Research interests:

Domain: Computational biology, bioinformatics, epigenetics, human genetics, phylogenetics, signal processing.

Direction: Developing novel computational and predictive models and frameworks utilizing 1. statistical analysis, 2. novel algorithms, 3. Machine learning, and 4. Deep learning.

Working datasets:

Transcriptomics: Bulk and single cell RNA-seq (short and long-read next generation sequencing (NGS) data)

Epigenomics: ChIP-seq, ATAC-seq, multi-omics, methylation, chromatin interactions (3C tehnologies like Hi-C, HiChIP).

Human genetics: QTL (eQTL, caQTL), GWAS

Proteomics: Protein mutations, VEP

Career

Lead Data Scientist (October 2024 - Current), Empirico,  San Diego, CA 92130, USA

Research area:  

1. Algorithms and frameworks for modeling human genetic variations (GWAS, QTLs) and application in binary and quantitative phenotypes.

2. Predictive modeling of protein missense mutations.

3. Discovering drug-target transcripts and isoforms utilizing long-read RNA-seq.

Instructor (January 2021 - October 2024), La Jolla Institute for Immunology, La Jolla, CA 92037, USA

Research area:

1. Modeling 3D chromatin structures and gene regulatory mechanism by combining chromatin interactions (Hi-C, HiChIP) with human genetics (QTL, GWAS) information.

2. Statistical and algorithmic techniques to prioritize putatively causal genetic variants for context-specific gene regulation using bulk and single cell genetic and epigenetic data, and applications in various diseases (COVID-19, T1D).

3. Deep learning based modeling of gene-regulatory landscape.

4. Modeling disease-specific genes and regulatory regions using single cell and multi-omics data.

Postdoctoral researcher (April 2017 - December 2020), La Jolla Institute for Immunology, La Jolla, CA 92037, USA

Research areas:

1. Developing computational methods to infer gene regulatory interactions from chromatin conformation capture (3C) interaction data (Hi-C, HiChIP) 

2. Developing novel models to infer putatively causal genetic variants (SNPs) utilizing transcriptomic, epigenetic, chromatin interactions.

3. Inferring regulatory interactions and causal genetic variants in immune cell types and disease-specific studies.

Ph.D. (July 2012 - August 2017), Computer Science and Engineering, Indian Institute of Technology Kharagpur, India

Research area: 

1. Algorithms in Computational phylogenetics and molecular evolution. 

1. • Resolving the conflict of evolutionary information among a group of species, due to the difference in individual genetic lineages.

Master of Science (M.S.) by research + Project Scholar (July 2009 - July 2012), Computer Science and Engineering, Indian Institute of Technology Kharagpur, India

Research area: 

1. Machine learning assisted detection of epileptic seizure patterns using neonatal electroencephalogram (EEG) signal and video recordings.

2. Framework to visualize EEG signals and annotate, and automated detection of epileptic seizure patterns.

Research Software Engineer in STMicroelectronics, India (July 2006 - July 2009) (R&D Section)

Research area: 

1. Video transcoding between formats H.264, MPEG-4, and MPEG-2, along with the bit rate control mechanism, for supporting low bandwidth.

   • Target Application: Integrated in STMicroelectronics implemented DBS (Dynamic Bitstream Shaper) transcoding library (integrated into STm71xx product family).

2. Integration of A/V codecs in  OpenMAX (Open Media Acceleration) and MPLAYER (version 1.0pre8) multimedia libraries.

Bachelor in Engineering (B.E) (June 2002—June 2006), Computer Science and Engineering, Jadavpur University, Kolkata, West Bengal 700032, India

Research Grants

• Submitted NIH R35 grant 1R35GM160043-01 (Predicting causality of genes and regulatory regions using 3D epigenome and graph-based deep learning) (under review).

• NIH R03 grant 1R03OD034494-01 (Using Common Fund datasets for prioritization of disease-associated genetic variants): Assisted my supervisor Dr. Ferhat Ay in preparing the grant proposal, initial results. (link)

• D - Challenge 2021: Our team (Joaquin Reyna, Sourya Bhattacharyya, Nikhil Rao, Abhijit Chakraborty and Ferhat Ay) obtained a grant of $20,000 for research in Type 1 Diabetes (T1D), from SugarScience (https://thesugarscience.org/). For details, check http://info.thesugarscience.org/dknet-21-d-challenge

Awards / Fellowship / Travel Grants / Recognitions

• JULY 2022: Conference travel fellowship from ISMB 2022.

• MARCH 2022: Our work on single-cell eQTL in immune cells is featured in various scientific news articles.

• NOVEMBER 2021: Our work on Functional variants of COVID-19 in immune cells is featured in various scientific news articles.

• JANUARY 2021: Our work on promoter interacting eQTL is highlighted in various scientific news articles.

• JUNE 2019: Our work Single-cell transcriptomic analysis of tissue-resident memory T cells in human lung cancer is featured in various scientific news articles. 

• JUNE 2015: Conference Travel fellowship from the Organizing Committee of ISBRA 2015.

• MAY 2015: Conference Travel fellowship from the Department of Science and Technology (DST), India, for attending conference ISBRA 2015.

• APRIL 2013: Ph.D. fellowship from Tata Consultancy Services (TCS) 

• JULY 2012: Ph.D. fellowship from Indian Institute of Technology, Kharagpur (until March 2013).