Research Interests and Experience

Areas of Interest

•   Bioinformatics algorithm workflows

•   Computational biology algorithms

•   High performance computing (HPC)

•   Graph theory

•   Data visualization

•   Machine learning

•   Networking

•   Database

1. Project title: “Tile-X: A vertex reordering approach for scalable long read assembly ” 

Under supervision of Dr. Ananth Kalyanaraman, Professor & Director, School of Electrical Engineering and Computer Science, Washington State  University, WA, USA 

Features of Research: This paper introduces Tile-X, a novel graph-based framework that enhances the speed and scalability of genome assembly using long-read sequencing data. By reordering reads based on their structural relationships in a graph, Tile-X enables efficient parallel assembly with reduced memory usage—while preserving or improving assembly quality. It also proposes a custom strategy, Tile-Far, that selects only the most informative reads, further accelerating performance. Tile-X outperforms leading assemblers across multiple datasets, making it a powerful tool for large-scale genomic analysis.

2. Project title: “An Efficient Parallel Sketch-based Algorithmic Workflow for Mapping Long Reads ” 

Under supervision of Dr. Ananth Kalyanaraman, Professor & Director, School of Electrical Engineering and Computer Science, Washington State  University, WA, USA 

Features of Research: This paper presents a scalable, parallel workflow for mapping long sequencing reads to reference sequences using lightweight sketching techniques such as MinHash and minimizers. Designed to handle large genomic datasets efficiently, the method balances accuracy and speed by avoiding full alignments and instead using compact data summaries. The approach demonstrates strong performance across diverse datasets and platforms, making it well-suited for modern high-throughput sequencing analysis. 

3. Project title: “Maptcha: An Efficient Parallel Workflow For Hybrid Genome Scaffolding ” 

Under supervision of Dr. Ananth Kalyanaraman, Professor & Director, School of Electrical Engineering and Computer Science, Washington State  University, WA, USA 

Features of Research: This paper presents Maptcha, a high-performance hybrid genome scaffolding tool that efficiently links fragmented contigs using long-read sequencing data. Designed for speed and scalability, Maptcha applies parallel sketch-based mapping and a custom wiring heuristic to produce accurate scaffolds, even with low long-read coverage. It significantly reduces gaps and misassemblies, offering a robust solution for improving draft genomes—especially those left unfinished in large sequencing projects. 

4. Project title: “An Efficient Parallel Sketch-based Algorithm for Mapping Long Reads to Contigs ” 

Under supervision of Dr. Ananth Kalyanaraman, Professor & Director, School of Electrical Engineering and Computer Science, Washington State  University, WA, USA 

Features of Research: This paper introduces a parallel mapping algorithm that efficiently aligns long sequencing reads to contigs using sketch-based techniques like minimizers and Jaccard similarity. The method leverages distributed and multithreaded computing to handle large genomic datasets with high speed and accuracy. Designed to be both lightweight and scalable, the algorithm forms a core building block for downstream genome assembly and scaffolding workflows. 

5. Project title: “Comparative study on selection of genes causing Alzheimer’s Dementia using Meta- heuristic approaches” Duration: June 2016 - June 2017 

Project Guide: Dr M. Murali, Assistant Professor, Department of Computer Science and Engineering, SRM University INDIA 

Features of Research: Meta- heuristic approaches such as Variable Neighborhood Search (VNS) and Differential Evolution (DE) are used for reducing the search space as the dataset having 33297 genes of individuals affected with Alzheimer's. Along with the meta – heuristic approaches a classification algorithm has also been used that is k Nearest Neighbor (kNN) then their performance is compared. kNN is used for scoring the genes and the neighborhood structures. It is seen that DE performs better than VNS in terms of both highest score and execution time.

6. Project title: “Protein function prediction from protein interaction network using clustering and sequence of amino acid”. Duration:    June 2014 - May 2015 

Project Guide: Mr. Sovan Saha, Assistant Professor, Department of Computer Science and Engineering, DSCSDEC, West Bengal University of Technology, INDIA

Features of Research: A network-flow based algorithm has been developed that exploits the underlying structure of protein interaction maps in order to predict protein function. The development of experimental methods for genome scale analysis of molecular interaction networks has made possible new approaches for inferring protein function. This project describes a method of assigning functions based on a probabilistic analysis of graph neighborhoods in a protein protein interaction network.

7. Project Title: "Applications of Computer Forensics". Duration : August 2014 - December 2014

Project Guide: Mrs Ruchira Datta, Assistant Professor, Department of Computer Science and Engineering, DSCSDEC, West Bengal University of Technology, INDIA

Features of Research: A review of Computer Forensics has been done till date and presented with multiple examples. Both the advantages and disadvantages has been illustrated.[PPT]

8. Project Title: "Usefulness of Dot Net for the design of websites". Duration: December 2013 - January 2014

Project Guide: Ms. Priyanka Chakraborty, Teaching Staff, CMC Limited, INDIA

Features of Research: Different applications have been shown in a website designed with the help of dot net. The website imitates all the usages of a mobile networking site including both the users and admin tasks like recharge, bill payments and also allotment of new numbers.