• Machine Learning: Multi-View Learning; Representation Learning; Big Data; Deep Learning; Probabilistic, Bayesian, and Causal Models; Energy-based Approaches.
• Medical Application: Neuroimage and Health Records Analysis; Disease diagnosis based on text, audio, and wearable device data.

• Jan/2023 – Present, Machine Learning Scientist, FutureCite, Based on my UofA Postdoctoral Fellow position, Under R. Greiner MITACS Grant for ML DevOps and data analysis.
• Apr/2019 – Present, Postdoc fellow under the supervision of Prof. Andrew Greenshaw and Prof. Russell Greiner at University of Alberta, Canada (full-time job).
• Jul/2018 – Mar/2019, Postdoc fellow under the supervision of Prof. Daoqiang Zhang at Nanjing University of Aeronautics and Astronautics, China (full-time job).
• Sep/2014 – Jun/2018, A Research Assistant under the supervision of Prof. Daoqiang Zhang at Nanjing University of Aeronautics and Astronautics (part of my Ph.D. degree).
• Aug/2013 – Aug/2014, Computer engineer at Rasa Ertebatat Soffe Co. (full-time job)
• Feb/2009 – Jul/2013, Computer engineer at Rasa Ertebatat Soffe Co. (part-time job)
• Nov/2006 – Aug/2008, Computer engineer at Reza Noor Ltd. (full-time job)

• Sep/2021 - Apr/2022, Lecturer (in cooperation with Prof. Andrew Greenshaw), University of Alberta, Research Project in Neuroscience, NEURO 498/499: Machine Learning Applications for Functional Neuroimage Analyze, Student: Bryan Holl (undergrade student).
• Sep/2021 - Dec/2021, Lecturer (in cooperation with Prof. Russ Greiner), University of Alberta, Individual Study, CMPUT 605: Using Machine Learning to Analyze fMRI data, Student: Mohsen Soltanpour (Ph.D. student).
• Feb/2021 - Aug/2021, Lecturer (in cooperation with Prof. Russ Greiner), University of Alberta, Individual Study, CMPUT 605: Using Machine Learning to Analyze fMRI data, Student: Bahareh Behroozi Asl (M.Sc. student).
• Sep/2020 - Dec/2020, Lecturer (in cooperation with Prof. Russ Greiner), University of Alberta, Individual Study, CMPUT 605: Using Machine Learning to Analyze fMRI data, Student: Jeff Sawalha (Ph.D. student).
• Feb/2015 - Sep/2015, Teacher Assistant, Nanjing University of Aeronautics and Astronautics, Data Mining under the supervision of Prof. Daoqiang Zhang.
• Feb/2010 – Jul/2014, Lecturer (part-time job), Mazandaran University of Science and Technology, Courses: Data Mining, Expert System, Machine Learning, Computer Networks & Lab., Network Operating System & Lab., Microprocessor & Lab., FPGA & Lab., VHDL & Verilog.
• Feb/2009 – Jul/2011, Teacher Assistant, Mazandaran University of Science and Technology, Assembly programming under the supervision of Dr. Saber Nourian.
• Sep/2005 – Jul/2006, Teacher Assistant, Islamic Azad University Eghlid branch, Microprocessor, FPGA, VHDL, and Verilog. under the supervision of Dr. Ali Bohlooli.
• Sep/2004 – Jul/2005, Teacher Assistant, Islamic Azad University Eghlid branch, Digital Electronic and Computer Architecture under the supervision of Dr. Nader Karimi.

• 2022, Second best poster award at Amii TechAid [Poster].
• 2018, Best Ph.D. thesis award at Nanjing University of Aeronautics and Astronautics.
• 2016, The best student paper award in the BICS 2016 for our paper entitled "Decoding visual stimuli in human brain by using Anatomical Pattern Analysis on fMRI images".
• 2015, Outstanding paper award 2015 in the International Academic Conference for Graduates, Nanjing University of Aeronautics and Astronautics, for our paper entitled "Adaptive Weighted Spectral Clustering." [snapshot]
• 2014, Outstanding paper award 2014 in the International Academic Conference for Graduates, Nanjing University of Aeronautics and Astronautics, for our paper entitled "Wisdom of crowd Cluster Ensemble."[snapshot]
• 2014, Invited to Ph.D. course as a Brilliant Student with full scholarship of China Scholarship Council (CSC) in the "Nanjing University of Aeronautics and Astronautics", China.
• 2013, Graduated as the top student over 25 peers in the course (M.Sc.), "Mazandaran University of Science and Technology", Iran.
• 2010, Invited to M.Sc. interview as a Brilliant Student without the entrance exam in "Mazandaran University of Science and Technology", Iran.
• 2010, Graduated as the top student over 30 peers in the course (B.Sc.), "Mazandaran University of Science and Technology", Iran.
• 2006, Invited to B.Sc. interview as a Brilliant Student without the entrance exam in "Islamic Azad University".
• 2006, Graduated as the top student over 40 peers in the course (Associate), "Islamic Azad University Eghlid branch", Iran.
• 2001, 3rd in Mazandaran Kharazmi Festival for designing a computer software in order to manage and control the cost and time in the Industrial Projects.
• 1999, 2nd programmer in Computer Programming Competition, Mazandaran, Iran.

• Mar/2022, Reading Minds: A Neuroscience Application of Machine Learning, Keynote, NatChat, University of Alberta [Video].
• Jan/2022, Machine Learning Applications in NeuroInformatics, Keynote (in cooperation with Prof. Russ Greiner), Neuroscience and Mental Health Institute (NMHI), University of Alberta.
• Aug/2021, Shared Space Transfer Learning for analyzing multi-site fMRI data, AI Seminar, University of Alberta [Video].
• May/2019, Human Brain Mapping and Decoding, AI Seminar, University of Alberta [Info].
• Jul/2018, Analyzing Human Brain Patterns by using deep approaches, Keynote, 1st Machine Learning, Optimization and Control (MLOC'18), Shenzhen, China. [Slides]
• Nov/2017, Deep Hyperalignment, Spotlight, 15th Workshop in Machine Learning and Application (MLA'17), Beijing Jiaotong University, China. [Slides] [Poster]
• Nov/2015, Adaptive Weighted Spectral Clustering, Keynote, 3rd International Conference of Postgraduates, Nanjing University of Aeronautics and Astronautics, China. [Slides]
• Dec/2014, Wisdom of Crowds Cluster Ensemble Selection, Keynote, 2nd International Conference of Postgraduates, Nanjing University of Aeronautics and Astronautics, China. [Slides]
• Jun/2011, Network Security, Keynote, 1st Annual Conference, Mazandaran University of Science and Technology, Iran.

• Machine Learning Related Projects
  • Founder of MedAI

  This is an under developing web and mobile applications as a distributed machine learning solution for medical application. It can process text, audio, wearable, anatomical and functional images - e.g., CT, MRI, fMRI, etc. MedAI employs NodeJS, FastAPI, Rust (Actix), Docker, Kubernetes to provide backend services. The distributed machine learning engine is developed using Python, Tensorflow, Rust, and bash script.

  • Founder of Easy fMRI (a toolbox for human brain mapping and decoding)
  • Founder of Easy Data (a repository for sharing preprocessed task-based fMRI datasets)
  • Founder of easyX (a python library for storing big, complex data structures)
  • Suicide prediction based on Chongqing, China dataset: A health record project
  • Diagnosing of the stork in mouse brains based on Calcium images
  • Predicting cognitive tasks in mouse brains by using EEG
  • Designing Expert System for forecasting production rate in Reza Noor Ltd.
  • Designing cheat detection for finance system in Reza Noor Ltd.
  • Designing and implementing Smart Identifier (a general smart key with multiple applications).
• Computing Engineering Related Projects
  • Designing and implementing Data Center for Sari municipality (Rasa Ertebatat Soffe Co.)
  • Designing and implementing network in Reza Noor Ltd.
  • Designing FPGA, USB and PCI learning kit (for MUST University).
  • Designing Emergency lights, LED halogen lights, fluorescent blast for Reza Noor Ltd.
  • Designing ICT-Master plan for Mazandaran University of Science & Technology
  • Analysis and implementation of software for network management at Reza Noor Ltd.

Neuroscience: AFNI, FSL, SPM, FreeSurfer, Group ICA, NIfTI.

Machine Learning Library: Scikit-learn, Tensorflow (+Probability, GPflux), JAX, PyTorch, PyWhy, Z3 API, Stable-Baselines3.

Programming Languages: Python, Javascript, SwiftUI, Rust, Bash, MatLab, C, C++.

Database: PostgreSQL, MongoDB, Redis, MySQL, Microsoft SQL, Oracle Database.

OS: Linux (Arch, Fedora, and Debian), OSX, Windows, Solaris, Cisco IOS.

DevOps: Docker, Kubernetes, CI/CD (GitLab and GitHub), JWT.

Cloud Platform: Amazon AWS, Google Cloud, Microsoft Azure.

Hardware: Cisco routers and switches, Siemens IP-PBX, Avaya IP-PBX, Mikrotik routers and switches, Asus and HP servers and networks.