Dr. Wang is a research faculty at the Institute of Transportation Studies (ITS), UC Berkeley, US. Her focus is on deep learning algorithms and applications for autonomous vehicles. As a team leader of the machine learning group, she leads projects on learning human-like driving behaviors, decision-making strategies, intention prediction, and motion planning, based on deep learning methods such as Imitation Learning, Reinforcement Learning, Inverse Reinforcement Learning, Generative Adversarial Learning, Meta-Learning, Semi-supervised learning, etc. She also collaborates with industries on projects such as intelligent traffic control and advanced vehicular technology assessment. Some other prior work included cooperative collision warning system, big data analysis on vehicle driving patterns, crash data analysis, road safety evaluation, etc.
1.Human-like behavior learning based on Imitation Learning and Adversarial Inverse Reinforcement Learning 2.Policy generalization based on Meta-learning and Semi-supervised Learning 3.Decision making, trajectory planning, and maneuver control for autonomous driving 4.Pedestrian intention prediction 5.Intelligent traffic signal control at intersections 6.Traffic simulation platform development for microscopic interaction among vehicles
Emdad Khan is Chairman of InternetSpeech which he founded with the vision to develop innovative technology for accessing information on the internet anytime, anywhere, using just an ordinary telephone and the human voice. He is a Faculty at Maharishi University of Management, Iowa, USA and a Research Professor at Southern University, Louisiana, USA. He holds 23 patents and published over 75 journal and conference papers on intelligent internet, natural language processing/understanding, machine learning, big data, bioinformatics, software engineering, neural nets, fuzzy logic, intelligent systems and more. He has developed the prototype of voice internet and semantic engine using brain-like approach.