Kapil was a graduate student in Electrical & Computer engineering. His research focuses on developing AR based traffic safety system. These systems will work on fusing real-time video and IMU sensing on-board smart glasses like Google Glass, ODG-R7 etc. to come up with a collision prediction and prevention system. He is a coding geek and helps the group in various aspects of embedded systems, from bringing up the hardware to write software for it. His other project is developing GPS-less (IMU based) tracking systems which our group works on with Texas Department of Transportation (TxDot). His other interests include Artificial Intelligence, developing cool things with chip size computers like Raspberry PI.

Originally from Houston, Arthur earned his Bachelor’s in Aerospace Engineering at the University of Texas, Austin. He has a particular interest in control systems and automation. He has been tinkering with UAVs since he started school at UT, and tries to apply everything he learns towards experimenting with and improving UAVs. He is also cofounder of a drone-based delivery startup.

Ofer’s research concerns developing a control supervisor for UAVs. By using classical reachability techniques he is able to predict what state the aircraft will be in and assist in preventing it from getting into unsafe scenarios when it’s controlled either by a human operator or by its autopilot. His goal is to use this control system to allow him to use the UAV in real-time flood monitoring. In this project machine-learning methods are used to tackle the computational challenges involved in the real-time reachability problem.

Alexander was a graduate student in Operations Research at the University of Texas, Austin. He currently works on network traffic state estimation, and Inertial-Measurement-Unit based traffic flow monitoring.

Vishnu earned his Bachelors at The University of Texas at Austin majoring in Aerospace Engineering with a certification in Computational Engineering. His interest areas include programming, experimenting with RC aircrafts, and playing football.

Tian was a postdoctoral scholar working on real-time traffic estimation and monitoring. She is directly involved in software and hardware development for Inertial Measurement Unit (IMU) based wireless traffic sensing system. Her research uses techniques like signal processing and sensor data fusion. The applications of her research includes real-time speed estimation, trajectory estimation and map matching using wireless sensing system. On parallel, Tian works on viability-constrained solutions to Hamilton-Jacobi equations, with applications to autonomous vehicles.

Sadegh was a visiting scholar working on a new type deflection measuring device for non-invasive pavement monitoring, based on high precision LIDARs, accelerometers and ring laser gyroscopes. He also focuses on autonomous vehicles, and on pavement serviceability rating measurements. His research interests include dynamics, vibration, automotive systems, optimization, uncertainty analysis and pavement analysis. His hobbies include swimming and ping pong. He also loves discovering new cultures. He can speak Persian (mother language), English and has a basic knowledge of French and German.

Michele earned a PhD from the Department of Civil Engineering at the University of Texas at
Austin. His research involves studying and developing models and algorithms for traffic
simulations. Some of the applications of his work include the estimation and control of distributed
parameter systems. Besides traffic flow theory, his main interests consist of urban freight distribution
and congestion pricing. You can find more information about his research at:
https://www.researchgate.net/profile/Michele_Simoni3

Andrew’s research focuses on the application of UAS (unmanned aerial systems) for civil purposes. Specifically, he looked into the use of fixed wing aircraft for flash flood monitoring and data assimilation as well as quadcopter aircraft for traffic sensing. He is interested in many different aerospace technologies (high-power rocketry, space systems technologies, UAS, etc.), and hopes to make a meaningful contribution to the aerospace engineering field that helps to solve some of the greatest technological challenges. For hobbies, he likes to learn new things (this involves lots of extracurricular activities), work out, swim, play guitar, spend as much time outside as possible, and play with his baby daughter.

Abduallah earned his PhD in Electrical and Computer Engineering from the University of Texas, Austin. He is an experienced automotive R&D engineer. His research interests include deep learning, sensors data fusion, and computer vision. His research involves human in the loop control of partially autonomous system, with a current focus on traffic safety. Abduallah worked in multiple international companies and holds a patent in deep learning. Website: https://www.abduallahmohamed.com/