Queer in AI @ NeurIPS 2026: Organizers

• Sharvani Jha (she/her) is a technologist who has worked as a software engineer on Microsoft Word (Clippy forever!) and led software development on a UCLA-run NASA mission studying space weather. At Queer in AI, she focuses on publicity, graphic design, and workshop organization. She has a B.S. in Computer Science from UCLA, where she founded ACM AI’s Outreach division and co-founded QWER Hacks, MLH’s first queer hackathon that is still going strong six years later.

• Alissa Valentine (she/they) is a postdoc in Computer Science at the University of Copenhagen. In Denmark, they work on the TRUSTMIND project, aimed to evaluate [the lack of] trustworthy AI in mental health. Alissa’s main interest is focused on addressing the intersectional disparities in psychiatry, using a combination of basic ML, NLP, epidemiology, and data science. Alissa has organized several Queer in AI workshops in the past, including EurIPS 2025.

• Kaiser Sun (they/them, hsun74@cs.jhu.edu): Kaiser is a Ph.D. student in Computer Science at the Data Science and AI Institute and the Center for Language and Speech Processing at Johns Hopkins University. Their research focuses on the training dynamics, evaluation, and interpretability of Large Language Models. Generally, Kaiser is interested in understanding how language models function and exploring how we can change them. Their work has been recognized with an honorable mention at CoNLL2023, an outstanding paper award at MLRC2022, and coverage by a few media outlets such as MIT Technology Review and WIRED. Previously, they obtained their B.S., B.A., and M.S. from the University of Washington and were a researcher at Meta AI, Together AI, and AWS AI Labs.

• Esmeralda S. Whitammer (she/they) is a Chancellor's Fellow in Informatics at the University of Edinburgh and a fellow of CIFAR's Learning in Machines and Brains programme. Her research focuses are algorithms for probabilistic inference and Bayesian machine learning, with applications in generative modelling, neurosymbolic methods, and machine reasoning. She obtained a PhD in mathematics from Yale University (2021) and was previously a postdoctoral researcher at Mila – Québec AI Institute in Montréal (2021 to 2024).

• Ashwin S (she/they) is a PhD student at TU Wien where her research focuses on designing algorithms with provable fairness guarantees. Previously, she earned her MSc in AI from Universitat Pompeu Fabra, Barcelona, graduating as valedictorian, where her thesis helped make risk-assessments for criminal recidivism in Catalunya more accurate, fair and interpretable. She also served as the first DEI Admin of Queer In AI, where her work won the Best Paper Award at FAccT 2023.

• Thibault Marette (he/him, marette@kth.se) is a 3rd year PhD student at KTH Royal Institute of Technology and affiliated to Digital Futures in Stockholm. His research interests encompass algorithmic robustness and fairness for unsupervised learning problems, with a current focus on clustering  methods. Previously, Thibault obtained his MSc in theoretical computer science from ENS Lyon (2022).

• Alex Markham (they/them, awm@math.ku.dk) is a postdocin the Copenhagen Causality Lab and a SMARTbiomed fellow at the University of Copenhagen. Their research focuses on causal machine learning, including discovery, inference, representation learning, and applications; it ranges from foundational work intersecting combinatorics and algebraic statistics, to developing causal deep generative models, to omics applications.

• Siyan Li (she/her) is a 4th-year Ph.D. student in Computer Science at Columbia University, co-advised by Zhou Yu and Julia Hirschberg. Her research focuses on interactive, privacy-preserving systems for education. Her work has been supported by NVIDIA, NAIRR, SONY, and Patronus AI. Previously, she has been a research intern at Adobe and Together AI.