Institute for Human-Centered Artificial Intelligence (HAI)
Showing 11-20 of 182 Results
Associate Professor of Operations, Information and Technology at the Graduate School of Business and, by courtesy, of Electrical EngineeringOn Leave from 03/15/2021 To 12/31/2021
Current Research and Scholarly Interests1) Healthcare management: I am interested in improving healthcare delivery using data-driven modeling and decision-making.
2) Network models and message-passing algorithms: I work on graphical modeling ideas motivated from statistical physics and their applications in statistical inference.
3) Personalized decision-making: I work on machine learning and statistical challenges of personalized decision-making. The problems that I have worked on are primarily motivated by healthcare applications.
Professor of Developmental Biology, of Computer Science, of Pediatrics (Genetics) and of Biomedical Data Science
Current Research and Scholarly InterestsDr. Bejerano, co-discoverer of ultraconserved elements, studies the Human Genome. His research focuses on genome sequence and function in both humans and related primate, mammalian and vertebrate species. He is deeply interested in mapping both coding and non-coding genome sequence variation to phenotype differences, and in extracting specific genetic insights from high throughput sequencing measurements, in the contexts of development and developmental abnormalities.
Associate Professor of Medicine (Primary Care and Population Health) and Senior Fellow at the Woods Institute for the EnvironmentOn Partial Leave from 09/14/2020 To 07/05/2021
Current Research and Scholarly InterestsEffect of global health policies on health of individuals in developing countries, global health, HIV and TB.
Professor of Pediatrics (Genetics) at the Lucile Salter Packard Children's Hospital and, by courtesy, of Genetics
Current Research and Scholarly InterestsMy research is focused on the diagnosis, discovery and delineation of rare genetic conditions with a focus of neurodevelopmental disorders. This work includes the application of novel computational methods and multi-omics profiling (whole genome sequencing, RNA sequencing, metabolomics). I additionally participate in an interdisciplinary project to develop induced pluripotent stem cell (iPSC) models of genetic neurodevelopmental disorders..
Associate Professor of Computer Science
BioMichael Bernstein is an Associate Professor of Computer Science and STMicroelectronics Faculty Scholar at Stanford University, where he is a member of the Human-Computer Interaction group. His research focuses on the design of social computing and crowdsourcing systems. Michael has received eight best paper awards at premier computing venues, and he has been recognized with an NSF CAREER award and an Alfred P. Sloan Fellowship. His Ph.D. students have gone on both to industry (e.g., Adobe Research, Facebook Data Science, entrepreneurship) and faculty careers (e.g., Carnegie Mellon, UC Berkeley). Michael holds a bachelor's degree in Symbolic Systems from Stanford University, as well as a master's degree and a Ph.D. in Computer Science from MIT.
Nomellini and Olivier Professor in the Graduate School of Education
Current Research and Scholarly InterestsStudying the Impact of a Mathematical Mindset Summer Intervention, HapCaps: Design and Validation of Haptic Devices for improving Finger Perception (with engineering & neuroscience) The effectiveness of a student online class (https://lagunita.stanford.edu/courses/Education/EDUC115-S/Spring2014/about) (NSF). Studies on mathematics and mindset with Carol Dweck and Greg Walton (various funders). Studying an online network and it's impact on teaching and learning (Gates foundation)
Assistant Professor of Computer Science
BioJeannette Bohg is an Assistant Professor of Computer Science at Stanford University. She was a group leader at the Autonomous Motion Department (AMD) of the MPI for Intelligent Systems until September 2017. Before joining AMD in January 2012, Jeannette Bohg was a PhD student at the Division of Robotics, Perception and Learning (RPL) at KTH in Stockholm. In her thesis, she proposed novel methods towards multi-modal scene understanding for robotic grasping. She also studied at Chalmers in Gothenburg and at the Technical University in Dresden where she received her Master in Art and Technology and her Diploma in Computer Science, respectively. Her research focuses on perception and learning for autonomous robotic manipulation and grasping. She is specifically interesting in developing methods that are goal-directed, real-time and multi-modal such that they can provide meaningful feedback for execution and learning. Jeannette Bohg has received several awards, most notably the 2019 IEEE International Conference on Robotics and Automation (ICRA) Best Paper Award, the 2019 IEEE Robotics and Automation Society Early Career Award and the 2017 IEEE Robotics and Automation Letters (RA-L) Best Paper Award.