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Sayan Goswami

Assistant Professor of Computer Science

Louisiana State University, Shreveport

Biography

I am an assistant professor in the department of Computer Science at LSU Shreveport. My research interests lie primarily in the big-data domain of de novo whole genome assembly and in general I am intested in the high-performance computing (HPC) aspect of handling scientific datasets. I am especially interested in desiging scalable memory-efficient tools for processing large datasets by sketching, streaming or partitioning them.

Lately, I am quite keen on third generation sequence assembly (also known as long read assembly) partly because of the computational complexity involved in it but mostly since low-cost portable 3G sequencers such as Oxford Nanopore MinION can make personalized medicine, and on-field analysis, such as monitoring pathogens or environmental samples, much more affordable.

Interests

  • Big Data
  • High-Performance Computing
  • Genome Assembly

Education

  • PhD in Computer Science, 2019

    Louisiana State University at Baton Rouge

  • BTech in Computer Science, 2011

    National Institute of Technology, Durgapur, India

Experience

 
 
 
 
 

Assistant Professor of Computer Science

Louisiana State University - Shreveport

Aug 2019 – Present Shreveport
Responsibilities include:

  • Teaching & Advising
  • Research
  • Service in university committees
 
 
 
 
 

Graduate Assistant

Louisiana State University - Baton Rouge

May 2019 – Jan 2013 Baton Rouge
Conducted research and assisted faculty in their teaching duties
 
 
 
 
 

Associate Technology

Sapient Global Markets

Jul 2011 – Jan 2013 Bangalore
Oversaw end-of-day workflows for clients in the energy & commodity market

Teaching

To be filled in soon. I am teaching CSC 285 and CSC 460660 in the Fall of 2019

Recent Publications

GPU-Accelerated Large-Scale Genome Assembly

Spurred by a widening gap between hardware accelerators and traditional processors, numerous bioinformatics applications have harnessed …

Towards Distributed Cyberinfrastructure for Smart Cities Using Big Data and Deep Learning Technologies

Recent advances in big data and deep learning technologies have enabled researchers across many disciplines to gain new insight into …

Augmenting Amdahl's Second Law: A Theoretical Model to Build Cost-Effective Balanced HPC Infrastructure for Data-Driven Science

High-performance analysis of big data demands more computing resources, forcing similar growth in computation cost. So, the challenge …

Lazer: Distributed memory-efficient assembly of large-scale genomes

Genome sequencing technology has witnessed tremendous progress in terms of throughput as well as cost per base pair, resulting in an …

Contact

  • +1 (314) 795-4281
  • 214 Technology Center, One University Place, Shreveport, LA, 71115, United States