Srinivas Aluru is Executive Director of the Georgia Tech Interdisciplinary Research Institute (IRI) in Data Engineering and Science (IDEaS) and a professor in the School of Computational Science and Engineering within the College of Computing. He co-leads the NSF South Big Data Regional Innovation Hub which nurtures big data partnerships between organizations in the 16 Southern States and Washington D.C., and the NSF Transdisciplinary Research Institute for Advancing Data Science. Aluru conducts research in high performance computing, data science, bioinformatics and systems biology, combinatorial scientific computing, and applied algorithms. He pioneered the development of parallel methods in computational biology, and contributed to the assembly and analysis of complex plant genomes. His group is currently focused on developing bioinformatics methods for long reads, graph representations of genomes, and network methods using mutual information and Bayesian approaches. His contributions in scientific computing lie in parallel Fast Multipole Method, domain decomposition methods, spatial data structures, and applications in computational electromagnetics and materials informatics. Aluru is a Fellow of the American Association for the Advancement of Science (AAAS), the Asociation for Computing Machinery (ACM), the Institute for Electrical and Electronic Engineers (IEEE), and the Society for Industrial and Applied Mathematics (SIAM). He is a recipient of the NSF Career award (1997), IBM faculty award (2002), Swarnajayanti fellowship from the Government of India (2007), and the John. V. Atanasoff Discovery Award from Iowa State University (2017).

Previously, Aluru held faculty positions at Iowa State University, Indian Institute of Technology Bombay, New Mexico State University, and Syracuse University. Immediately prior to joining Georgia Tech, Aluru spent 14 years working as a faculty in the Department of Electrical and Computer Engineering at Iowa State University. At Iowa State, he held the Ross Martin Mehl and Marylyne Munas Mehl endowed professorship (2009-2013) and the Richard Stanley Chair in Interdisciplinary Engineering in the College of Engineering (2006-2009). He chaired the interdepartmental Bioinformatics and Computational Biology graduate program (2005-2007), served as associate chair for research in the department (2003-2006), and led the Dean's Research Initiative in high-throughput computational biology, a multi-disciplinary and multi-investigator initiative at the interface of high performance computing and computational biology. He was a recipient of university level awards for Outstanding Achievement in Research (2011) and Mid-career Achievement in Research (2006), Young Engineering Faculty Research Award (2002) within the College of Engineering, and the Warren B. Boast Undergraduate Teaching Award (2005).

Recent Keynotes/Distinguished Lectures

  • Genome graphs: Models, algorithms, and applications, keynote at the 16th International Symposium on Bioinformatics Research and Applications (ISBRA), Moscow, Russia, December 1, 2020.
  • Genomes galore: Big data challenges in computational genomics and systems biology, Computer Science and Mathematics Dvision (CSMD) Reocgnition Lecture Series, Oak Ridge National Laboratory, September 26, 2019.
  • Genomes galore: Big data challenges in computational genomics, University of Brasilia, May 27, 2019.
  • Long read mapping at scale: Algorithms and applications, keynote at the 8th IEEE International Conference on Computational Advances in Bio and Medical Sciences (ICCABS), Las Vegas, October 19, 2018.
  • Parallel machine learning approaches for reverse engineering genome-scale networks, invited talk at Symposium on Machine Learning in Science and Engineering, Carnegie Mellon University, Pittsburgh, June 7, 2018.
  • High performance computing for biology and medicine, invited talk at the CCC Workshop on Digital Computing Beyond Moore's Law, San Francisco, May 3, 2018.
  • Automata processor and its applications in bioinformatics, keynote at the 1st International Workshop on Accelerator Architectues in Computational Biology and Bioinformatics (AACBB), held in conjunction with International Symposium on High Performance Computer Architecture (HPCA), Vienna, Austria, February 24, 2018.
  • Genomes galore: Big data challenges in the life sciences, invited talk at the University of Illinois at Urbana-Champaign, Urbana, Illinois, February 12, 2018.

Current Funded Projects

  • S. Aluru, S. Kalidindi, D. Sherrill, D. Shoemaker and R. Vuduc, National Science Foundation, MRI: Acquisition of an HPC System for Data-Driven Discovery in Computational Astrophysics, Biology, Chemistry, and Materials Science, Oct 2018 -- Sep 2021.
  • S. Aluru, S. Kalidindi, M. Marathe, R. Rawlings-Goss and P. Sullivan, National Science Foundation, BD Hubs: The South Big Data Innovation Hub, June 2019 -- May 2023.
  • S. Aluru, National Science Foundation, Algorithmic Techniques for High-throughput Analysis of Long Reads, May 2018 -- May 2021.
  • X. Huo, S. Aluru, D. Randall, P. Tetali and J. Wu, National Science Foundation, TRIPODS: Transdisciplinary Research Institute for Advancing Data Science (TRIAD), Sep 2017 -- Aug 2020.
  • S. Aluru and S. Thankachan, National Science Foundation, Sequential and Parallel Algorithms for Approximate Sequence Matching with Applications to Computational Biology, Aug 2017 -- Aug 2020.
  • S. Aluru, National Science Foundation, Reproducibility and Comprehensive Assessment of Next Generation Sequencing Bioinformatics Software, July 2017 -- June 2020.

Recent Conference Leadership

Handbook of Computational Molecular Biology

Aluru's book cover