Kempner Institute Welcomes Fall Undergraduate Student Researchers
Twenty undergraduate students receive KURE awards to undertake intelligence-focused research projects
Cambridge, MA – The Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard is pleased to announce the fall 2024 recipients of the Kempner Undergraduate Research Experience (KURE). KURE awards Harvard undergraduate students funding for term-time research supervised by Kempner-affiliated faculty during the fall and spring semesters of the academic year.
Student research projects investigate the foundations of intelligence, including mathematical and computational models of intelligence, cognitive theories of intelligence, and the neurobiological basis of intelligence, as well as applications of artificial intelligence from a scientific or engineering perspective.
Twenty Harvard undergraduate students received Fall 2024 KURE awards, representing the second cohort of undergraduates to participate in the Kempner’s term-time undergraduate research program. The inaugural cohort of KURE participants celebrated the successful completion of the Spring 2024 KURE program in May.
In addition to its term-time undergraduate research program, in summer 2024 the Kempner launched a 10-week residential summer program providing a small cohort of undergraduates with a formative research experience under the supervision of a Kempner-affiliated faculty member. The program, Kempner Research in Artificial & Natural Intelligence for Undergraduates with Mentorship (KRANIUM), is a part of the Harvard Summer Undergraduate Research Village (HSURV) and provides students with a summer living stipend, housing, and a partial boarding/dining plan, as well as access to rich social and academic programming.
To be eligible for either KURE or KRANIUM, students must find a research position with a Kempner-affiliated faculty member prior to application. More information about KURE and KRANIUM can be found on the Kempner Institute website.
The full list of Fall 2024 KURE program participants, mentors and projects are listed below:
Student | Supervisor/Mentor | Project title |
---|---|---|
Jonah Brenner ’25 | Supervisor: Gabriel Kreiman; Mentor: Chenguang Li | Policy Optimization Emerges from Noisy Representation Learning |
Camilo Brown-Pinilla ’26 | Supervisor: Sham Kakade; Mentor: David Brandfonbrener | Optimizing Data: Model Based Methods for the Selection of Optimal Data Subsets for Large Language Model Training |
Ege Cakar ’27 | Supervisor: Cengiz Pehlevan; Mentor: William Tong | Exploring the Logical Performance and Compositionality of Various Architectures |
Corwin Cheung ’26 | Supervisor: Bernardo Sabatini; Mentor: Celia Beron | Applying Language Sequencing Models to Mice Decisions in Two Armed Bandit Tasks |
Karina Chung ’26 | Supervisor: Sham Kakade; Mentor: David Brandfonbrener | Improved CoLoR-Filter for Targeted Language Model Pre-training |
Emma Finn ’26 | Supervisors: Demba Ba and Andy Keller; Mentor: Manos Theodosis | Forging Artistics Signatures: Diffusion Models and Detail in Style Transfer |
Isabella Gidi ’27 | Supervisor: Cengiz Pehlevan; Mentor: Hamza Chaudhry | A Low-Dimensional Training Method for Neural Networks |
Ely Hahami ’27 | Supervisor: Haim Sompolinsky; Mentor: Kazuki Irie | Continual Memorization in Large Language Models |
Linda He ’27 | Supervisor: Sham Kakade; Mentor: Yilun Du | Robotics Online Learning: Combining Dynamics Model with Reward Model |
Alexis Hu ’27 | Supervisor: Samuel Gershman | Enhancing Deep Neural Network Robustness to 3D Viewpoint Variations |
Sabrina Hu ’26 | Supervisor: Nada Amin | Using Symbolic Execution to Improve LLM Identification of Counterfeit Programs |
Justin Ji ’26 | Supervisor: Martin Wattenberg; Mentor: Kenneth Li | Targeted Control of Attributes in Language Models in Multi-Persona Settings |
Sarah Li ’27 | Supervisor: Patrick Slade; Mentor: Jordan Feldman | Utilizing Machine Learning to Determine Movement Objectives to Reduce Mobility Challenges |
Victoria Li ’26 | Supervisor: Naomi Saphra | Evolution as a Framework for ML Training Dynamics |
Annabel Ma ’26 | Supervisors: David Alvarez-Melis and Melanie Weber | Dataset Comparison with Underlying Symmetries |
Yeabsira Mohammed ’25 | Supervisor: George Alvarez | Comparative Analysis of Neural and Artificial Representations in Visual Recognition |
Aneesh Muppidi ’25 | Supervisor: Samuel Gershman; Mentor: Wilka Carvalho | Who’s Out There? Emergent Agent Discovery |
Josh Mysore ’26 | Supervisor: Tomer Ullman; Mentor: Jennifer Hu | Computational and Behavioral Investigation of Causal Inferences in Everyday Conversation |
Aseel Rawashdeh ’26 | Supervisor: Susan Murphy; Mentor: Daiqi Gao | Incorporating Uncertainty-Aware Reinforcement Learning for Adaptive Action and Information Gathering in Digital Health |
Susannah Su ’25 | Supervisor: Wilka Carvalho | Joint Goal-Directed Behavior in Minds and Machines |
About the Kempner Institute
The Kempner Institute seeks to understand the basis of intelligence in natural and artificial systems by recruiting and training future generations of researchers to study intelligence from biological, cognitive, engineering, and computational perspectives. Its bold premise is that the fields of natural and artificial intelligence are intimately interconnected; the next generation of artificial intelligence (AI) will require the same principles that our brains use for fast, flexible natural reasoning, and understanding how our brains compute and reason can be elucidated by theories developed for AI. Join the Kempner mailing list to learn more, and to receive updates and news.
PRESS CONTACT:
Deborah Apsel Lang | (617) 495-7993 | kempnercommunications@harvard.edu