School of Engineering

Showing 21-30 of 58 Results

  • Steven Feng

    Steven Feng

    Ph.D. Student in Computer Science, admitted Autumn 2022

    BioI'm a 2nd-year Stanford Computer Science PhD student and NSERC PGS-D scholar, working with the Stanford AI Lab and Stanford NLP Group. I am co-advised by Michael C. Frank and Noah Goodman and am part of the Language & Cognition (LangCog) and Computation & Cognition (CoCo) Labs. Previously, I was a master's student at Carnegie Mellon University (CMU) and an undergraduate student at the University of Waterloo.

    My ultimate goal is to blend knowledge from multiple disciplines to advance AI research, specifically by teaching machines how to understand and generate human language and vision. I have explored ways to improve the controllability of language and visual generation models, incorporate and assess their reasoning capabilities, and integrate structured and multimodal information to enhance them. I am also exploring psychologically and cognitively-inspired methods to close the gap between human and LLM learning while shedding further light on human cognitive models and our efficient language acquisition capabilities.

    I worked with Eduard Hovy at CMU's Language Technologies Institute and Malihe Alikhani at the University of Pittsburgh on research projects involving language generation, semantics, and data augmentation. Earlier, I worked at the University of Waterloo with Jesse Hoey.

    My research contributions have been recognized with several publications at major conferences and a best paper award at INLG 2021. I am also an Honorable Mention for the Jessie W.H. Zou Memorial Award and CRA Outstanding Undergraduate Researcher Award.

    I am a co-instructor for the Stanford CS25 Transformers course, and mentor and advise several students. I also led the organization of CtrlGen, a controllable generation workshop at NeurIPS 2021, and was involved in the GEM benchmark and workshop for NLG evaluation.

    In my free time, I enjoy gaming, playing the piano and guitar, martial arts, and table tennis. I am also the founder and president of the Stanford Piano Society.

  • Richard Fikes

    Richard Fikes

    Professor (Research) of Computer Science, Emeritus

    BioRichard Fikes has a long and distinguished record as an innovative leader in the development of techniques for effectively representing and using knowledge in computer systems. He is best known as co-developer of the STRIPS automatic planning system, KIF (Knowledge Interchange Format), the Ontolingua ontology representation language and Web-based ontology development environment, the OKBC (Open Knowledge Base Connectivity) API for knowledge servers, and IntelliCorp's KEE system. At Stanford, he led projects focused on developing large-scale distributed repositories of computer-interpretable knowledge, collaborative development of multi-use ontologies, enabling technology for the Semantic Web, reasoning methods applicable to large-scale knowledge bases, and knowledge-based technology for intelligence analysts. He was principal investigator of major projects for multiple Federal Government agencies including the Defense Advanced Research Projects Agency (DARPA) and the Intelligence Community’s Advanced Research and Development Activity (ARDA).

  • Chelsea Finn

    Chelsea Finn

    Assistant Professor of Computer Science and of Electrical Engineering

    BioChelsea Finn is an Assistant Professor in Computer Science and Electrical Engineering at Stanford University, and the William George and Ida Mary Hoover Faculty Fellow. Professor Finn's research interests lie in the ability to enable robots and other agents to develop broadly intelligent behavior through learning and interaction. Her work lies at the intersection of machine learning and robotic control, including topics such as end-to-end learning of visual perception and robotic manipulation skills, deep reinforcement learning of general skills from autonomously collected experience, and meta-learning algorithms that can enable fast learning of new concepts and behaviors. Professor Finn received her Bachelors degree in Electrical Engineering and Computer Science at MIT and her PhD in Computer Science at UC Berkeley. Her research has been recognized through the ACM doctoral dissertation award, an NSF graduate fellowship, a Facebook fellowship, the C.V. Ramamoorthy Distinguished Research Award, and the MIT Technology Review 35 under 35 Award, and her work has been covered by various media outlets, including the New York Times, Wired, and Bloomberg. Throughout her career, she has sought to increase the representation of underrepresented minorities within CS and AI by developing an AI outreach camp at Berkeley for underprivileged high school students, a mentoring program for underrepresented undergraduates across three universities, and leading efforts within the WiML and Berkeley WiCSE communities of women researchers.