Stanford HAI Welcomes Graduate, Postdoc Fellows
The Stanford Institute for Human-Centered AI is pleased to welcome its 2023/24 graduate and postdoctoral fellows. This year’s fellows comprise scholars from sociology, law, art, computer science, mechanical engineering, anthropology, psychology, ethics, ecology, and more.
The Stanford HAI fellowship programs encourage interdisciplinary research, facilitate new collaborations, and seek to grow the community of researchers interested in human-centered approaches to AI. In the two programs, these scholars will be able to learn from each other and HAI’s leading faculty, participate in enriching discussions, and develop new projects and research.
“These fellowships allow a cross-seeding of ideas from all disciplines,” says HAI Director of Research Programs Vanessa Parli, who oversees the program. “The hope is these students will challenge each other’s way of thinking, broaden their understanding of the role and impact of artificial intelligence, and share this broader understanding as they grow their career as future AI leaders.”
David Broska: David is a third-year PhD student in sociology who is also pursuing an MS in statistics. After earning his BA in sociology, politics, and economics at Zeppelin University in Germany, he completed an MSc in social research methods at the London School of Economics. His research interests center around the ethics of computational research with big data and AI, open science, social inequality, and social policy.
Matt DeButts: Matt is a PhD student in communication and Knight-Hennessy Scholar. A former Beijing-based journalist from 2014 to 2019, Matt is interested in how government and media institutions shape public beliefs in the United States and China. Matt holds a BA in law, jurisprudence and social thought from Amherst College and an MA in China studies from Peking University. His journalistic work has been published in the Los Angeles Times, Vox, Foreign Policy, and elsewhere.
Hank Gerba: Hank is a PhD student in the Department of Art & Art History’s Film and Media Program. Their dissertation proposes a media theoretical investigation of aliasing, using it to explore various contemporary conversations in the study of digital media.
Neel Guha: Neel is a fourth-year JD-PhD candidate in computer science, advised by Associate Professor Chris Ré, and a graduate student fellow in the Stanford RegLab.
Priscilla Guo: Priscilla is a third-year law student who has served as co-president of the Asian and Pacific Islander Law Students Association and articles editor of the Stanford Law Review. Most recently, she was a policy advisor for the Day One Project, where she curated, developed, and advised science and technology policy proposals to inform the Biden-Harris administration and Congress. Previously, she served as a representative on the New York City Youth Board and has worked in both technology and public policy roles at Facebook, Microsoft, Electronic Frontier Foundation, and NASA Jet Propulsion Laboratory. Priscilla holds an MS in global affairs from Tsinghua University as a Schwarzman Scholar, an MSc in the social science of the internet from Oxford University as a Clarendon Scholar, and a BA in technology, policy, and society with a secondary in women, gender, and sexuality studies from Harvard University.
Mohammadmahdi Honarmand: Mohammadmahdi is a PhD candidate in mechanical engineering doing interdisciplinary research at the intersection of ME, AI, and healthcare.
Jeongyeon Kim: Jeongyeon is a PhD candidate in computer science specializing in human-computer interaction. Her research primarily revolves around enhancing knowledge communication through video media. Before pursuing her doctoral studies at Stanford, she obtained her master’s degree at the Korea Advanced Institute of Science and Technology. Her research findings and innovations have been recognized and published in conferences such as CHI, DIS, and AAAI.
Ragav Manimaran: Ragav is a Knight-Hennessy Scholar. He earned a bachelor’s degree in medical physics and bioengineering and a medical degree from University College London. As a practicing physician in the UK, he has worked across emergency medicine, internal medicine, and general surgery while contributing on the front line to the National Health Service’s response to COVID-19. Ragav has published international peer-reviewed publications spanning AI, digital health, and medical physics. In Europe, he worked with the World Health Organization to identify essential medical technologies for low-resource settings and supported Roche Diagnostics with cardiovascular projects. Ragav co-founded Kickstart, London’s first cross-university pre-accelerator, and helped develop, fund, and launch several student startups.
Bethanie Maples: Bethanie is pursuing a PhD in the Graduate School of Education’s Learning Sciences and Technology Design Program. Her research focuses on embodied AI and NLP in education. She ran product for teams at Google AI and Google X, and advises the OECD, UNESCO, and philanthropic foundations on AI policy, education, and technology. She’s a startup founder, and likes sailing and science fiction.
Desire Immaculate Uwera Nalukwago: Desire is a PhD student in biology in the Mordecai Lab. She started research in an undergraduate behavioral ecology lab studying life history trade-offs, where she gained an interest in applying these concepts to disease ecology. She is passionate about quality healthcare, bridging the gap between scientists and communities through communication, and improving STEM education in low- and middle-income countries.
