(check out my new homepage here)

Computer scientist by training, Life science researcher by determination!



The Broad Institute of MIT and Harvard
Stanley Center for Psychiatric Research (Genetics and Therapeutics)
&
Massachusetts General Hospital, HMS
Analytic and Translational Genetics Unit



https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwjuj86L_J_QAhWm3oMKHapQDNAQFggdMAA&url=http%3A%2F%2Fscholar.google.com%2Fcitations%3Fuser%3DxJZm7UsAAAAJ%26hl%3Den&usg=AFQjCNEfiAcXh52nwA7QzrGFBOgz5DgOJw&sig2=EGgvIE-hdgjAJA0U3MqYlg
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  • Attending 63rd BPS Annual Meeting in March 2019!
  • Dec 2018: Championed Machine learning breakout session at Broad Annual retreat!
  • Nov 2018: Presented at American Epilepsy Society meeting, 2018
  • Oct 2018: Presented workshop at Cleveland Clinic
  • Oct 2018: Presented my reviewer's choice abstract-poster at ASHG18
  • Apr 2018: Manuscript accepted in Oxford Bioinformatics!
  • Feb 2018: Presented my poster at Biophysical society meeting, 2018


I am a postdoc at Broad Institute of MIT and Harvard, and a fellow at Massachusetts General Hospital, HMS. I closely work with the genetics and therapeutics group of Stanley Center, under the mentorship of Mark DalyDennis LalArthur CampbellFlorence Wagner, and Jeff Cottrell.

My research crosses and connects the field of translational genetics and structural biology, by synergetic application of machine learning, data science, and computational and statistical approaches. My current project, at Broad Institute, involves the interpretation of the biological and functional impact of protein-altering missense variants, upon mapping them onto 3D protein structures at scale, using a data-driven and analytical approach. While the complex biological pathways and precise molecular-level functions need to be explained by critical experiments, our quantitative approach will assist in rationalizing variant selection for molecular assays and formulating hypotheses for experiments, thus will contribute to the translation of personal genomics to precision medicine. My doctoral research was focused on the prediction of intrinsically disordered protein and their crucial correspondence with human disease, and the prediction of protein-binding regions from primary sequence using large-scale data analysis and machine learning. Besides, I have developed multiple optimization algorithms (evolutionary algorithms/meta-heuristics) to find near-optimal solutions to complex problems during my doctoral and master's research.

I earned my Ph.D. in Engineering and Applied Science, concentration: Computer Science and specialization: Machine Learning and Bioinformatics (2013-2017). I obtained my B.Sc. (2004-2009) and M.Sc. (2010-2013) in Computer Science and Engineering (CSE) from Bangladesh University of Engineering & Technology (BUET). Prior to beginning the PhD, I worked as a lecturer for three years in the CSE department at my alma mater, BUET.

During Ph.D., I have been elected to membership in the Honor Society of Phi Kappa Phi, and have received Completer Award by the graduate council. Currently, I am a member of distinguished communities such as American Society of Human Genetics (ASGH), Biophysical Society (BPS), American Epilepsy Society (AES), International Society of Computational Biology (ISCB), and ACM.

I am passionate about my research. To understand – and intervene on – the development of disease phenotype and therapeutically target the patho-mechanism, the Integrative and Translational Genetics in Medicine will require the inclusion of quantitative and analytical approaches to molecular and biophysical phenomena, and I am strongly motivated to continue my scientific exploration in this area through a research-based academic career.