About

Steven H. Wang is a talented computer science undergraduate with a passion for machine learning and artificial intelligence. He is currently working as a Research Intern and Machine Learning Research Engineer at the Center for Human-Compatible AI. Steven has gained extensive experience through his past roles, including his position as an Undergrad Research Assistant at UC Berkeley's Interact Lab. Here, he worked on engineering projects such as "Probabilistically Safe Robot Planning with Confidence-Based Human Predictions," which was published at Robotics: Science and Systems 2018. Steven's contributions included developing real-time human trajectory predictions based on Hidden Markov Model over reward functions and Boltzmann rationality coefficients. He also conducted internal experiments evaluating the pros and cons of estimating the Boltzmann rationality coefficients of human models rather than assuming fixed rationality. In addition, Steven has worked as a Software Engineering Intern at Nefeli Networks, where he made open-source contributions to Berkeley Extensible Software Switch (BESS), NetBricks, tcpdump, and gopacket. He also implemented a Layer 7 Load Balancer and RED queue in C++, as well as C++ bindings for OpenStack Compute and Network APIs. Steven holds a Bachelor of Science in Electrical Engineering and Computer Science from the University of California, Berkeley, where he graduated in 2018. He also participated in the Williams-Mystic Maritime Studies Program in 2016. With 4.87 years of relevant experience, Steven is a skilled research scientist and machine learning expert. He is passionate about leveraging his skills and knowledge to drive innovation in the field of AI and create solutions that can positively impact society.