SERC Postdocs, 2026-2027

Dr. Natalie Collina

Dr. Natalie Collina is a joint SERC and MAPS postdoctoral fellow at MIT. She graduated with a PhD in Computer and Information Science from University of Pennsylvania in 2026. She loves breakfast sandwiches, karaoke, and games. Natalie’s research focuses on algorithmic game theory and the foundations of responsible AI. She’s particularly interested in understanding repeated strategic interaction in mixed human-algorithm ecosystems.

Dr. Erik Engberg

Dr. Erik Engberg is an economist specialized in AI and the labor market. He is passionate about social science and making sense of the impact of AI. Before his PhD studies, he worked in innovation policy. His postdoctoral research agenda is focused on AI and the future of work.

Dr. Ziv Epstein

Dr. Ziv Epstein is a computational social scientist sitting between the MIT Schwarzman College of Computing and History Theory & Criticism in the School of Architecture. His current research explores how to audit the values amplified by social media ranking algorithms, and how to steer these algorithms to align with human values. Beyond social media, he is also interested in the impacts of AI on creative production in settings such as visual media and interpretative labor (e.g. divination). He was previously a postdoctoral fellow at Stanford University (2023-2025), and received his PhD from the MIT Media Lab (2023) where his dissertation focused on new ways to operationalize and measure attention on social media and implications for fighting misinformation online. He is also a practicing multimedia artist whose work has been featured in Ars Electronica, MIT Museum, and Burning Man.

Dr. José Luis Gallegos-Quezada

Dr. José Luis Gallegos-Quezada is holds a Masters in Public Administration from Harvard University and a PhD from Rotterdam School of Management, where his dissertation examined how workers and unions shape the consequences of automation and AI—from dockworkers at the Port of Rotterdam to service workers in the U.S. telecommunications industry. His research has been recognized by the Academy of Management and the Society for the Advancement of Socio-Economics. Beyond academia, he advises the International Transport Workers’ Federation on AI and automation and authored the Dockers’ AI Toolkit, a guide that helps unions negotiate the introduction of AI in the workplace. His research asks a simple but increasingly urgent question: Who gets to shape what technologies do at work? Combining qualitative fieldwork, archival research, and comparative institutional analysis, he examines how the costs and benefits of technological change are distributed.

Dr. Johannes Geith

Dr. Johannes Geith is a postdoctoral fellow at the Department of Political Science and a SERC postdoc at the MIT Schwarzman College of Computing. His research interests include AI governance and international political economy. Johannes received his PhD in political science from Stockholm University in 2026. In his dissertation he investigated the global governance of AI, focusing specifically on actor preferences, bargaining dynamics, and institutional design. In his postdoctoral research project, Johannes is working to better understand state-industry relations between states and Big Tech corporations in the age of AI and thereby contribute to scholarship in comparative and international political economy.

Dr. Sarah Gillet Schlegel

Dr. Sarah Gillet Schlegel is a SERC Wallenberg postdoctoral fellow in the Personal Robots Group in the MIT Media Lab. Her research aims to advance autonomous social robots to support interactions between people. In her work, she develops algorithms and interaction methods for social robots, while also investigating how these technologies shape people’s experiences and interactions. She received her PhD from KTH Royal Institute in Technology in Stockholm Sweden in 2024 and worked on mobile robot navigation at the Corporate Research of KUKA before joining MIT. Her work has been recognized with a prestigious Wallenberg Postdoctoral Fellowship, selection to RSS Pioneers and HRI Pioneers, and a Best Paper Award at the ACM/IEEE Human-Robot Interaction Conference.

Dr. Anna-Kaisa Kaila

Dr. Anna-Kaisa Kaila is a postdoctoral fellow at MIT Media Lab and SERC. Before joining MIT, she received her PhD at KTH Royal Institute of Technology (2026), with the dissertation focusing on the impacts of AI technologies on artist communities and how the lens of care ethics could guide the development of creative AI applications. Her current research explores the conditions of fairness at the intersections of technology and artmaking, and the futures of algorithmic literacy in creative and cultural domains. She has also previously worked internationally in artist advocacy, cultural diplomacy, and music copyright management.

Dr. Ce Li

Dr. Ce Li is a postdoctoral associate in the Laboratory for Information and Decision Systems and SERC, where she works with Professors Asu Ozdaglar and Chara Podimata. Her research spans economics, machine learning, and artificial intelligence. Her work has a focus on information design, mechanism design, game theory, and trustworthy AI, with applications to, e.g., recommender systems, AI alignment, and AI agents. She received her PhD in Economics from Boston University, where she was advised by Professor Bart Lipman, and her S.M. in Health Data Science from Harvard University.

