Honorable Mention of CRA Outstanding Undergraduate Researcher Award 2021: Xinliang (Frederick) Zhang
Xinliang (Frederick) Zhang is awarded the Honorable Mention of CRA Outstanding Undergraduate Researcher Award 2021. CRA Outstanding Undergraduate Researcher Award, a prestigious award program, recognizes undergraduate students in North American colleges and universities who show outstanding research potential in an area of computing research.
Xinliang (Frederick) Zhang is a senior undergraduate student at the Ohio State University, majoring in Computer Science & Engineering and Industrial & Systems Engineering, primarily advised by Dr. Huan Sun. He also works closely with Dr. Marie-Catherine de Marneffe. He is a candidate in Graduation with Honors Undergraduate Research Distinction as well. Before transferring to OSU, he was an undergraduate student at Sichuan University, China, where he was awarded National Scholarships twice consecutively. He also served as an undergraduate teaching assistant for many CSE classes at OSU, such as Database, Software, Algorithms and Programming Languages.
His research interests lie in the fields of Natural Language Processing (NLP) and Machine Learning (ML). He has been leading several NLP projects with topics spanning Question Answering & Generation, Information Retrieval and Natural Language Inference. He recently works on NLP applications in healthcare. He has managed to improve the generalizability of clinical question answering systems by automatically synthesizing diverse questions in a controllable way. Recently, his team released a large, challenging dataset for COVID-19 FAQ retrieval to help combat the ongoing pandemic. He also investigated annotation disagreements detection, an overlooked problem in natural language inference, by proposing ensemble methods to simulate annotation uncertainties.
His ultimate research goal is to build robust and trustworthy general-purpose NLP systems to better serve people. Therefore, he aims to tackle the generalizability issues frequently encountered by machine learning systems and develop algorithms to precisely understand knowledge encoded in (or entailed by) unstructured text.
He expressed sincere gratitude for the mentorship of Dr. Huan Sun. He is committed to conducting NLP research with real-world impact moving forward. Lastly, he shared his messages with other students who expect to be engaged in undergraduate research, “start early, think deeply, work proactively, and never be afraid of failures”.