Hao Chih Lee
About Hao Chih Lee
Hao Chih Lee is an AI Scientist at BenevolentAI with a background in biomedical engineering and applied mathematics, known for his contributions to AI in drug discovery.
Current Position at BenevolentAI
Hao Chih Lee currently holds the position of AI Scientist at BenevolentAI. In this role, Lee leverages his expertise in artificial intelligence to drive advancements in drug discovery. His work involves the development and implementation of machine learning models tailored to biomedical applications.
Assistant Professor at Icahn School of Medicine
From 2018 to 2021, Hao Chih Lee served as an Assistant Professor at the Icahn School of Medicine at Mount Sinai. During his tenure, he focused on applied research in artificial intelligence, particularly within the biomedical domain. Lee's work contributed to the integration of AI solutions in medical research, enhancing the efficiency and accuracy of biomedical data analysis.
Postdoctoral Fellow at Icahn School of Medicine
From 2015 to 2018, Hao Chih Lee worked as a Postdoctoral Fellow at the Icahn School of Medicine at Mount Sinai in the Greater New York City Area. His research concentrated on the application of machine learning algorithms to solve complex biomedical problems. This period marked significant advancements in his career, laying the groundwork for his later work in AI and biomedical engineering.
Academic Background
Hao Chih Lee holds a Ph.D. in Biomedical/Medical Engineering from Carnegie Mellon University. During his doctoral studies, he developed a strong foundation in applying AI to solve biomedical challenges. Lee also earned a Master's Degree in Applied Mathematics from National Taiwan University, where he honed his mathematical and analytical skills. His diverse educational background underpins his expertise in AI and computational biology.
Research and Presentations
Hao Chih Lee published research on the application of AI in drug discovery, demonstrating the potential of machine learning models to significantly enhance prediction accuracy in protein-ligand interactions. In 2022, he presented his findings at the International Conference on Machine Learning (ICML), showcasing his contributions to the field. Lee has also collaborated with interdisciplinary teams to advance computational biology and contributed to various open-source AI projects.