Riyan Roy

Location: Burnaby, British Columbia Email: riyan.roy@mail.utoronto.ca / ryanroy9698@gmail.com
Project Portfolio: Github Link
LinkedIn URL: LinkedIn

Summary

Process Engineer Specialist with 3+ year of experience in Process Data Analysis, Carbon Capture & Storage, Process Development, First Principles based Modelling & Simulation, Adsorption, Characterization, Cycle Testing, Data Science & Machine Learning.
Extensive Experience in deploying data-driven methodologies to address challenges in the process industry, adept at optimizing operations, creating real time dashboards for monitoring process parameters.
Experience in designing and developing treatment technologies for water and wastewater treatment plants.
Proficient in deploying data-driven methodologies, optimizing operations, and creating real-time dashboards for informed decision-making.

Carbon Capture: Adsorption, Sorbent Characterization, Cycle Testing, Process Development, Sensitivity Analysis, Heat & Mass Balance.
Process Engineering: P&IDs, PFDs, Aspen HYSYS, HTRI, PLC/DCS, Control Philosophy, Modeling & Simulation.
Programming Languages: Python, Pyspark, MATLAB, SQL, NoSQL.
Data Visualization: Plotly Dash, Matplotlib, Seaborn, Bokeh, Tableau, Power BI.
Data Analysis: Data Wrangling, Exploratory Data Analysis, Dimensionality Reduction, Optimization, Model Drift.
Water Treatment: P&IDs, RO Membrane Projections, Water/Wastewater Treatment Schema.

Analyzed 150+ operational process tests and instruments to identify trends, contributing to cycle testing, parameter selection, and process development.
Studied competitive CO2/H2O adsorption (CALF-20 and amine-based adsorbents) and energy consumption, optimizing processes through ML-based multi-objective optimization. Validated model predictions through Test Station demonstrations.
Developed and validated applications using Python for KPI calculations, Mass Balance, Breakthrough Testing, and Pressure Drop Testing, specializing in carbon capture projects.
Led mass balance initiatives, providing recommendations and addressing daily issues with mass spectroscopic signals.
Designed and implemented KPI dashboards for real-time monitoring of crucial metrics, employing system profile visuals for comprehensive insights and process improvement in capturing carbon at pilot scale. More information about the VeloxoTherm^TM Process Svante Reference:

Conducted a comprehensive review resulting in a 40% increase in water treatment capacity.
Led a greenfield project for an FMCG major in Europe with a 5/5 client rating.
Utilized Aspen HYSYS for simulating plant behavior and optimizing system performance.
Provided a novel water treatment solution, recommending Veolia ActinaTM for enhanced water quality.

Implemented quality improvement procedures, achieving a 20% reduction in defects.
Supervised internal quality audit program for 50+ audits, generating monthly audit reports.

Conducted data collection, preprocessing, and visualization using Plotly Dash.
Engineered predictive models for accurate estimation of H2S and SO2 concentrations.
Utilized Cloud technologies for automated data preprocessing and model fine-tuning.

Implemented advanced machine learning algorithms for anomaly detection.
Developed a comprehensive dashboard for data visualization using Tableau.
Employed SHAPLEY analysis for insights into the contribution of various parameters.

Utilized a comprehensive dataset for developing multivariate regression models.
Demonstrated proficiency in Microsoft Azure Machine Learning and data visualization tools.

University of Toronto: MEng in Chemical Engineering with an Emphasis in Data Analytics (Sept ‘22 – April ‘24)

Principal Component Analysis application in process engineering for creating optimal batch size for a chemical plant
Healthcare Analytics
Financial Data Modeling for Fault Prediction
Recommender System
Intrusion Detection System
Miscellaneous Projects

My primary focus is on the application of Artificial Intelligence in Process Engineering, Control, and Modeling.