Samuel S. Kim, Ph.D., is a Technology Specialist and Patent Agent in the New York office of Fish & Richardson P.C. He focuses his practice on patent prosecution support in the life sciences and electrical and computer technologies, with experience in bioinformatics, genetics/genomics, artificial intelligence/machine learning, integrated circuit design, natural language processing, image processing, and synthetic biology. He is also familiar with wet lab techniques including molecular cloning and flow cytometry.
Dr. Kim has an extensive research background in statistical genetics, having served roles at both Harvard School of Public Health and Massachusetts Institute of Technology, as well as a major biotechnology company. He has published multiple first-authored and collaborative articles in high-impact journals and was awarded NIH predoctoral fellowship. In addition to his patent practice, Dr. Kim is heavily involved in STEM education and mentorship. He has mentored nine MIT undergraduate researchers and is currently an interviewer for undergraduate admissions to the school. Dr. Kim also has a particular interest in advocating diversity with his former experience of diversity recruitment at MIT and mentoring first-generation college students and LGBTQ+ youth.
Samuel Kim, Karthik Jagadeesh, Kushal K. Dey, Amber Z. Shen, Soumya Raychaudhuri, Manolis Kellis, and Alkes L Price, “Leveraging single-cell ATAC-seq to identify disease-critical fetal and adult brain cell types,” bioRxiv, 2021 (preprint).
Carla Marquez-Luna, Steven Gazal, Po-Ru Loh, Samuel Kim, Nicholas Furlotte, Adam Auton, 23andMe Research Team, and Alkes L. Price, “Incorporating functional priors improves polygenic prediction accuracy in UK Biobank and 23andMe data sets,” Nature Communications, 2021 (in press).
Samuel Kim, Kushal K. Dey, Omer Weissbrod, Carla Marquez-Luna, Steven Gazal, and Alkes L Price, “Improving the informativeness of Mendelian disease pathogenicity scores of common disease,” Nature Communications, 2020.
Kushal K. Dey, Bryce van de Geijn, Samuel Kim, Farhad Hormozdiari, David R. Kelley, and Alkes L. Price, “Evaluating the informativeness of deep learning annotations for human complex diseases,” Nature Communications, 2020.
Kushal K Dey, Samuel Kim, David R. Kelley, Joseph Nasser, Jesse M. Engreitz, and Alkes L. Price, “Integrative approaches to improve the informativeness of deep learning for human complex diseases,” bioRxiv, 2020 (preprint).
Samuel Kim, Chengzhen Dai, Farhad Hormozdiari, Bryce van de Geijn, Steven Gazal, Yongjin Park, Luke O’Connor, Tiffany Amariuta, Po-Ru Loh, Hilary Finucane, Soumya Raychaudhuri, and Alkes L Price, “Genes with high network connectivity are enriched for disease heritability,” American Journal of Human Genetics, 2019.
Rohil Verma, Samuel Kim, David Walter, “Syntactical analysis of the weaknesses of sentiment analyzers,” Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2018.
Bozhi Tian …, Samuel Kim, … Yuanwen Jiang, “Roadmap on semiconductor-cell biointerfaces,” Physical Biology, 2018.
Ph.D., Electrical Engineering and Computer Science, Massachusetts Institute of Technology (2021)
S.M, Computer Science, with minor in Applied Economics, Massachusetts Institute of Technology (2019)
B.E.E., Computer Engineering, Auburn University (2016)