CV

Curriculum Vitae

Education

• Doctorate in Mathematics and Industrial Engineering
  • Ecole Polytechnique de Montreal, Montreal, Quebec
  • Sept 2021 - Present
  • Conducting research on optimization techniques for low precision deep neural networks training under the supervision of Prof. Dominique Orban
  • Analyzing floating point arithmetic for deep learning
  • Awarded NSERC Postgraduate Scholarships 2022
  • Relevant coursework: MILA: Matrix and tensor factorization techniques for machine learning, MILA: Reinforcement learning and optimal control, McGill: Matrix computations, PolyMtl: Operational research, PolyMtl: Numerical optimization
• Master of Science in Electrical Engineering
  • McGill University, Montreal, Quebec
  • 2017 - 2020
  • Thesis: Semi-deterministic finite interval estimation of linear system dynamics and output trajectory
  • GPA: 4.0/4.0
  • Relevant coursework: Mathematical Foundations of Systems, Probability and Random Signals 2, Filtering and Prediction for Stochastic Systems, Regression and Analysis of Variance, Introduction to Time Series Analysis, Optimization and Optimal Control, Fundamentals of Academic Writing in English
• Bachelor of Engineering, Computer Engineering (Co-op)
  • University of Guelph, Guelph, Ontario
  • 2012 - 2017
  • Minor in Computer Science
  • GPA: 84/100

Research & Work Experience

• Data Science PhD Intern (Machine Learning Research)
  • Huawei Technologies, Noah’s Ark’s AI lab, Montreal, Canada
  • Nov 2021 - March 2022
  • Worked on training quantized CNN models for efficient inference
  • Supervisor: Prof. Vahid Partovinia
• PhD Research Scientist Intern
  • GERAD, Montreal, Canada
  • July 2021 - September 2021
  • Developed and implemented optimization techniques for low-precision deep neural network training.
  • Analyzed floating-point errors in inner products used in deep learning.
  • Coded in Julia.
  • Produced a technical report on mixed-precision floating-point operations for inner products.
  • Supervised by Prof. Orban.
• Co-founder, VP of Research
  • Notos Technologies, Montreal, Canada
  • Nov 2019 - July 2021
  • Developed proprietary technology combining AI and reinforcement learning to power fixed-wing drones through autonomously harvested wind energy.
  • Raised $800K in seed money and established collaborations with universities for cutting-edge research.
  • Led the team’s technical direction and supervised interns.
  • Implemented smart decision systems using reinforcement learning.
  • Designed and implemented the MVP and worked on the IP roadmap.
• Machine Learning Research Engineer Intern
  • Huawei Technologies, Noah’s Ark’s AI lab, Montreal, Canada
  • May 2019 - September 2019
  • Conducted research on optimizing Deep Neural Networks using various compression methods.
  • Worked on edge device computation and model compression techniques.
  • Supervised by Prof. Vahid Partovinia.

