Work experience

• Gas and Chemical Commissioning Engineer

  LotusWorks

  2026.04-Current

  (4 months)
• Process Engineer

  Huminly

  2025.11-2026.03

  (5 months)
• Advanced Process Development Engineer

  Svante

  2022.09-2025.11

  (3 years)

  (3 years 3 months) • Served as pilot plant process engineering lead. Monitor, troubleshoot, design, analyze, and maintain operational excellence and process optimization for Pressure Swing (PSA) and Temperature Swing (TSA) gas adsorption testing pilot plants. • Process testing of MOF material characterization. Cycle, process development and optimization through pilot and demonstration unit testing, DOE, advanced statistical analysis and computational modelling using MATLAB, Python and Excel. • Project lead/manager for the commissioning of contaminant gas (NOx, SOx) test station, design of experimental test plan, advanced data analysis, PHA, SOP and HAZOP analysis. Improved commissioning time by 25% • Commissioned an industrial modular-sized gas diffusion testing rig. (CO2,O2, N2 gas separation) • Developed automation/control software to enhance process design, KPI and mass/energy balance calculation, data visualization and quality, and sorbent selection using Python and MATLAB. Improved testing accuracy and productivity by 85% • Experienced with instrumentation troubleshooting and process diagrams (P&ID, PFD, BFD), vacuum compressors, control and safety valves, mass spectrometers, heat exchangers, and humidifiers.
• Market Analyst

  ClearBlue Markets

  2022.05-2022.08

  (4 months)

  • Analyzed Cap & Trade Program between WCI and Washington State. • Research and developed Supply & Demand report for Washington State Carbon market. • Outlined carbon financial market and Cap & Trade Invest by understanding carbon credit trading and its policies. • Examined Machine Learning model developed for forecasting future carbon allowance price.
• Machine Learning Research Engineer

  (NSERC)

  2021.05-2021.08

  (4 months)

  • Completed research under Dr. Arvind Rajendran on Characterization of Sorbents for Gas separation and optimizing Pressure Swing absorption Carbon capture process using machine learning models. • Developed Artificial Neural Network and regression model through MATLAB to achieve over 92 - 95% accuracy for predicting Key Performing Indicators for Pressure Vacuum Swing Adsorption process. • Applied data analytic and data mining skills using Excel and Python to tabulate findings and results.

Educational experience

• University of Toronto

  Chemical Engineering

  2021.09-2024.06

  (3 years)

Certificates