards: Distinguished Engineer Fellowship Recipient

Bachelor of Science, Mathematics & Computer Science

Minor in Philosophy

2018 - 2022

Purdue University

Awards: Freshman Honors Society, National Honors Society

Experience

Machine Learning Engineer Intern

(Summer 2025)

Meta

Facebook trust and safety team.

Research Assistant

(August 2022 - May 2023)

Michigan State University

Researched state of the art techniques for the development and deployment of trustworthy learning-enabled autonomous systems, with focus on adaptive unmanned aerial vehicles employing object detection models.

Automation Engineer Intern

(Summer 2022)

Ironclad

Expanded automation framework and increased regression detection for over 500,000 yearly user events via custom mobile testing suite.

Security Engineer Intern

(Summer 2021)

Accenture

Improved internal security infrastructure through development of data-driven Python applications, increasing security incident detection rate and minimizing response time.

Software Engineer Intern

(Summer 2020)

Perflo

Developed and implemented a data analytics dashboard using GraphQL API, Postgresql, and a custom React library for a B2B project-management application.