• Pioneering THC Detection & Multi-Device Development: Spearheaded R&D and machine learning model development for Cannabix Breathalyzer V.4, the first handheld for real-time THC detection, with an intuitive GUI enabling device registration, Wi-Fi setup, and automated cloud data uploads. Expanded expertise to the Breath Logix alcohol and health breathalyzers, enhancing device functionality and real-time data capabilities across product lines.• Data-Driven Model Optimization: Conducted sensor analysis and feature extraction to isolate optimal parameters for THC detection, while minimizing environmental interferences. Developed models across devices to ensure reliable detection for THC, alcohol, and health markers, addressing parameters like humidity and temperature to enhance selectivity and accuracy.• Advanced Signal Processing & ML Algorithms: Designed ML models for detecting THC, CBD, alcohol, and health markers such as ketosis and air quality. Applied advanced signal processing to the Breath Collection Unit for high-precision data capture and extended model reliability to multiple devices for consistent, real-time results.• Cloud-Based Visualization & User Access: Built an AWS-integrated portal using S3, SageMaker, and Cognito, providing customers worldwide with secure access to device data and predictive insights. Enabled seamless access to dashboards, real-time alerts, and automated reporting across Cannabix product lines, supporting global reach and real-time data visualization.

• Software Development: Developed a software for automating “the data reading” and “optimization-based EIS signal analysis”. The software is being used by people with no engineering or coding background in the maintenance/sales section.• Automation: Automated data cleaning, data analysis, and data visualization in real time using Python. The model is being used by experimentalists for Ballard air-cooled and water-cooled fuel cell stacks.• Conference Presentation: Presented Ballard Power Systems as the lead scientist in International Conference of Impedance Spectroscopy (IWIS), Sep 2022, Chemnitz, Germany

• Numerical Modeling & ML: Created a numerical model in C++ and Python to analyze the effects of air stoichiometry on hydrogen emissions and developed a classifier/regressor using ANN.• Anomaly Detection: Utilized Autoencoders, One-Class SVM and K-Means Clustering in Python for detecting hydrogen starvation in Ballard PEMFC stacks in real-time.

• Virtual Hydrogen Sensor for Fuel Cells: Developed an innovative virtual sensor for detecting fuel starvation in fuel cells, leveraging machine learning and deep learning techniques on large datasets using Python, MATLAB, and Microsoft Visual C++.• High-Temperature SOFC Modeling: Created a computationally efficient pseudo-2D model in Microsoft Visual C++ and MATLAB, enabling hydrogen concentration, current density, and cell temperature predictions up to 10⁵ times faster than existing methods.• Fuel Cell Modeling Review: Published an in-depth review on fuel cell CFD and FEM modeling, with applications in ANSYS and COMSOL.• PEMFC Catalyst Optimization: Enhanced PEMFC maximum power density by 14% through a two-phase model and genetic algorithm, using Microsoft Visual C++ and MATLAB.• CFD & Optimization for PCM Units: Conducted MATLAB and ANSYS Fluent simulations for CFD modeling and phase change material optimization, improving efficiency for a 72-kW solar-assisted absorption chiller.• Magnetic Nanoparticle Modeling: Utilized COMSOL Multiphysics and ANSYS Fluent UDFs for CFD modeling of Fe₂O₃ nanoparticles, pioneering analysis of magnetic field effects on fluid streamlines under electromagnetic fields.• NZEB Analysis & Optimization: Designed economic, environmental, and energy analysis methods for Net Zero Energy Buildings, achieving a 63% energy efficiency increase in both residential and commercial buildings.• Inverse Analysis for SOFC Materials: Estimated multi-physiochemical properties of SOFC materials (yttria-stabilized zirconia and lanthanum strontium manganite) using pattern search optimization in Microsoft Visual C++ and MATLAB.• Nano-Refrigerant Heat Transfer: Achieved a 109% improvement in condensation heat transfer by experimentally investigating R600a/POE/CuO nano-refrigerant in optimized tube geometry.

holding lectures/labs/marking/workshops for the following courses at SFU:• Engineering Graphics and Design (SolidWorks), supervisor: Krishna Vijayaraghavan, Fall 2017, Fall 2018, Fall 2020.• Calculus I-III, Summer 2017-Spring 2021.• Process, form, and convention in professional genres, supervisor: Maureen Hindy, Spring 2017- Spring 2021• The business of engineering II, supervisor: Maureen Hindy, Summer 2018, Summer 2019, summer 2020

Research Interests• Fuel Cells• Energy Efficient Thermal Management (Thermal Storage, Nano-Scale Heat Transfer)• Experimental and Numerical studies on Heat Transfer.• Energy systems (Solar-HVAC)• Multi-phase Systems (Boiling, Condensation, and Solidification)• CFD (Fluid Mechanics, Bio-Engineering, Turbo-machinery)Experience:• In collaboration with Shahid Rajaei 1000 MW thermal power plant: Designed and optimized an innovative system of a hybrid dry cooling tower and a solar chimney using ANSYS Fluent and MATLAB. The novel design showed a 0.5 percent increase in the total thermal efficiency of the plant.• Leading a team of 15 to design a residential net-zero energy building (NZEB) in Tehran: Applied passive techniques such as thermal mass, Trombe-wall, roller shading, flat-plate and evacuated solar collectors, fiber optics, photovoltaic panels, solar absorption heat pumps, etc. • Feasibility analysis of employing a Gurney Flap in the design of supercritical NASA airfoils: Numerical turbulent simulation with MATLAB and ANSYS Fluent showed up to 50 percent increase in lift to drag ratio.• Determining the exact temperature distribution of a vertical drill embedded partly in the soil with certain pressure and friction factor, introduced to variable heat flux from beneath using a 3D analytical model.• Analysis of a chip-and-the-substrate transient surface temperature variations during a model of very large-scale cooling microelectronic circuits with ANSYS Fluent, MATLAB and Microsoft Visual C++.• Book editor, and translator (to Persian), “An Introduction to Heat Transfer”, THEODORE L. BERGMAN, ADRIENNE S. LAVINE, FRANK P. INCROPERA, DAVID P. DEWITT, Translators: Prof.H.Shokouhmand, B.Ghorbani, M.A.Bijarchi

M.Sc. Courses• Advanced Fluid Mechanics, Supervisor: Amir Nejat, Spring 2014• Continuum Mechanics, Supervisor: Alireza Riasi, Fall 2013• Advanced Convection Heat Transfer, Supervisor: Mehdi Ashjaee, Spring 2014B.Sc. Courses:• Heat transfer I, Supervisor: Farshad Kowsari, Spring 2012• Heat transfer I, Supervisor: Mehdi Ashjaee, Fall 2012 & Fall 2013 & Fall 2014• Heat transfer II, Supervisor: Hossein Shouhmand, Fall 2012 & Spring 2013 & Spring 2014• Thermodynamics I, Supervisor: Mehdi Ashjaee, Fall 2013 & Spring 2014• Thermodynamics II, Supervisor: Pedram Hanafizadeh, Spring 2013• Fluid Mechanics II, Supervisor: Alireza Riasi, Fall 2012• Thermal Power Plants, Supervisor: Mehdi Ashjaee, Fall 2013• Solar Energy, Supervisor: Mehdi Ashjaee, Spring 2012• Statics, Supervisor: Caren Abrinia, Spring and Fall 2010 & Spring and Fall 2011 & Spring 2012• Mechanical Design II, Supervisor: Caren Abrinia, Spring and Fall 2014