Who Am I?

Fueled by a passion for pixels and algorithms, I'm currently navigating the exciting realms of AI, robotics, and computer vision. Think of me as a digital explorer, always tinkering with neural networks, teaching robots new tricks (like sorting packages or pollinating plants!), and striving to make data privacy a reality, not an afterthought.

When I'm not wrestling with PyTorch or designing the next intelligent system, you might find me pondering the mysteries of large language models or figuring out how to get a robot to understand human speech (spoiler: it involves lots of code and a bit of digital magic). My goal? To build cool, impactful things and maybe, just maybe, get one step closer to understanding true artificial intelligence.

Currently on a quest for a PhD to dive even deeper into the machine learning rabbit hole!

Armin Nejadhossein Qasemabadi

Education

M.A.Sc. Electrical Engineering, University of Windsor

Windsor, ON, Canada | 2022-2024

GPA: 4.0/4.0 (95.5/100)

Dissertation: Privacy-Preserving Deep Learning Model Development for Intelligent Transportation Systems

Supervisors: Dr. Shahpour Alirezaee, Prof. Majid Ahmadi

B.Sc. Engineering Science, University of Tehran

Tehran, Iran | 2017-2022

GPA: 16.18/20 (approx. 81/100)

Capstone Project: Remotely Operated Vehicle Localization using Deep Learning Approaches

Supervisor: Dr. Hadi Amiri

Professional Experience

Research Assistant, Mechatronics Lab, University of Windsor

Windsor, Canada | 2022-Present

  • Developed and evaluated privacy-enhancing machine learning models for ADAS, including RNN-based models (PyTorch) with Secure Multi-Party Computation (SMPC) for lane change prediction.
  • Conducted experimental validation on NVIDIA Jetson platforms (Orin Nano, Nano).
  • Contributed to AI-driven robotic systems for industrial automation, including an autonomous package sorting system (ABB IRB 360, Random Forest, NVIDIA Jetson) achieving 96% accuracy.
  • Designed a vision-guided robotic pollination system (UR5e robot, YOLO on NVIDIA Jetson) achieving 90% success.
  • Developed a speech-controlled autonomous wheelchair using OpenAI Whisper and LLMs on NVIDIA Jetson.

Graduate Assistant, University of Windsor

Windsor, Canada | 4 Semesters during M.A.Sc.

Provided teaching support for courses including Control Theory, Artificial Intelligence, Engineering Mathematics, and Signals and Systems. Responsibilities included grading, holding office hours, and assisting instructors.

Network Security Intern, Borna

Tehran, Iran | Jun 2021-Sep 2021

Gained experience with Cisco Switches/Routers, Sophos Firewall/VPN, VMWare ESXi, and Kaspersky security software. Developed and maintained internal knowledge base.

Key Projects

Privacy-Preserving Advanced Driver-Assistance Systems (ADAS)

Focused on developing and evaluating privacy-enhancing machine learning models (RNNs with SMPC in PyTorch) for intelligent transportation systems, validated on NVIDIA Jetson platforms.

Learning-based Robotic Sorting (VistaPrint Partnership)

Engineered an autonomous package sorting system using an ABB IRB 360 robot, computer vision (Random Forest, Intel RealSense), and a Python-based bin assignment system (NVIDIA Jetson), achieving 96% sorting accuracy.

Robotic Pollination in Greenhouses (GTN Partnership)

Designed and implemented a vision-guided robotic system (UR5e robot, YOLO on NVIDIA Jetson) for autonomous pollination, achieving a 90% success rate in field trials.

Speech-Controlled Autonomous Wheelchair

Developed a real-time control system integrating OpenAI Whisper and LLMs for natural language command execution on an NVIDIA Jetson platform.

Selected Publications

Nejadhossein Qasemabadi, A., Mozaffari, S., Ahmadi, M., Alirezaee, S. (2025). Privacy-Preserving Lane Change Prediction using Recurrent Neural Network with Secure Multiparty Computation. International Journal of Intelligent Transportation Systems Research. DOI: 10.1007/s13177-025-00489-6

Rasekh, B., Nejadhossein Qasemabadi, A., Mozaffari, S., Alirezaee, S. (2025). Pedestrian Intention Prediction Using Uncertainty-Aware Human Pose Estimation. Submitted to International Symposium on Signals, Circuits and Systems (ISSCS 2025)

Nejadhossein Qasemabadi, A., Mozaffari, S., Rezaei, M., Alirezaee, S. (2025). Uncertainty-Aware Lane Change Prediction for Autonomous Driving Using LSTM Networks. Accepted to Canadian Conference on Electrical and Computer Engineering (CCECE 2025)

Nejadhossein Qasemabadi, A., Mozaffari, S., Ahmadi, M., Alirezaee, S. (2024). Privacy-Preserving Lane Change Prediction Using Deep Learning Models. 2024 5th International Conference on Artificial Intelligence, Robotics and Control (AIRC), Cairo, Egypt. pp. 46-49

Skills

Deep Learning & AI

Computer Vision (YOLO, OpenCV), ML Algorithms (CNN, LSTM, Transformers, RNN), PyTorch, TensorFlow, Keras, SMPC

Programming

Python, C++, MATLAB/Simulink, ABB RAPID

Data Science

NumPy, Pandas, SciPy, Matplotlib, Scikit-learn

Robotics & Automation

ABB, Universal Robots (UR5e), RobotStudio, URSim, FactoryIO, Coppelia Sim, NVIDIA Jetson, Intel RealSense

PLC & HMI

Siemens S7-1200/S7-1500, TIA Portal (LAD, FBD), WinCC

Cloud & Deployment

Google Cloud Platform (GCP), Docker, Git

Contact

Email: nejadho@uwindsor.ca / nezhad.armin@gmail.com

LinkedIn | Google Scholar