Yann Hicke

I am a PhD student in the Computer Science department at Cornell University, advised by Claire Cardie and Rene Kizilcec. I have also had the opportunity to collaborate with Wen Sun, Emma Brunskill and Dora Demszky. I received an MEng in Operations Research and Information Engineering from Cornell University in 2015, and a BSc in Applied Mathematics and Industrial Engineering from the École Nationale Supérieure des Mines de Nancy in 2014.

Between my MEng and my PhD, I studied and worked as a theatre actor.

Email / CV / Scholar / Github / LinkedIn

Research

My research develops AI-driven patient simulations for medical education that enhance clinical training through multimodal conversational analysis. I focus on modeling realistic patient interactions, analyzing dialogue patterns, and generating evidence-based feedback. This work aims to improve medical learners' communication and clinical reasoning skills while developing robust methods to evaluate AI simulation effectiveness in educational settings. Representative papers are highlighted.

	MedSimAI: Simulation and Formative Feedback Generation to Enhance Deliberate Practice in Medical Education Yann Hicke, Jadon Geathers, Niroop Rajashekar, Colleen Chan, Anyanate Gwendolyne Jack, Justin Sewell, Mackenzi Preston, Susannah Cornes, Dennis Shung, Rene Kizilcec Arxiv, 2025
	Benchmarking Generative AI for Scoring Medical Student Interviews in Objective Structured Clinical Examinations (OSCEs) Yann Hicke, Jadon Geathers, Colleen Chan, Niroop Rajashekar, Justin Sewell, Susannah Cornes, Rene Kizilcec, Dennis Shung 26th International Conference on Artificial Intelligence in Education, 2025
	The Life Cycle of Large Language Models in Education: A Framework for Understanding Sources of Bias Jinsook Lee, Yann Hicke, Renzhe Yu, Christopher Brooks, René F. Kizilcec British Journal of Educational Technology, 2024
	Enhancing Tutoring Effectiveness Through Automated Feedback: Preliminary Findings from a Pilot Randomized Controlled Trial on SAT Tutoring Yann Hicke, Joy Yun, Mariah Olson, Dorottya Demszky Proceedings of the Eleventh ACM Conference on Learning@ Scale, 2024
	AI-TA: Towards an Intelligent Question-Answer Teaching Assistant using Open-Source LLMs Yann Hicke, Anmol Agarwal, Christina Ma, Paul Denny, NeurIPS'23 Workshop: Generative AI for Education (GAIED), 2023*
	Assessing the efficacy of large language models in generating accurate teacher responses Yann Hicke, Abhishek Masand, Wentao Guo, Tushaar Gangavarapu ACL, Innovative Use of NLP for Building Educational Applications Workshop, 2023
	Automated Essay Scoring in Argumentative Writing: DeBERTeachingAssistant Yann Hicke, Tonghua Tian, Karan Jha, Frank Kim LAK'23: Workshop on Partnerships for Cocreating Educational Content, 2023
	From Human Days to Machine Seconds: Automatically Answering and Generating Machine Learning Final Exams Iddo Drori, Sarah J Zhang, Reece Shuttleworth, Sarah Zhang, Keith Tyser, Zad Chin, Pedro Lantigua, Saisamrit Surbehera, Gregory Hunter, Derek Austin, Leonard Tang, Yann Hicke, Sage Simhon, Sathwik Karnik, Darnell Granberry, Madeleine Udell International Conference on Knowledge Discovery and Data Mining (KDD), 2023
	A dataset for learning university STEM courses at scale and generating questions at a human level Iddo Drori, Sarah Zhang, Zad Chin, Reece Shuttleworth, Albert Lu, Linda Chen, Bereket Birbo, Michele He, Pedro Lantigua, Sunny Tran, Gregory Hunter, Bo Feng, Newman Cheng, Roman Wang, Yann Hicke, Saisamrit Surbehera, Arvind Raghavan, Alexander E Siemenn Nikhil Singh, Avi Shporer, Jayson Lynch, Nakul Verma, Tonio Buonassisi, Armando Solar-Lezama, Educational Advances in Artificial Intelligence (EAAI), 2023
	Human Evaluation of Text-to-Image Models on a Multi-Task Benchmark Vitali Petsiuk, Alexander E Siemenn Saisamrit Surbehera, Zad Chin, Keith Tyser, Gregory Hunter, Arvind Raghavan, Yann Hicke, Bryan A Plummer, Ori Kerret, Tonio Buonassisi, Kate Saenko, Solar-Lezama, Iddo Drori NeurIPS Workshop on Human Evaluation of Generative Models (HEGM). Oral, 2022