Dr. Alicja Ostrowska

Dr. Alicja Ostrowska is a postdoctoral fellow at the MIT’s Program in Science, Technology and Society and SERC. Her research is about how computation changes scientific cultures and our understanding of life. Based on fieldwork at NASA, she studied how AI changes scientific cultures in planetary science and astrobiology, focusing on explorations of life in the universe. Before joining MIT, Alicja conducted doctoral research at Chalmers University of Technology, Gothenburg, Sweden. Her current research focuses on exploring how new simulations – synthetic data for AI – change the ways in which knowledge is produced in life sciences.

Dr. Bill Noble

Dr. Bill Noble is a researcher in the field of Computational Linguistics currently working as a SERC/WASP-HS postdoctoral fellow at the Center for Constructive Communication, a research lab hosted at the MIT Media Lab. He received my PhD in Computational Linguistics from the University of Gothenburg in 2023. He also holds a Masters in Logic from the University of Amsterdam. His work uses, statistical and machine learning modeling to investigate questions about how human language works, especially about the dynamics of meaning in natural language. He’s interested in how people collaboratively build up communicative resources in conversation, and the persistent effects of that collaboration.

Dr. Yi-Hao Peng

Dr. Yi-Hao Peng is a postdoctoral fellow at MIT CSAIL. He earned his PhD at Carnegie Mellon University’s iHuman–Computer Interaction Institute. He was advised by Jeff Bigham and Amy Pavel, and worked closely with Jason Wu. His research builds collaborative, accessible AI agents that work alongside people, with a particular focus on those with disabilities. He develops data-driven models and interaction methods that help AI systems interpret multimodal context, collaborate with users proactively without undermining their agency, and define success in ways that reflect both shared standards and individual preferences.

Dr. Virgile Rennard

Dr. Virgile Rennard is a postdoctoral associate in SERC. He received his PhD in computer science from École Polytechnique im 2025 where his dissertation focused on dialogue understanding and summarization, with applications to political discourse and meeting conversations. His research lies between the intersection of natural language processing and political science. He is particularly interested in the development of large language models (LLMs) for dialogue and debate, and in understanding how these models reflect and reproduce political and cultural biases. In addition to bias and fairness, Virgile’s research addresses the practical deployment of dialogue systems. At MIT, he will be working on leveraging LLMs and generative AI for deliberative democracy.

Dr. Erik Sandelin

Dr. Erik Sandelin is a postdoctoral fellow in the Data+Feminism Lab and SERC. As a designer and researcher, Erik makes prototypes to activate and investigate gracious modes of life. He holds a PhD in art, technology, and design from KTH Royal Institute of Technology and Konstfack in Stockholm. In his dissertation, Erik develops the concept of grace (actively not doing what you are able to do) to decouple action from force and passivity from resignation in design. He has deployed prototypes in museums, schools, and public spaces around the world. Erik is also a co-founder of interaction design and innovation studio, Unsworn. At MIT, Erik seeks to articulate a register of grace in contemporary technology design and development. When and how does it become possible to create by not using all the force at your disposal?

Dr. Ben Schwartz

Dr. Ben Schwartz is a postdoctoral associate in the Department of Linguistics and Philosophy and SERC. He received his PhD in philosophy from the University of North Carolina, Chapel Hill in 2025. Ben’s primary interests are in ethics of technology, ethics, PPE, and social & political philosophy, and his research focuses upon the impact of recent and emerging technologies on human flourishing. In his current work, he argues that the attention economy underlying recent digital technologies is an impediment to human flourishing, to autonomy, to intimate personal relationships, and to the crucial virtues that involve attention.

Dr. Jakob Stenseke

Dr. Jakob Stenseke is a postdoctoral fellow in the Algorithmic Alignment Group, hosted by Prof. Dylan Hadfield-Menell, and SERC. His interests revolve around three Ms: minds, machines, and morality. He earned his PhD in philosophy from Lund University in 2025, where he examined artificial approaches to morality through lenses such as virtue ethics, game theory, and computational complexity. At MIT, Jakob seeks to combine insights from moral philosophy and cognitive science to inform the design and training of AI systems that better reflect the richness of human values and the intricacies of human thought.