Favour Nerrise: Favour Nerrise is a second-year PhD candidate in electrical engineering. Her doctoral research is supported by the Stanford Graduate Fellowship, EDGE Fellowship, and NeuroTech Training Program Fellowship. She holds bachelor’s degrees in computer engineering and mathematics and minors in Arabic and global engineering leadership from the University of Maryland, College Park. At Stanford, she serves as a student officer of the Graduate Students in Electrical Engineering committee and as a member of the Electrical Engineering Culture, Equity, and Inclusion committee. She is also a peer academic coach for the Center for Teaching & Learning, and an officer in the Black Graduate Student Association and the Black Engineering Graduate Student Association. Her current research focus is in using geometric connectomics and deep learning to predict AI-driven, digital biomarkers of neurological disorders. She is also currently a PhD resident at SandboxAQ, a next-gen AI + quantum technology company, and does neurotechnology consulting for startups in Silicon Valley and Canada. Favour is dedicated to building communities, teaching, and leadership engineering. In her spare time, she loves going to Stanford athletics home games, speed reading science fiction and fantasy books, cooking varied cuisines, trying new outdoor and water sports, and listening to Dutch hip-hop.
Nick Okafor: Nick, a strategist and design researcher, is a PhD student in management science and engineering. His research focuses on the practice and pedagogy of responsible innovation. He puts research into practice as the founder of trubel&co, a nonprofit championing the next generation to tackle complex societal problems using equitable data analytics, responsible technology, and inclusive design to reshape society for the better. Previously, Nick was a senior associate at Sidewalk Labs (Google’s urban innovation arm), where he drove commercialization for emerging products that improve quality of life in cities. He advocates for a radical reimagining of the tools used to create a more just and equitable society, and is committed to ensuring the digital revolution can increase opportunity, mitigate harm, and create liberatory futures for all.
Benjamin Perez: Benjamin is a PhD student in anthropology interested in the big question of what it means to be human in the age of generative AI.
Liam Rahman: Liam is an MBA-MA Education student and Knight-Hennessy Scholar. Prior to Stanford, he co-founded, built, and led Equal Education Partners, a leading UK-based education management company. As an undergraduate, Liam studied philosophy, politics, and economics at Yale-NUS College (Singapore) and Yale University.
Anka Reuel: Anka is a PhD student in computer science at the Stanford Intelligent Systems Laboratory, advised by Associate Professor Mykel Kochenderfer. Her work focuses on operationalizing responsible AI (RAI). Anka’s goal is to help organizations understand the complex RAI landscape and enable them to develop and deploy socially beneficial AI systems. Anka is further involved in AI governance efforts. Most recently, she worked jointly with members of the Center for the Governance of AI on design considerations for AI ethics boards to reduce risks from AI systems. She is also an advocate for more collaboration between the field of technical AI safety and AI governance and is a founding member of KIRA, an independent German think tank advocating for more collaboration in the field of responsible AI. Anka is a fellow at the Carnegie Council for Ethics in International Affairs, and has won multiple awards for her work, including the University of Pennsylvania’s Outstanding Academic Award 2022. Anka is a first-generation, low-income student and a careleaver. She advocates in various roles to improve the conditions and opportunities for both of these groups. In her spare time, she is an avid traveler: Anka has visited 52 countries and lived in 10 of them. She is also a casual ultimate frisbee player and a hardstyle enthusiast.
David Rose: David is a PhD student in psychology working in developmental and cognitive areas. His research is focused on categorization and causation. David draws on a range of tools to address questions on these topics and is especially interested in how large language models can inform our understanding of categorization and causal judgments in adults and children.
Juliette Woodrow: Juliette, a PhD student in computer science, is passionate about helping individuals learn computer science, as she believes that mastering this skill can open doors to numerous opportunities across disciplines. Her research predominantly centers on creating tools and resources that facilitate effective teaching and learning of computer science for both educators and students. Beyond her research, Juliette enjoys teaching computer science courses whenever she can – a passion that was ignited during her undergraduate and graduate studies. Outside the realm of academia, she spends her time reading, hiking, listening to podcasts, and practicing or teaching pilates.
Michael Wornow: Michael is a fourth-year PhD student in computer science co-advised by professors Nigam Shah and Chris Ré. His research focus is on developing and operationalizing AI models in healthcare, with a particular interest in making large language models more factual and capable of executing full workflows. Michael graduated summa cum laude from Harvard in 2020 and is supported by an NSF Graduate Research Fellowship.
Katie Wu: Katie is a PhD student in the Emmett Interdisciplinary Program in Environment and Resources (E-IPER). Prior to Stanford, she studied data science and AI for product innovation at Duke University, where she obtained a Master of Engineering Management degree. She was a Sustainability Graduate Intern at Lyft Inc., where she completed and rebuilt its 2020 Greenhouse Gas Inventory and Report and designed an air quality model forecasting potential health benefits for underserved communities from platform-wide EV adoption. Katie holds an MS in medical science from the University of Colorado School of Medicine and a BS in animal science with distinction in research from Cornell University. She is a Dean’s Graduate Scholar in the Doerr School of Sustainability and a Stanford Dalai Lama Fellow.
Mofan Zhang: Mofan is a PhD candidate in civil and environmental engineering in the Fletcher Lab. Her research integrates simulation, optimization, and AI in water resources systems planning. She has an MS in operations research from Johns Hopkins University and a BS in water resources and hydrology from Tsinghua University. In her free time, she enjoys reading science fiction novels, playing the piano, and traveling with family and friends. She is also a nature lover and passionate about small animal protection.
