Lead an organization of four groups within R&D: Process Design Development: Provide technical leadership and expertise for scale-up and commercialization of new technologies for renewable fuels, gas processing and hydrogen, adsorbents, refining and petrochemicals. This group provides support in developing techno-economic analyses, life cycle analyses, preliminary technology analyses, basic engineering package development for new product commercialization. Modeling and Optimization: Developing fundamental kinetic models, integrated process simulation tools and software packages to support R&D new product development programsDigital: Developing process technology analytics utilizing kinetic models, data analytics tools and cloud-based software platform in support of Honeywell UOP’s technical service offerings. Tools: Developing technical sales support tools and software to enable technical proposal generation, digitization of data and productivity improvements through automation

Managing and leading technical talent in developing models, digital solutions and analytics, integrated process simulation tools and software packages to support sustainable technology solutions and lifecycle technology solutions businesses.New product development: Leadership and consulting support to R&D teams during experimental planning and execution, development of conceptual process design and techno-economic analyses for new product development and technology commercialization.R&D transformation: Leading role in transforming R&D through digitalization, data analytics and model directed experimentation and developing state-of-the-art new capabilities and tools to enhance R&D productivity Building exceptional talent: Recruiting, onboarding and training highly diversified talent. Managing a diverse group of highly technical individuals, Sr Fellows to early career engineers. General coordinator of early career R&D training in the areas of operations research, techno-economic analysis, process modeling, Six Sigma and advanced statistics

Lead the efforts with Honeywell's Connected Performance Services business to expand cloud based optimization capabilities for refineries and petrochemical complexes using first principles models, domain knowledge and AI, machine learning techniquesCollaborated with multiple strategic business units to deliver integrated solutions Developed advanced analytics capabilities for commercial data sets and new data cleansing toolsActed as the product owner of a scrum team and adopted agile software development practices

Provide leadership and engineering knowledge to develop process design solutions for the evaluation and scale up of refining, petrochemical, and gas processing technologies. Led a 10+ team of engineers to provide conceptual process design support for new product development programs. Provided techo-economic analyses and basic engineering packages to facililate new technology development and commercialization.

Developed proof of concept and implemented new methods for lean experimental design to increase experimental efficiencyLeading role in improvements for statistical quality control in pilot plant testingCompleted Lean Expert training and led a project for pilot plant resource management

- Leading role in the development of new and improvement of existing technologies associated with UOP’s Gas Processing business. These technologies are used to remove impurities from natural gas and syngas produced by coal gasification.- Accountable for providing technical support in technology development for acid gas removal, including experiments, simulation, modeling and process flow scheme development. - Responsible for managing the technical knowledge base for gas processing technologies in the area of solvent based acid gas removal

Develop and scale-up new process technology for commercialization, process synthesis and design, techno-economic analysis, preliminary technology analysis, process simulation and optimization, flowsheeting, cost estimation

Research Areas:- Integrated product design, process design and optimal control for efficient and environmentally benign batch and biological processes under uncertainty- Characterization and quantification of uncertainties in chemical and biological processes using novel sampling techniques and stochastic differential equations- Statistical sampling techniques for increased efficiency in Monte Carlo molecular simulations for the prediction of thermodynamic and toxicological properties of chemicals

Developed new techniques for parameter estimation to improve yield estimation for various UOP processes to reconcile lab, pilot plant scale and commercial scale data