U.S. Department of Energy

Pacific Northwest National Laboratory

Neeraj Kumar

Neeraj Kumar
Professional Title: 
Scientist
Email: 
Neeraj.Kumar@pnnl.gov
Biography: 

Dr. Neeraj Kumar, research scientist, has extensive research experience in computational chemistry, biophysics, structural and molecular biology, bio/cheminformatics, multi-omics data analysis, metabolic network, molecular modeling and simulation of complex biological systems. His graduate research was directed toward molecular level understanding of Vitamin B12 mediated enzymatic reactions and structure based drug design. Currently, his research interests are focused on developing mathematical and machine learning tools to solve challenging systems and synthetic biology problems at fundamental level using basic principles of statistical physics/chemistry including chemical properties and accurate data computed from first principles approximation. 

Education: 
  • Post-Doctoral, Pacific Northwest National Lab., Biophysics/Catalysis, 2017
  • Ph.D., University of Louisville, Louisville, Computational Chemistry/Biology, 2013
  • Graduate Research Intern, Bioscience Division, LLNL, Livermore, Computational Biology, 2012
  • M. S., Panjab University, Chandigarh, India, Chemistry/Cheminformatics
  • B. S., Panjab University, Chandigarh, India, Math/Chemistry/Physics
Awards: 
  • Outstanding Performance Award, Pacific Northwest National Laboratory, Computational Catalysis (April 2016)
  • Awarded Graduate Dean’s Citation for Excellence in Graduate Studies at University of Louisville, (Dec., 2013)
  • Lawrence Graduate Student Award, Biosciences Division, Lawrence Livermore National Laboratory, Livermore, CA (July, 2012)
  • Graduate Student Union (GSU) Fellowship, University of Louisville (Feb., 2011).
Research Interests: 
  • Computational modeling and analysis of genome-scale metabolic networks
  • Genome Annotation and Pathway Engineering
  • Multi-omics (transcriptomics, proteomics, and metabolomics ) data analysis, integration, and prediction
  • Machine learning/Deep Reinforcement Learning
  • Quantum Mechanics, Molecular Dynamics and Molecular Mechanics
  • Quantum Computing/Sensing and High Performance Computing
Publications: 

2018

  • Cannon WR, JD Zucker, DJ Baxter, N Kumar, SE Baker, J Hurley, and JC Dunlap. 2018. "Prediction of Metabolite Concentrations, Rate Constants and Post-Translational Regulation using Maximum Entropy-based Simulations with Application to Central Metabolism of Neurospora crassa." Processes 6(6):Article No. 63.  doi:10.3390/pr6060063

2016

  • Cardenas AJ, B Ginovska-Pangovska, N Kumar, J Hou, S Raugei, ML Helm, AM Appel, RM Bullock, and MJ O'Hagan. 2016. "Controlling Proton Delivery with Catalyst Structural Dynamics." Angewandte Chemie International Edition 55(43):13509-13513. doi:10.1002/anie.201607460
  • Pegis ML, BA McKeown, N Kumar, K Lang, DJ Wasylenko, P Zhang, S Raugei, and JM Mayer. 2016. "Homogenous Electrocatalytic Oxiygen Reduction Rates Correlate with Reaction Overpotential in Acidic Organic Solutions." ACS Central Science 2(11):850-856. doi:10.1021/acscentsci.6b00261

2015

  • Hulley E, N Kumar, S Raugei, and RM Bullock. 2015. "Manganese-Based Molecular Electrocatalysts for Oxidation of Hydrogen." ACS Catalysis 5(11):6838-6847. doi:10.1021/acscatal.5b01751
  • Darmon JM, N Kumar, E Hulley, CJ Weiss, S Raugei, RM Bullock, and ML Helm. 2015. "Increasing the Rate of Hydrogen Oxidation without Increasing the Overpotential: A Bio-Inspired Iron Molecular Electrocatalyst with an Outer Coordination Sphere Proton Relay." Chemical Science 6(5):2737-2745.  doi:10.1039/C5SC00398A

2014

  • Kumar N, DM Camaioni, M Dupuis, S Raugei, and AM Appel. 2014. "Mechanistic Insights into Hydride Transfer for Catalytic Hydrogenation of CO2 with Cobalt Complexes." Dalton Transactions 43(31):11803-11806.  doi:10.1039/c4dt01551g
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