About Me

I'm an AI Researcher at Huawei Technologies Canada based in Edmonton. During my Masters in Computing Science at the University of Alberta, I focused on neurosymbolic programming and reinforcement learning, supervised by Levi Lelis and Sandra Zilles. Before that, I completed my B.Sc. in Computer Engineering at Amirkabir University of Technology.

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Education

M.Sc. Computing Science

University of Alberta, Edmonton, AB | 2023 – 2025

Supervisor: Levi Lelis and Sandra Zilles | GPA: 3.8

B.Sc. Computer Engineering (AI)

Amirkabir University of Technology, Tehran, Iran | 2018 – 2023

Major: AI; Minor: Networks | GPA: 18.75/20 (3.96/4)

Publication

Common Benchmarks Undervalue the Generalization Power of Programmatic Policies

RLC 2025 Programmatic RL Workshop

Amirhossein Rajabpour, Kiarash Aghakasiri, Sandra Zilles, Levi Lelis.

arXiv Code Project Page

Work Experience

AI Researcher | Huawei Technologies Canada

Oct 2025 – Present

Working on efficient inference of Large Language Models (LLMs) on Smartphones using the LiteRT Framework.

Technical Advisement | Alberta Machine Intelligence Institute (Amii)

Sep – Oct 2024

1-month project on advanced AI/ML methods to enhance real-time intrusion detection and anomaly detection in high-speed network storage infrastructures.

Machine Learning Engineer | Crouse PJS Co.

Oct 2021 – Jan 2022

  • Localizing LEDs on monitors for quality control.
  • Clustering LED light pixels using fuzzy C-means for luminance/wavelength extraction.
  • Applying regression models per color to detect malfunctioning hardware.
DevOps Engineer Intern | Graph Co.

Nov 2020 – Apr 2021

Hands-on experience with Docker and cloud-native tooling.

Research Experience

Research Assistant | University of Alberta

May 2024 – Jul 2025 | Supervised by Levi Lelis & Sandra Zilles

  • Refined neural policies (RL agents) through targeted architectural and training adjustments, enabling them to match or outperform programmatic policies in generalization on key benchmarks.
  • Proposed new benchmarks highlighting strengths of programmatic policies (e.g., memory-based reasoning).
  • Built end-to-end training/evaluation pipelines (Python, Bash, PyTorch, TensorFlow).
  • Used Large Language Models to generate/assess interpretable policies where RL underperforms.
  • Work accepted at RLC 2025 Programmatic RL workshop.
Individual Study Course Project | University of Alberta

Jan – Apr 2024

Improved "Unveiling Options with Neural Decomposition" using hill-climbing search and genetic algorithms.

Bachelor’s Thesis | Amirkabir University of Technology

Mar – May 2023 | Supervised by Mohammad Rahmati

Developed a face-aging platform using generative models (e.g., CycleGAN, reversible models).

Technical Skills

Programming Languages
PythonC/C++JavaKotlinOctave
AI & Machine Learning
PyTorchTensorFlowKerasScikit-learnFast.aiNumPyPandas
Backend & Dev Tools
MySQLPostgreSQLDjangoFlaskDockerGitOpenCVLaTeX

Teaching Assistant

Graduate Teaching Experience | University of Alberta

  • CMPUT 365: Introduction to Reinforcement Learning
    Fall 2025 | Instructor: Marlos C. Machado

    Labs, grading assignments, and exams.

  • CMPUT 366: Search & Planning in AI
    Fall 2024, Winter 2025 | Instructor: Levi Lelis

    Lectures, labs, and grading for all course components.

  • CMPUT 291: Introduction to File & Database Management
    Fall 2023, Winter 2024 | Instructors: Davood Rafiei & Arash Dargahi Nobari

    Lectures and lab sessions, grading projects, assignments, and exams.

Undergraduate Teaching Experience | Amirkabir University of Technology

  • Principles of AI
    Fall 2022 | Instructor: Mahdi Javanmardi

    Designed and graded projects covering CSPs, search, and RL.

  • Cloud Computing
    Fall 2022 | Instructor: S. Ahmad Javadi

    Designed assignments and labs focused on APIs, cloud services, Docker, and Kubernetes.

  • Internet of Things
    Fall 2022 | Instructor: Siavash Khorsandi

    Developed scenarios for sensor/actuator integration and Arduino programming assignments.

  • Algorithm Design
    Winter 2021, Fall 2021, Winter 2022 | Instructors: Alireza Bagheri & Sajad Shirali-Shahreza

    Graded assignments on greedy algorithms, divide & conquer, and dynamic programming.

Projects

I maintain a variety of open-source projects ranging from Reinforcement Learning implementations to Computer Vision platforms.

Explore Projects on GitHub

Honors & Awards

  • Fully funded admission to UAlberta (CS, ECE, Radiology & Diagnostic Imaging), Western Ontario (CS) (2023).
  • Nationwide Mathematics University Entrance Exam (Iran): Top 1% among 140,000+ applicants.
  • 4-year scholarship, Amirkabir University of Technology.