Yuchen Cui: Yuchen graduated with a PhD in computer science from the University of Texas at Austin in 2021. Her research interest lies in robot learning from humans, with a focus on enabling humans to efficiently teach robots with a diverse set of feedback modalities.
Dapeng Feng: Dapeng earned his PhD in hydrology at The Pennsylvania State University, where his research focused on systematically integrating machine learning and physical models for large-scale water cycle simulations and streamflow forecasting. He earned his bachelor’s degree in hydraulic engineering from Wuhan University and his master’s degree in hydrology and water resources from Peking University. His current research interests focus on synergizing AI, domain physics, and large observational data for Earth systems modeling and geoscientific knowledge discovery, with emphasis on the global water cycle and interactions between water and plant systems under climate change.
Caroline Glidden: Caroline received her undergraduate degree in ecology and evolution from the University of Colorado, Boulder. She then obtained her PhD in integrative biology, with a minor in statistics, from Oregon State University. As a graduate student, Caroline studied the community ecology of parasites and pathogens in southern African wildlife. Upon completing her PhD, she joined the Mordecai Lab, where she expanded her expertise to include understanding the impacts of global change on human infectious diseases. Through graduate school and her work in the Mordecai Lab, she has developed a great appreciation for and significant expertise in data science and computational biology. She is excited about the substantial benefits that AI will have on human health, biodiversity, conservation, and sustainable development.
Farnaz Jahanbakhsh: Farnaz is working with computer science professors Sanmi Koyejo and Michael Bernstein. She received her PhD in computer science from MIT, where she was advised by David Karger. Her research is in the field of human-computer interaction and social computing and is aimed at re-imagining the design of social information spaces such as social media and the web to achieve greater end-user empowerment. She holds an MSc in computer science from the University of Illinois at Urbana-Champaign and a BSc in computer engineering from Sharif University of Technology.
Christopher Kelly: Christopher’s research interest lies at the intersection of psychology and technology. His current research centers around the examination of digital media consumption patterns, and how such patterns reflect and shape well-being. Before joining Stanford, Christopher completed his PhD in cognitive neuroscience simultaneously at University College London and as a visiting PhD student at MIT.
Luca Vendraminell: Luca’s scientific work deals with understanding the effect of AI adoption in organizations. His research centers around four areas. First, he studies algorithmic navigation guidance in human-in-the-loop decision-making systems, delving into the interplay between algorithm outcomes and human cognitive mechanisms. Second, he explores the organizational dynamics of AI diffusion looking at social network effects. Third, he investigates AI’s innovation and design process and the creative work of data scientists. Last, he researches ways to use design thinking practice to conceptualize and execute digital transformation strategies. His work has appeared in scientific journals such as the Journal of Product Innovation Management. He was awarded the 2020 Albert Page Award for Outstanding Professional Contribution for the publication “Innovation and Design in the Age of Artificial Intelligence.”
Kaveh Waddell: Kaveh is a 2023-24 John S. Journalism Fellow and an investigative journalist at Consumer Reports, where he uses documents, data, and rigorous testing to reveal corporate harms and overreach. Much of his reporting focuses on digital rights and environmental justice. In 2022, his data-driven investigation into the harmful effects of Amazon warehouses on surrounding communities was a finalist for the Livingston Award and a Deadline Club award. Previously, Kaveh co-wrote the Axios Future newsletter, reporting on developments in emerging technology such as AI, robotics, and neurotech. He was a 2018 AI Fellow at the National Press Foundation. He spent a year as a freelance journalist in Beirut, Lebanon, where he wrote about a secret effort to map Lebanon’s disappearing civil war graves. Kaveh’s career began in Washington, D.C., where he covered technology policy for National Journal and privacy and technology at The Atlantic, with a focus on the disproportionate harm of surveillance on marginalized groups.
Luwen Wan: Luwen is interested in interdisciplinary research to better understand the complexity of coupled human environment systems. Her work has focused on climate change, extreme climate events, landscape pattern evolution and their impacts on surface runoff, water quality, and ecosystem services. As a postdoctoral fellow, she will be working with Kate Maher, professor of Earth system science.
Zhecheng Wang: Zhecheng received his PhD degree in civil and environmental engineering with a minor in computer science in 2022, and MS degree in mechanical engineering in 2018, both from Stanford University. He also holds a bachelor’s degree in energy and power engineering from Tsinghua University.
Journalist in Residence
Alex Goldmark: Alex is the executive producer for Planet Money at NPR. During his time at Planet Money, the team launched its weekly broadcast radio show, video shorts series, and newsletter, and won a Peabody and a duPont-Columbia award. He is exploring ways to responsibly apply AI to journalism, and for the journalism industry to respond to AI. As a 2022-23 John S. Knight Journalism Fellow, he worked with students in Stanford’s computational journalism class to prototype and study AI journalism tools including an AI chatbot based on Planet Money’s archives, a project that is ongoing.
Stanford HAI’s mission is to advance AI research, education, policy and practice to improve the human condition. Learn more.