Shashank Sharma Ph.D. Candidate, Amar Nath and Shashi Khosla School of Information Technology, Indian Institute of Technology, Delhi. Email : shashank AT cse DOT iitd DOT ac DOT in Research Interest: Computational Biology, String Algorithms

Work-related:

• Courses at IIT Delhi: Advance Data Structures, Advance Algorithms, Probabilistic Graphical Models, Machine Learning
• Teaching Assistantship: Advance Data Structures (COL702), Machine Learning (C0L774), Learning Probabilistic Graphical Models (COL776), Model Centric Algorithm Design (COL757), Introduction to logic and functional programming (CSL765), Data Structures (CSL201), Introduction to Computer Science and Engineering (CON101)

Research Work:

Currently, I am working on the Sequence Assembly Problem. Our objective is to re-construct the Bacterial and Virus genomes from millions of short reads. Typically, the genome length is in the order of 2-10 Mbp and read length is about 35-200 bp. One can think of the Sequence Assembly as a Jigsaw puzzle.

Due to massive amounts of data that we are dealing with, the challenge lies in developing time and space efficient algorithms for the problem. Complex variations in genomes and errors in the reads also pose various challenges to the algorithm. Sequence Assembly is inherently hard and one must rely on heuristics to solve it. We are developing a new model for the problem and it will be interesting to provide the theoretical explanation and probabilistic guarantees on the quality of results.

An efficient method to assemble Bacterial and Virus genomes can aid biologists to characterize various properties and have a better understanding of microbial organisms.

Publications: