CV

Below are some highlights from my CV.

For more information, please see the PDF of my Full CV.

Education

• Bachelor of Science (B.Sc.) in Biomedical Engineering, September 2007.
  • Sahand University of Technology, Tabriz, Iran.
  • Thesis Title: “Adaptive Control Using NARMA-L2 Model for Nonlinear Systems,” Score: 19/20 PDF.
• Master of Science (M.Sc.) in Electrical Engineering, January 2010
  • Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran. Total GPA: 3.34/4.
  • Thesis Title: “Image Fusion in the Multi-Scale Transforms Domain Using Fuzzy Logic and Particle Swarm Optimization,” Score: 20/20 PDF.
• Doctor of Philosophy (Ph.D.) in Electrical Engineering, September 2015
  • Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran. Total GPA: 3.67/4.
  • Thesis Title: “Synthetic Aperture Radar Signal Processing Using Nonlinear Frequency Modulation and Phase Error Compensation,” Score: 19.50/20 PDF.

Experiences

Work

• Jan 2019 – Present: Postdoctoral researcher at Swiss AI Lab IDSIA (Istituto Dalle Molle di Studi sull’Intelligenza Artificiale), Lugano, Switzerland.
  • Participated in the design and implementation of multiple automated visual inspection and quality control projects for steel, electromechanical, and textile products through the development and application of cutting-edge deep learning, signal processing, and computer vision techniques.
  • Contributed to various projects involving object detection and tracking, 3D surface matching, microwave image reconstruction, and time series forecasting for financial assets.
• June 2016 – November 2018: Signal and image processing engineer at Towzin Electric Company (TEC), Tehran, Iran.
  • Contributed to the design and construction of the first Iranian High-Speed Weigh in Motion system at Towzin Electric Company (TEC), Tehran, Iran, (September 2016).
  • Involved in the design and implementation of real-time license plate recognition software, (March 2017).
• March 2016 – June 2016: Research associate at Information and Communication Technology Research Center (ICTRC), Tehran, Iran.
• September 2011 – January 2015: Signal processing engineer at Pardis Electronic Development Co., Tehran, Iran.
  • Played a role in the design and construction of the first Iranian Synthetic Aperture Radar (IRSAR/N-1) at Pardis Electronic Development Co., Tehran, Iran, (July 2013).
  • Contributed to technology transfer for a pulsed mode SAR system manufactured by Russia, at Pardis Electronic Development Co., Tehran, Iran, (2012-2013).
• September 2007 – September 2015: Research assistant at Machine Vision Research Lab. (MVRL) under the supervision of Prof. Karim Faez, Electrical Engineering Department. Amirkabir University of Technology.
  • Obtained M.Sc. and Ph.D. degrees in electrical engineering in 2010 and 2015, respectively.
  • Published 10 ISI journal papers and 7 conference papers in various research areas.

Volunteering

• 2012 – Present: Reviewer for IEEE, Elsevier, Springer, IET, Taylor & Francis, and World Scientific journals on signal and image processing, computer vision, and remote sensing.
• February 2017 – December 2019: Evaluator of knowledge-based companies at Presidential Deputy for Science and Technology, Tehran, Iran.

Skills

• Programming Languages:
  • Python (proficient), C/C++ (intermediate), MATLAB (proficient).
• Development Environments (IDEs/Editors):
  • Experienced with Visual Studio Code, PyCharm, Jupyter Notebook, Qt, Visual Studio, Eclipse, MATLAB/Simulink, and Maple.
• Machine Learning and Deep Learning:
  • Excellent knowledge of Supervised methods (Classification, Regression), Unsupervised methods (Clustering, Feature Selection, Dimensionality Reduction) and Self-supervised learning.
  • Experienced in designing and implementing CNNs for image and video analysis, including classification, object detection, and semantic segmentation. Skilled in Autoencoder development for anomaly detection, image denoising, and feature learning. Expertise in deep learning model architecture, hyperparameter tuning, image augmentation, and transfer learning. Familiar with time-series forecasting using deep learning and machine learning techniques. Proficient in data cleaning, imputation, feature engineering, and machine learning models for data science projects.
  • Skilled in using Scikit-learn, Pyod, SciPy, TensorFlow, Keras, TensorBoard, PyTorch, PyTorch Lightning, Albumentations, Imgaug, Comet, MLflow, Pandas and LightGBM for building and deploying machine learning and deep learning models.
• Computer Vision and Image Processing:
  • Expertise in various computer vision tasks, including Image reconstruction, 3D surface matching, depth estimation, SLAM, multi-sensor image fusion, object detection (instance segmentation) and tracking, semantic segmentation, visual inspection, image registration, template matching, and image enhancement.
  • Proficient in utilizing OpenCV, Scikit-image, and Kornia for image and video analysis.
  • Competent in using Open3D and Point Cloud Library (PCL) for point cloud data processing.
• Signal Processing:
  • Proficient in Synthetic Aperture Radar (SAR) signal processing, biomedical signal analysis (ECG, EEG), speech signal processing, and dynamic load-cell signal processing for vehicle weight estimation.
  • Skilled in using a comprehensive set of signal processing libraries, including NumPy, SciPy, Matplotlib, Scikit-signal, PyWavelets, FilterPy, and Wavelets, covering a wide range of signal processing tasks.
• Optimization Algorithms:
  • Proficient in particle swarm optimization (PSO) and Genetic algorithms for solving complex optimization problems.
  • Experienced in utilizing Python libraries such as DEAP, PySwarm, and PyGMO for implementing and solving optimization tasks.
• Technologies and Frameworks:
  • Infrastructure: Proficient in Linux, Microsoft Windows (WSL2), and Docker for containerized microservices.
  • Version Control: Experienced in collaborative coding using GitHub and GitLab.
  • Web Development: Proficient in Flask and FastAPI for building APIs and ZeroMQ for efficient messaging.
  • Data Analysis: Skilled in data manipulation and analysis using Pandas, Seaborn and Numpy.
  • Parallel Programming: Proficient in multithreading and multiprocessing for optimizing program performance.
  • GPU Computing: Experience with CUDA Processing for parallel computing on GPUs.
• Other relevant skills: Problem-solving, teamwork, communication.

Language

• Persian (native)
• English (full professional proficiency)
  • TOEFL iBT: total 100 (Reading 23/30, Listening 29/30, Speaking 24/30, Writing 24/30)
• Italian (B1)

Honors and Awards

• Member at Iran’s National Elites Foundation (BMN), (April 2016 – Present).
• Scholarships for PhD and Master Educations, granted for top students in entrance exam, granter: Iranian government, (Sep 2010 and Sep 2007).