Rajib Mukherjee

Bristol Myers Squibb, Devens, MA (Feb 2022 - Present)

     Process Analytics Engineer at Manufacturing Science & Technology

• Develop advanced multivariate analysis models for real-time multivariate process monitoring
• SIMCA® and SIMCA®-online for multivariate model development and online implementation of the models for process monitoring
• Maintain the existing modeling platforms
• Model updates with changing process conditions
• Develop advanced data analytics methods to transform manufacturing/lab data into actionable proactive insights. 
• Root cause analysis to identify process yield variation among batches.
• Data engineering, data analysis, data visualization, modeling, and prediction
• Deep Learning algorithms for digital twin of chromatographic separation processes

University of Texas Permian Basin, Odessa, TX (Aug 2019 – Dec 2021)

     Assistant Professor: Department of Chemical Engineering

• Courses taught: Chemical Engineering Fluid Operation, Chemical Engineering Analysis, Heat Transfer Operations, Chemical Engineering Thermodynamics, Chemical Engineering Mass Transfer, Advanced Engineering Analysis, Gas and Petroleum Processing, Senior Design, Chemical Engineering Plant Design
• Research: Natural Gas Processing, Optimal Sensor Networks, Water-Energy Nexus

Texas A&M University, College Station, TX (Oct 2015 – Aug 2019)

      Research Associate, Texas A&M Energy Institute 

• Data driven modeling and simulation for the SUPERFUND project. Application of Machine Learning (ML) algorithms including Deep Learning (DL) for spatiotemporal data analysis.
• Developing SUPERFUND, a python Django based tool for environmental and bio data analysis

      Assistant Research Engineer-Faculty, Gas and Fuels Research Center (GFRC), Texas A&M Engineering Experiment Station (TEES)

• Teaching “MATLAB® for Engineers”, “Applied Statistics for Engineers” to the visiting students in Chem Engg Department
• Energy and water network optimization under uncertainty.
• Reliability assessment of Eco-Industrial Park (EIP) under uncertain process conditions.
•  Selection of sustainable chemical process with multivariate statistical algorithms. 

     Visiting Assistant Professor, Department of Mechanical Engineering, TAMU

•  Teaching MEEN 357-501 Engineering Analysis for Mechanical Engineers

Vishwamitra Research Institute, Clear Lake, IL (May 2014 – Aug 2015)

    Research Engineer, Center for Uncertain Systems: Tools for Optimization and Management (VRI-CUSTOM)

• Development of stochastic optimization algorithms for sensor placement in water network systems, environmental pollution monitoring, coal power plant
• Computer aided molecular design (CAMD) of novel functional materials

US Environmental Protection Agency, Cincinnati, OH (Nov 2012 – Apr 2014)

    ORISE postdoctoral research fellow at Office of Research and Development/National Risk Management Research Lab (NRMRL), Sustainable Technology Division.

• Advancing Chemical Process Engineering by integrating sustainable technologies in process design. 
• Developing GREENSCOPE, a tool for sustainability evaluation of chemical process
• Data analytics with multivariate statistics (PCA, PLS) to select sustainability indicators.    

Tulane University, New Orleans, LA and Louisiana Tech University, Ruston, LA (Jun 2010 – Apr 2012)

    Postdoctoral research associate of Louisiana Alliance for Simulation-Guided Materials Applications (LASiGMA) at the Center for Computational Science (CCS), Tulane University.

• Supercomputing, application of novel tools for distributed high-performance computing (HPC). 
• Molecular Simulations, Molecular Dynamics (MD) simulations of biomolecular systems. 
• Data Analysis, application of multivariate statistics for analyzing structure and dynamics of biomolecular systems.

Louisiana State University, Baton Rouge, LA (Aug 2004 – May 2010)

    Dissertation from Process Systems Engineering Laboratory, Department of Chemical Engineering.

• Statistical Process Monitoring, image Analysis using multiresolution (wavelet) and multivariate (PCA), cluster and Fourier analysis.
• Multiscale Modeling and Stochastic Simulation, mesoscale lattice based modeling and important sampling Monte Carlo (MC) and Kinetic Monte Carlo (KMC) simulations of polymer solution systems for dynamics of phase separation
• Graduate Teaching Assistant in the Department of Chemical Engineering for:
  • Advanced Process Control, Optimization, Mathematical Methods in Chemical Engineering, Advanced Mathematics in Chemical Engineering, Process Dynamics & Control.

National Metallurgical Laboratory, Jamshedpur, India (Feb 2003 – Jul 2003)

    Project Engineer

• Numerical Analysis, solution of simultaneous Ordinary Differential Equations (ODE) obtained from mass and energy balance inside blast furnace reactor.

Tata Consultancy Services, India (Aug 1999 – Feb 2003)

    Systems Engineer

Technical Skills