Postdoctoral Research Associate
Broad Institute of MIT and Harvard
Stanley Center, Genetics and Therapeutics Group
75 Ames St, Cambridge, MA 02142
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  • August 07, 2017: Started working at the Broad Institute of MIT and Harvard
  • April 25, 2017: Defended PhD Thesis!
  • April 08, 2017: Gave a talk on 5th Annual Conference on Bioinformatics and Computational Biology' 2017 at NOLA
  • December 27, 2016: Going to present poster at BPS Annual Meeting' 2017 at NOLA
  • December 7, 2016: Received Completer Award by Graduate Council for Spring 2017
  • December 2, 2016: Article accepted in SWEVO Journal!
  • September 25, 2016: Article got accepted in IJBIC!
  • September 16, 2016: Gave a talk in UNO Engineering Forum.
  • August 12, 2016: Gave a talk in Meiler Lab, Vanderbilt University.
  • August 6, 2016: Article got accepted in PloS One!
  • May 25, 2016: Received ACM student travel grant to attend SIGEVO-GECCO'2016 
  • March 19, 2016: Paper accepted to GECCO'2016!
  • March 6, 2016: Paper accepted to CCBC/GLBIO'2016!
I am a Postdoctoral Associate at the Broad Institute of MIT and Harvard. I closely work with the Genetics and Therapeutics groups of Mark Daly and Ed Scolnick within the Stanley Center. My research involves prediction, phenotype and functional data correlation analyses of genes and variants, to map genetic variants and annotate structural motifs onto the primary sequence and tertiary structure of disease associated genes.

I earned my Ph.D. in Engineering and Applied Science (2013 - 2017), concentration: Computer Science and specialization: Machine Learning and Bioinformatics, from the University of New Orleans, LA, USA.  I worked as a Graduate Research Assistant in the Bioinformatics and Machine Learning Lab (BML Lab/Hoque's Lab) of Computer Science department at University of New Orleans (UNO). I obtained my B.Sc. and M.Sc. in Computer Science and Engineering (CSE) from Bangladesh University of Engineering & Technology (BUET). Prior to beginning the PhD, I worked as a faculty for three years in the CSE department at my alma mater, BUET.  

 My key research areas are Machine Learning and Scientific ComputingBioinformatics, Computational and Systems Biology, Data Mining and Pattern Recognition, Evolutionary Algorithms and Metaheuristic Applications.
My research addresses the need for computational methods in modern biology, medicine and drug discovery, to manage and mine large-scale biological data and extract knowledge out of these data using machine learning. My doctoral research focuses on Protein Structure Prediction, Identification of Protein Disorder and its critical correspondence with human diseases, Development of Machine Learning based Predictive Tools for Protein Research by Large Scale Data Analysis, and Building Evolutionary Algorithms/Meta-heuristics to find near-optimal solutions to complex problems.

During Ph.D., I have been elected to membership in the UNO chapter of the Honor Society of Phi Kappa Phi, awarded to the top 10 percent of graduate students only. In my last semester,
I have been selected as a recipient of Completer Award by the graduate council of UNO and elected as a member of Golden key International Honor Society. Currently, I am a member of distinguished communities such as American Society of Human Genetics (ASGH), ACM, IEEE, Biophysical Society and International Society of Computational Biology (ISCB).

I am passionate about my research and strongly motivated to continue my career further in the field of bioinformatics, computational biology and machine learning. Please feel free to check my research, publications and CV