Experienced Researcher and Software Developer with dual M.Sc. degrees in Physics and one in Computer Science, complemented by a robust mathematical and statistical analysis skill set. Expertise in Data Science, Deep Learning, Neural Networks, and Machine Learning, with proficiency in Decision Tree, Clustering, and Regression analysis. Skilled in Image Processing, Parallel Computing, and AI Modeling. Demonstrated success in Industrial R&D, particularly in Power Electronics and Smart Thermostat Software development.
ENA Solutions, Calgary, Canada (11/2023 - 02/2024)
- Led AI predictor development for ENA Smart Thermostats, achieving <2.0 °C deviation in accuracy.
- Innovated with multiple Machine Learning models and Neural Networks, enhancing data preprocessing and feature engineering.
- Managed 600K+ data points, per device, using diverse Machine Learning models and Neural Networks.
- Developed an OCR-based Automated Energy Bill Parser, focusing on efficient data extraction from PDFs and images.
- Oversaw RESTful API data flow in Python, supporting communication for 200+ IoT devices.
- Improved code readability and maintainability by 50% through Functional Programming and OOP.
Niroutrans Co., Shiraz, Iran (01/2017 - 08/2019)
- Developed a C++ program for optimized electric insulation designs of Electrical Bushings, integrating with Ansys Maxwell 2D for EM field simulations.
- Led the establishment of an internal RIS electrical bushing production line up to 15Kv, managing a team of 8 electrical engineers.
- Created macro-based Excel tools for efficient data analysis and product troubleshooting.
- Acted as a scientific consultant for diagnosing and solving issues in High/Medium/Low Voltage products.
Saskatchewan Polytechnic, Saskatoon, SK, Canada (03/2024 - 2025)
- AI Engineer
- Software Developer
University of Saskatchewan, Saskatoon, SK, Canada (2022 - 02/2024)
- Simulated plasma behavior of charged particles in electromagnetic fields using Julia and C++, enhancing understanding of particle dynamics in magnetic nozzles.
- Performed parallel computing in Julia on CPU and GPU, demonstrating enhanced performance with GPU, vital for multiprocessing efficiencies in charged particle systems.
University at Albany, Albany, NY, U.S. (2019 - 2021)
- Devised mathematical models to detect Digital Holographic Microscopy (DHM) optical aberrations, achieving 3x faster image processing through Cythonization and Multiprocessing.
- Created a Python, OpenCV application for biophysics cell image analysis, reducing processing time from weeks to seconds for extensive datasets.
Shiraz University, Shiraz, Iran (2013 - 2016)
- Conducted a dHAN model simulation using C++ to mimic brain function in 300-500 neuron networks, revealing exponential trends in network activity over a 3-month period, resulting in a substantial 2GB data set.
- Applied Runge-Kutta 4th order method for precise system analysis and modeling in complex systems.
Shiraz University, Shiraz, Iran (2009 - 2013)
- Python
- C++
- Julia
- Multiprocessing
- Numpy
- Pandas
- Scikit-learn
- TensorFlow
- PyQT
- PyTorch
- Matplotlib
- Plotly
- Selenium
- Beautiful Soup
- Linear Regression
- Random Forest
- LightGBM
- Gradient Boost
- SVR
- KNN
- CNN
- RNN
- FNN
- SVR
- Skforecast
- LSTM
- PCA
- MySQL
- SQL
- SQLite
- Excel
- Statistical Analysis
- Docker
- Kubernetes
- Google Cloud
- RESTful API
- OpenCV
- Postman
- JSON
- YAML
- Git
- SVN
- Google Colab
- Jupyter
- GitHub
- BitBucket
- Miro
- ClickUp
- Figma
- Blockchain Structure
- Solidity
- Hardhat
- Windows
- Linux
- Mac
- Introduction to Containers w/ Docker, Kubernetes & OpenShift - IBM via Coursera, 2023
- Foundations of Cybersecurity - Google via Coursera, 2023