London, Ontario, Canada
Chemical Engineer (Ph.D.) specialized in process design, predictive modeling, and process systems analysis, applying Lean Six Sigma principles to deliver sustainable engineering solutions. Over the past 5+ years, I have combined first-principles modeling with data-driven approaches to develop hybrid models for analyzing fluid flow, heat and mass transfer, and reaction systems. My experience includes: • Computational modeling, data analytics, and visualization using MATLAB, Python, and Power BI • Machine learning (ML) applications for model development, validation, and performance assessment • Engineering decision support for process design (PFDs & P&IDs) and process safety analysis (HAZOP) • Development of technical reports, dashboards, and presentations, translating complex data into actionable insights for cross-functional and non-technical audiences I am an active and approachable professional who values knowledge-sharing, mentorship, and teamwork. I enjoy connecting with engineers, researchers, and industry professionals working on process innovation, sustainability, and applied modeling. 🌱 Open to opportunities in process engineering, modeling, and sustainability-focused initiatives!
• Prepare and review compliance submissions under the Canadian Clean Fuel Regulations (CFR), British Columbia LCFS, and similar programs. • Interpret regulatory requirements and prepare client-facing deliverables (reports, memos, presentations). • Support regulatory audits and verification processes, including responses to verification bodies. • Support credit generation, compliance calculations, and evaluation of optimization opportunities. • Work with clients to collect, validate, and document operational data; maintain audit-ready records.
• Developed and implemented process simulation and optimization workflows (MATLAB/Python) to assess industrial system performance and support engineering design and operational decision-making. • Performed heat and material balance (H&MB) calculations and preliminary equipment sizing to support early-stage process design and configuration development. • Coordinated cross-functional initiatives by integrating experimental datasets with computational and machine learning models to reduce experimental dependency and improve predictive capabilities. • Authored peer-reviewed publications and project reports, communicating data-driven findings to technical and non-technical audiences through conference presentations (ISCRE27, CSChE 2024 & 2025) and sponsor engagements.
• Facilitated interdisciplinary teams in the development of sustainability-focused projects, supporting project structuring, coordination, and alignment between technical feasibility and environmental objectives. • Evaluated project feasibility and technical approaches using structured qualitative criteria, providing actionable feedback to strengthen engineering justification and design proposals. • Supported iterative refinement of project scope through technical reviews to strengthen alignment between feasibility and implementation constraints.
• Provided hands-on technical training to 180+ engineering students in industrial process simulation using Aspen HYSYS/Plus, enhancing understanding of process behavior, system operations, and emissions impacts. • Supervised and reviewed 50+ plant design projects, validating heat and material balances (H&MB), PFDs, and P&IDs, and evaluating equipment sizing calculations to ensure engineering rigor and ASME compliance. • Supported process safety evaluations, including HAZOP studies and risk identification, to strengthen safe and reliable engineering practices.
• Processed and validated multi-source environmental monitoring data using Advanced Excel (VBA) to develop indicators for air quality assessment, compliance reporting, and alignment with national environmental regulatory frameworks. • Performed statistical analysis of emissions datasets (PM2.5, PM10, SOx, NOx, CO) to identify trends, anomalies, and potential emission sources, supporting environmental performance evaluation and data-driven decision-making. • Developed and maintained environmental datasets and workflows to improve emissions tracking, data traceability, and transparency in reporting for regulatory applications.