Ning Lab (Ongoing)
Ben joined Dr. Xia Ning’s laboratory in the spring of 2022, where his research focuses on developing deep learning artificial intelligence methodologies to pioneer research and discovery within the biomedical community. As a first-year undergraduate student in the lab, Ben developed interactive web portals to highlight two projects from Ning Lab: the Clinical Trails Knowledge Graph and G²Retro. Both web portals can be accessed through the Ning Lab website (https://u.osu.edu/ning.104/webportals/).
In the summer of 2023, Ben worked with Ph.D. student Bo Peng to co-author their manuscript, “Towards Efficient and Effective Adaptation of Large Language Models for Sequential Recommendation,” which is currently under review by ACM Transactions on Knowledge Discovery from Data. In this paper, Ben and Bo investigate computationally efficient large language model fine-tuning for recommender systems. Their design implements a side network of learnable mixture-of-experts adaptors connected by a recurrent backbone. In this way, the large language model weights can be frozen and parameter updates, as well as back-propagation, only occur on the side network. A pre-print copy is available on arxiv (https://arxiv.org/abs/2310.01612).
Following this work, Ben co-authored “Enhancing drug and cell line representations via contrastive learning for improved anti-cancer drug prioritization,” which has since been published in Nature partner journal npj Precision Oncology. He also recently co-authored “ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery,” which is currently under review at ICLR 2025.
Ben is now leading the development of a multimodal deep learning model for Alzheimer’s disease progression prediction. He will defend this research as part of his Honors Thesis.
Data Analytics Student Assistant (Ongoing)
In the summer of 2022, Ben began working at the Translational Data Analytics Institute as a Data Analytics Student Assistant. His primary responsibility is to serve on the Data Science Corps Service, which assists university faculty with their data processing and analysis needs. He also supports graduate students in the Masters in Translational Data Analytics (MTDA) program by offering tutoring services for their classes in Python, R, and statistics. Recently, Ben has started developing a lecture series to supplement the MTDA coursework. He is currently creating an introductory course for exploratory data analysis using R.
Tufts University — DIAMONDS REU (Summer 2024)
Details coming soon.
Brown University — The Leadership Alliance Summer Research Early Identification Program + U.S. Department of Veterans Affairs (Summer 2022)
In the summer of 2022, Ben participated in a research internship at Brown University through The Leadership Alliance’s Summer Research Early Identification Program. The Leadership Alliance is an organization that provides underrepresented and minority students with competitive undergraduate research opportunities and professional development training. Ben’s research was conducted through the Providence Veterans Affairs Medical Center, where he performed a comprehensive literature review of suicide prevention strategies for elderly veterans in primary care settings. His research culminated in assembling a state-of-the-art compendium of suicide prevention toolkits and a presentation of my findings at The Leadership Alliance National Symposium in Hartford, CT. The resulting paper, “An Environmental Scan of Suicide Prevention Resources for Older Veterans in Primary Care,” is published in Clinical Gerontologist and can be accessed here.