Rakesh Kaundal

Plants, Soils, & Climate (PSC)

Assistant Professor, Bioinformatics; Director, Bioinformatics Facility

Rakesh Kaundal

Contact Information

Office Location: CIB 101B
Phone: 435-797-4117
Email: rkaundal@usu.edu
Additional Information:

Educational Background

PhD, Plant Breeding & Genetics, (Plant Pathology), Dr. B.R. Ambedkar University, 2006
Genetic analysis of yield components and blast resistance vis--vis identification of molecular markers for blast resistance in rice
PGD, Bioinformatics, Sikkim Manipal University, 2004
MS, Plant Breeding & Genetics, (Plant Pathology), CSK Himachal Pradesh Agricultural University, 1998
Stability Analysis for Yield and some other Quantitative Characters in Elite Varieties of Maize (Zea mays L.)
BS, Agriculture, (Crop Production), CSK Himachal Pradesh Agricultural University, 1995


Rakesh Kaundal is an Assistant Professor of Bioinformatics in the department of Plants, Soils, and Climate at Utah State University. He is also the Director of Bioinformatics Facility in the Center for Integrated BioSystems (CIB), USU. In addition, he has an adjunct faculty appointment in the department of Computer Science. Dr. Kaundal grew up in India and in 2007 moved to USA to conduct a Postdoctoral Research Fellowship in bioinformatics & computational biology at the Noble Research Institute, Ardmore (OK). In 2011, he joined the Oklahoma State University, Stillwater (OK) as a non-tenure track faculty member where he established a new bioinformatics and high-performance computing lab; joint appointment in the National Institute for Microbial Forensics & Food and Agricultural Biosecurity (NIMFFAB), and the department of Biochemistry & Molecular Biology. He is the founding director of OSU’s interdisciplinary Center for Research Excellence in Science and Technology (iCREST); for his creative efforts in promoting interdisciplinarity on campus, he was awarded the prestigious President’s Cup in 2013. In 2014, Dr. Kaundal was appointed as the Director of High-Performance Computing and Bioinformatics Facility in the Institute for Integrative Genome Biology (IIGB) at the University of California, Riverside (UCR). In 2017, he joined the USU faculty and initiated a multidisciplinary research program in data science, bioinformatics, OMICS bigdata analytics, and high-performance computing. Dr. Kaundal also established a Bioinformatics Center inside the biotechnology building and has set up a new High-Performance Computing (HPC) Facility to cater to the needs of biological bigdata analysis on USU campus and elsewhere. He maintains ongoing collaborations with various groups at USU (departments of ADVS, PSC, CS), three USDA labs across the nation (Forage and Range Research, Logan; US Salinity Lab, Riverside; Cereals Crop Research, Madison), multiple state universities in the US, and with international teams working in the areas of Next-Generation Sequencing, -omics data science, comparative genomics, bigdata mining and computational modelling.

Teaching Interests

Data science, Bioinformatics, Computational biology, -omics bigdata analysis, High-performance computing. To fulfill the CAAS need for an upper-division or graduate-level course in data science, Dr. Kaundal has developed a new course (PSC 4150 / 6150) in Bioinformatics and -omics Bigdata Mining which is being offered every Fall semester. This course provides instruction on the computational mining of diverse and large multi-dimensional biological datasets, high-performance computing for bigdata analytics, introduce the operating system of Linux and data analysis on command line. It also include discussions of bioinformatics papers; heavy focus is on hands-on experience in NGS data analysis on the HPC cluster. The ultimate goal is to equip the participants with the necessary computational and programming skills so that they can independently mine and interpret -omics based bigdata sets. Students from diverse backgrounds usually sign up for this course, currently representing four colleges (CAAS, CoS, CoE, CoNR) and seven departments (PSC, ADVS, CS, Biology, NDFS, Biological Engineering, and Wildland Resources). In addition, Dr. Kaundal is contributing teaching to other courses on campus, e.g. ADVS 5260, CS 6900, and others.

Research Interests

At USU, Dr. Kaundal has developed an independent as well as a collaborative research program in bioinformatics & computational biology. Research in the Kaundal Artificial intelligence and Advanced Bioinformatics Lab (KAABiL) is multidisciplinary, primarily covering topics on computational mining of large multi-dimensional -omics datasets, computational modeling using supervised (Machine Learning) and unsupervised learning (Bayesian-based) techniques, and developing novel tools and software to apply the gained knowledge towards organismal improvement. Some specific scientific areas of interest are: Systems-based understanding of complex genetic traits (e.g. modeling of gene regulatory networks, visualization); Predicting intra- and inter-species protein interaction networks (host-pathogen interactions); Protein function prediction (subcellular localization, predicting pathways related to lignin degradation/synthesis, classification of other protein functions); Metagenomics (e.g. rhizosphere microbiome interacting with host); and Next-generation sequencing data analysis (develop packages for assembly, alignment, annotation, etc.). Dr. Kaundal has a multidisciplinary background in the life sciences with expertise in bioinformatics, plant breeding, genetics, artificial intelligence (AI), high-performance computing, and computational genomics. This diverse background is a consequence of the progression in his training (e.g. shift from plant breeding & genetics to bioinformatics followed by expansion of his knowledge to scientific programming, information management and bigdata analytics) and pursuit of new opportunities (e.g. predicting individual organisms’ characteristics from their DNA sequence). His lab brings together biology, computer science, engineering, and related disciplines to train the next generation of data scientists. To date, he has trained more than ten graduate and ten undergraduate students, one postdoctoral fellow, and three full-time bioinformatics staff members in his career research program.

Publications | Journal Articles

Academic Journal

An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.

Publications | MultiMedia


An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.

Publications | Technical Reports

Research Reports

An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.

Publications | Other

An asterisk (*) at the end of a publication indicates that it has not been peer-reviewed.


, Fall 2021
PSC 6150, 4150 - Bioinformatics and -OMICS bigdata mining, Fall 2021
PSC 4150, 6150 - Bioinformatics and Big Data Mining, Fall 2021
CS 6900 - Research topics in computer science, Fall 2021
PSC 6150, 4150 - Bioinformatics and -OMICS bigdata mining, Fall 2020
CS 6900 - Research topics in computer science, Fall 2020
ADVS 5260 - Methods in Biotechnology: Molecular cloning, Fall 2019
CS 6900 - Research topics in computer science, Fall 2019
PSC 6900 - Special Problems in Plants, Soils, and/or Climate, Fall 2019
ADVS 5260 - Methods in Biotechnology: Molecular cloning, Fall 2018
CS 6900 - Research topics in computer science, Fall 2018
ADVS 5260 - Methods in Biotechnology: Molecular cloning, Fall 2017

Graduate Students Mentored

David Guevara, Computer Science, January 2021
Raghav Kataria, Plants, Soils, and Climate, August 2020
Rousselene Larson, Plants, Soils, and Climate, August 2020
Nikhil Kurivella, Computer Science, August 2019
Naveen Duhan, Plants, Soils, and Climate, January 2019
Cristian Loaiza, Plants, Soils, and Climate, January 2018 - June 2020
Udarika Ediriweera, Computer Science, August 2018 - June 2019
Tyler Weirick, January 2012 - May 2014
Robyn Kelley, August 2011 - December 2013