Teaching Experience

• Instructor & Course Designer- CCCS 315 Data Structures and Algorithms
  • McGill University, Montreal, Canada
  • Jan 2022 - now
  • Programming techniques used to implement algorithms on computers with an object-oriented programming.
  • Study data structures which support the efficient manipulation of data.
  • Prepare and design the course for future online training.
  • Teaching two sections during the winter term.
  • Manage and assign tasks to Teacher Assistance of the course.
• Instructor & Course Designer- CCCS 300 Programming Techniques 1
  • McGill University, Montreal, Canada
  • Sept 2022 - now
  • Designed and developed course material for CCCS 300, a graduate-level course on fundamental programming techniques, concepts, and data structures, and an introduction to Object-Oriented Programming.
  • Created assignments and assessments to evaluate students’ understanding and mastery of the course material.
  • Delivering lectures, providing feedback, and offering additional support to students during office hours.
  • Utilizing various tools and techniques to facilitate learning, including interactive coding exercises and group projects.
  • Collaborating with other instructors and departmental staff to ensure course alignment with departmental objectives and standards.
• Instructor- CCS2 505 Programming for Data Science
  • McGill University, Montreal, Canada
  • Sept 2021- Dec 2021
  • Taught Python as a tool for Data Science in a graduate-level course with a class size of 50 students.
  • Developed and delivered course content on tools and techniques for designing and implementing software applications using modern programming languages relevant to data science.
• Instructor- Introduction to Algorithm
  • Matrix College, Montreal, Canada
  • Nov 2019- May 2021
  • Taught based on the Introduction to Algorithms.
  • Managed and provided support to a class of 40 students.
  • Discussed topics related to data structures and software design.
• Instructor- Object Oriented Programming
  • Matrix College, Montreal, Canada
  • Nov 2019- May 2021
  • Taught Object-Oriented Programming to 150 students over the course of 3 terms.
  • Managed TA work balance to ensure effective support for students.
  • Designed and delivered interactive classes both in person and over Zoom.
  • Designed and organized assignments and hands-on exams to assess students’ understanding and skill development.
  • By the end of the course, students gained practical experience in coding Java and OOP, having written over 100 Java programs.
• Instructor- Big Data
  • Matrix College, Montreal, Canada
  • May 2020-May 2021
  • Taught the basics of Big Data, including its characteristics and challenges.
  • Organized the students into groups to facilitate collaboration and teamwork.
  • Taught the basis of Case Study Analysis to help students understand real-world Big Data applications.
  • Designed interactive classes to engage students and enhance their learning experience.
  • Designed and organized assignments and hands-on exams to assess students’ knowledge and skills.
  • Introduced students to the Hadoop, MapReduce, and Spark ecosystems, as well as the concept of Big Data architecture.
  • Managed the workload of teaching assistants to ensure a smooth course delivery.
• Head Teaching Assistant
  • School of Continuing Studies, McGill University, Montreal, Canada
  • Sept 2018 – May 2019
  • Teaching Assistant for Statistical Machine Learning.
  • Coordinate and teach python and machine learning libraries to over 50 students.
• Teaching Assistant
  • McGill University, Montreal, Canada
  • Jan 2018 – April 2018
  • ECSE 305 Probability and Random Signal.
  • Prepare and present all the scheduled course tutorials.
• Teaching Assistant
  • School of Continuing Studies, McGill University, Montreal, Canada
  • April 2018 – May 2018
  • Taught Computational Applied Statistics.
  • The course was based on Statistics and Data science Methodology.
• Teaching Assistant
  • University of Guelph, Guelph, Canada
  • Jan 2013 – Jan 2016
  • CIS*1500, C programming course.
  • CIS* 1000, Web development course.
  • Provided input to improve assignments for 433 students.
  • One of the few undergraduate students who were selected to Teach C programming.
  • Enhanced time management and prioritize skills in juggling heavy academic load.
  • Developed strong communication skills in one on one and in-group settings.

Skills

• Programming Languages: Python, Java, C++
• Machine Learning: TensorFlow, PyTorch, scikit-learn
• Deep Learning: CNNs, RNNs, GANs
• Optimization Techniques
• Data Analysis and Visualization: Pandas, Matplotlib, Seaborn
• Version Control: Git
• Software: MATLAB, Julia

Awards & Honors

Awards & Competitions

• NSERC PGSD
  • NSERC (Natural Sciences and Engineering Research Council), Montreal, Canada
  • March 2022-2025
  • Doctoral (PGS D) program provides financial support to high-calibre students.
  • Recognized for high academic and leadership standing.
  • Total value: $63,000
  • Accepted
• EPFLglobaLeaders Fellowship
  • EPFL (École Polytechnique Fédérale de Lausanne), Lausanne, Switzerland
  • March 2021
  • Doctoral fellowship program funding early-stage researchers to become leaders in the transition towards sustainable societies.
  • Only Forty-eight doctoral fellows selected.
  • Total value: $125,000
  • Declined
• Walter C. Sumner Fellowship
  • McGill University, Montreal, Canada
  • March 2018
  • Total value: $8,000
  • Declined
• MITACS Accelerate
  • McGill University, Montreal, Canada
  • March 2018
  • Secured funding of $45,000 to implement a predictive system for NexJ Systems.
  • Utilizing LSTM and random forest algorithms for predicting and classifying error types.
  • Conducting remaining useful life analysis to predict the timing of future failure events.
• Host and the Mentor for Guelph Programming Competition
  • University of Guelph, Guelph, Canada
  • Feb 2017
• Undergraduate Research Award (NSERC)
  • University of Guelph, Guelph, Canada
  • Oct 2016
• Haessler Family Engineering Scholarships
  • University of Guelph, Guelph, Canada
  • Oct 2015
  • The scholarship is awarded to students who demonstrate commitment to the engineering profession through employment and volunteer activities.
  • $5000
• Ontario Engineering Competition (OEC 2015)
  • Represented the Guelph School of Engineering in the Programming category at the 2015 Ontario Engineering Competition.
• Ontario Engineering Competition (OEC 2014)
  • Second Place
  • Computer Programming contest with the designing of an App for the Blackberry platform using the Google API.
  • Developed a new Algorithm and proved it using the Midpoint method (Numerical method).
• International Brotherhood of Electrical Workers
  • University of Guelph
  • Oct 2013
  • Awarded to the student with the highest cumulative average.
• University of Guelph Entrance Scholarship
  • University of Guelph
  • Oct 2012