I am a Postdoctoral Research Fellow working with Quaid Morris and Jian Carrot-Zhang at the Memorial Sloan Kettering Cancer Center. My research interests are centered on cross-population somatic-germline interactions in cancer, interpretable machine learning methods, and functional genomics. I received my PhD in Computational Biology and Bioinformatics and MA in History of Science and Medicine at Yale University, MS in Bioinformatics at IU, and BS in Computer Science at LAU.
H. Mohsen, K. Blenman, P.S. Emani, Q. Morris, J. Carrot-Zhang, and L. Pusztai (2023). Dynamic clustering of genomics cohorts beyond race, ethnicity—and ancestry, bioRxiv, doi 10.1101/552035. ⤴ [ASHG'23 Reviewers' Choice Abstract Award] [SMBE'24 Invited Talk]
T. Qing*, H. Mohsen*, V. Cannataro, M. Marczyk, M. Rozenblit, J. Foldi, M. Murray, J. Townsend, Y. Kluger, M. Gerstein, and L. Pusztai (2022). Cancer Relevance of Human Genes, Journal of the National Cancer Institute, djac068. ⤴
H. Mohsen, V. Gunasekharan, T. Qing, M. Seay, Y. Surovtseva, S. Negahban, Z. Szallasi, L. Pusztai, and M. Gerstein (2021). Network propagation-based prioritization of long tail genes in 17 cancer types, Genome Biology, 22, 287. ⤴
T. Qing, H. Mohsen, M. Marczyk, Y. Ye, T. O’Meara, H. Zhao, J.P. Townsend, M. Gerstein, C. Hatzis, Y. Kluger and L. Pusztai (2020). Germline variant burden in cancer genes correlates with age at diagnosis and somatic mutation burden, Nature Communications, 11, 2438. ⤴
H. Mohsen, J. Warrell, M.R. Min, S. Negahban, and M. Gerstein (2020). Weight-based Neural Network Interpretability using Activation Tuning and Personalized Products, Machine Learning in Computational Biology Workshop 2020 (MLCB'20). ⤴
M. Amodio, D. van Dijk, K. Srinivasan, W.S. Chen, H. Mohsen, K.R. Moon, A. Campbell, Y. Zhao, X. Wang, M. Venkataswamy, A. Desai, V. Ravi, P. Kumar, R. Montgomery, G. Wolf, and S. Krishnaswamy (2019). Exploring Single-Cell Data with Deep Multitasking Neural Networks, Nature Methods, 16, pp. 1139–1145. ⤴
S. Lou, K.A. Cotter, T. Li, J. Liang, H. Mohsen, J. Liu, J. Zhang, S. Cohen, J. Xu, H. Yu, M. Rubin, and M. Gerstein (2019). GRAM: A generalized model to predict the molecular effect of a non-coding variant in a cell-type specific manner, PLoS Genetics, 15 (8): e1007860. ⤴
J. Warrell, H. Mohsen, and M. Gerstein (2018). Rank Projection Trees for Multilevel Neural Network Interpretation, NeurIPS Machine Learning for Health Workshop (NeurIPS'18 ML4H). ⤴
H. Mohsen, H. Tang, and Y. Ye (2017). DNPipe: Improving De Novo Metatranscriptome Assembly via Machine Learning Algorithms, International Journal of Computational Biology and Drug Design (IJCBDD), 2 (10), pp. 91-107. ⤴
H. Mohsen, H. Kurban, K. Zimmer, M. Jenne, and M. Dalkilic (2015). Red-RF: Reduced Random Forests using priority voting dynamic data reduction, IEEE International Congress on Big Data (IEEE BigData Congress'15), pp. 118-125. ⤴
H. Mohsen, H. Kurban, M. Jenne, and M. Dalkilic (2014). A New Set of Random Forests with Varying Dynamic Data Reduction and Voting Techniques, IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA’14), pp. 309-405. ⤴
N. Mansour and H. Mohsen (2014). Computational Evaluation of Protein Energy Functions, International Conference on Intelligent Computing (ICIC’14), Lecture Notes in Computer Science (LNCS): Intelligent Computing in Bioinformatics, 8590, pp. 288-299. ⤴
H. Mohsen (2014). A Model to Measure Inter-communication between Segregated Communities, IEEE International Conference on Behavioral, Economic and Social Computing (IEEE BESC'14), pp. 1-6. ⤴
H. Mohsen, M. Fawaz, and K. Jahed (2011). Multi-Purpose Speech Recognition and Speech Synthesis System, IEEE Multidisciplinary Engineering Education Magazine (IEEE MEEM), 6 (4), pp. 22-27.
H. Mohsen (2020). Race and Genetics: Somber History, Troubled Present, Yale Journal of Biology and Medicine, 93 (1), pp. 215-219. ⤴
F.C.P. Navarro, H. Mohsen, C. Yan, S. Li, M. Gu, W. Meyerson, and M. Gerstein (2019). Genomics and data science: an application within an umbrella, Genome Biology, 20 (109). ⤴
NOV 2023 | American Society of Human Genetics (ASHG) Reviewers’ Choice Abstract Award
JAN 2023 | CCNY-MSKCC Partnership Fellowship (2023-2024)
SEP 2020 | American Association for Cancer Research (AACR) Scholar-In-Training Award
SEP 2019 | Franke Fellowship in Science and the Humanities (2019-2020)
AUG 2016 | Gruber Science Doctoral Fellowship (2016-2019)
AUG 2016 | Nicholas Jabr Fellowship Fellowship (2016-2017)
AUG 2013 | Fulbright Graduate Scholarship (2013-2015)
SEP 2012 | Erasmus Mundus Postgraduate Exchange Scholarship (2012-2013)
JUN 2011 | Best Computer Science Capstone Project Award - LAU Class of 2011
JUL 2010 | 2nd Place - Nokia-NNA contest for mobile application development in Lebanon
JUL 2010 | Extreme Programmer Award - ACM Lebanese Collegiate Programming Contest 2010, Beirut, Lebanon
2009-2011 | Lebanese American University (LAU) Honor List
SEP 2008 | LAU Undergraduate Merit Scholarship (2008-2011)
JUL 2024 | I will be giving a talk at the SMBE'24 symposium "Clustering of human cohorts beyond race and ancestry: Towards relational thinking in genomics"
AUG 2023 | Our submission to ASHG'23 on the dynamic clustering of genomics cohorts beyond predefined cateogories received a Reviewers' Choice Abstract Award
JAN 2023 | I was selected as a CCNY-MSKCC Partnership Scholar (2023-2024)
APR 2022 | New paper on the spectrum of human gene cancer relevance is out in the Journal of the National Cancer Institute
OCT 2021 | New paper on prioritizing long tail genes in cancer using network propagation is out in Genome Biology
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