Academic Credentials
  • Ph.D., Electrical Engineering, University of Texas, Dallas, 2023
  • M.S., Electrical Engineering, University of Texas, Dallas, 2023
  • B.S., Electrical Engineering, University of Texas, Dallas, 2019
Licenses & Certifications
  • Certified Fire and Explosion Investigator (CFEI)
Professional Honors
  • Excellence in Education Doctoral Fellowship, University of Texas as Dallas, 2020-2023.
  • Best Paper Award, Joint Workshop on CPS and IoT Security and Privacy (CPSIoTSec), in conjunction with the ACM Conference on Computer and Communications Security, 2021, Seoul, South Korea.
Professional Affiliations
  • Institute of Electrical and Electronics Engineers (IEEE)
  • Society of Automotive Engineers (SAE)
  • National Association of Fire Investigators (NAFI)

Dr. Sleiman Safaoui's expertise is in electrical and computer systems, including robotics, autonomy, advanced driver assistance systems (ADAS), automotive and consumer electronics, electric vehicles (EVs), and other battery-powered devices. His work focuses on safety evaluations, failure analysis, design reviews, testing, and analysis.

Dr. Safaoui works on automotive projects involving electrical and electronic systems, including infotainment, communication, ADAS technologies, airbag and occupant protection systems, and vehicle charging systems. His experience includes EV charging systems, charging accessories, on-board chargers, DC/DC converters, battery charging circuits, and related charging protocols and infrastructure. He reviews design documents, inspects field failures, and performs targeted testing and analysis.

Dr. Safaoui also performs analysis and testing of battery systems, consumer electronics, and commercial robotic systems. He conducts failure analyses and fire investigations involving automotive systems and consumer devices and supports intellectual property infringement litigation.

Dr. Safaoui's research background focuses on aerial and ground robotic system design and control through complex and intelligent algorithms. His work spans the design and assembly of battery-powered robotic platforms with various sensing modalities, including cameras and LiDAR, as well as the deployment of autonomy stacks using novel risk-based planning and decision-making algorithms based on control theory, statistics, optimization, and machine learning.

Prior to joining Exponent, Dr. Safaoui worked in the Controls, Optimization, and Networks Lab at The University of Texas at Dallas, where he developed motion planning algorithms and managed the lab's single- and multi-agent robotic platforms. Dr. Safaoui also worked at Mitsubishi Electric Research Laboratories, where he developed and implemented solutions for autonomous vehicle decision-making and multi-agent motion planning.