Curriculum Vitae

Education

2023 – Present
Ph.D., Electrical and Computer Engineering, University of Manitoba
Supervisor: Prof. Miroslaw Pawlak

2016 – 2019
M.Sc., Artificial Intelligence, Shahid Bahonar University of Kerman
Thesis: Multi-Agent Path Planning Based on Evolutionary Methods
Supervisor: Dr. Aliakbar Niknafs

2007 – 2012
B.Sc., IT Engineering, Payame Noor University of Kerman
Thesis: Security and Reliance in Ecommerce
Supervisor: Dr. Hemat Pour

Academic Projects

2023 – Present

• Developed and evaluated a machine learning algorithm using polynomial regression to fit and predict data from both noisy and noise-free datasets, implemented regularized and non-regularized models, and analyzed overfitting by comparing errors between training sets.
• Optimized a Simulated Annealing algorithm for the Travelling Salesman Problem by increasing inner loop iterations to 5000 and introducing random route generation functions, improving the algorithm’s ability to escape local minima and find shorter routes.
• Developed and evaluated an enhanced autoencoder for image reconstruction, inpainting, denoising, and anomaly detection, optimizing latent space dimensions and activation functions.
• Implemented and evaluated a Variational Autoencoder (VAE) for generative modeling, conducting experiments with random sample generation, FID and IS metrics, latent space interpolation, and comparing its performance with a standard autoencoder for diverse tasks.

2018 – 2019

• Multi-robot path planning in an unknown environment with obstacle by evolutionary methods to reach goals.
• Implementation of robot path planning algorithm in V-REP simulator and writing a plugin for it.
• Implementation of PSO, GSA, Cellular PSO and GWO algorithms in Lua and C++.

2016 – 2017

• Discovering frequent itemsets and association rules using  the Apriori algorithm.
• Implementation of Rotation Forest, Random Forest, ID3 and C4.5 algorithms to check accuracy in different data sets.
• Implementation of machine learning methods in Tic-Tac-Toe game and Rooster Chase.
• Detecting and quantifying fruits in different kinds of image with simple and complex background by digital image processing techniques.
• Generating fuzzy rules by learning from examples (Wang & Mendel)
• Implementation of Support Vector Machines (SVMs) and Bayes classifier for gender classification in an image dataset with 400 distinct people with different facial expressions and under different lighting conditions.

Teaching Experience

Teaching Assistant – Numerical Methods for Electrical Engineers
2024 – Present      University of Manitoba 

• Led lab sessions, provided one-on-one support, and graded assignments
• Assisted students with MATLAB programming, numerical analysis techniques, and problem-solving methods

Teaching Assistant – Signal Processing
2024 – Present      University of Manitoba 

• Guided students through lab work and assignments related to digital signal processing
• Supported students with MATLAB, Fourier transforms, and filter design concepts

Publications

Toufan, N., Niknafs, A. ‘’Robot path planning based on laser range finder and novel objective functions in grey wolf optimizer’’. SN Appl. Sci. 2, 1324 (2020).

https://link.springer.com/content/pdf/10.1007/s42452-020-3093-5.pdf

Research Interests

• Machine Learning
• Deep Learning
• Transfer Learning
  
• Self-Supervised Learning
• Reinforcement Learning
• Heuristic Algorithms
• Robotics
• Image and Signal Processing
• Data Mining

Online Courses

Optimization Problems and Algorithms   “Udemy”

Deep Learning Specialization “Coursera”

Work and Professional Experience

• Installing and configuring computer hardware, software, systems, printers and scanners.
• Investigating, diagnosing and solving computer software and hardware faults.
• Repairing equipment and replacing parts.
• Establishing, maintaining and troubleshooting network system hardware.
• Programing network router/switch and creating a domain in windows server.
• Creating and maintaining website with Drupal and WordPress CMS.

Honors and Awards

2016 – 2019

• Ranked within the top 2% among more than 30,000 participants in Iranian university entrance exam for Master’s degree in computer engineering
• Received full scholarship from Shahid Bahonar University of Kerman

Skills

Language:

•   English (Fluent)
•   Persian (Native)

Computer:

• Programming Languages: Python, MATLAB, C++, Lua
• Machine Learnig Framework: TensorFLow, PyTorch
• Applications: Visual Studio, Office suite, SPSS Modeler, LaTeX
• Operating Systems: Windows, Linux, Windows Server
• Network: GNS3, Wireshark
• Simulator: V-REP, VMware

Certifications

CCNP    CCNA   Network+   ICDL