People: Collaborators & HQP

An international, human-centered team.

AIRL has established research collaborations with professors from seven countries and engages Highly Qualified Personnel (HQP), including graduate students, Mitacs interns, and undergraduate researchers at Thompson Rivers University.

Research Team

Director & co-investigator network

Led from Kamloops with long-standing research partners across seven countries — joint publications, patents, grants, and student supervision.

Dr. Ghazanfar Latif Founding Director · TRU · Canada

Dr. Ghazanfar Latif

Assistant Professor, Computing Science, Thompson Rivers University. World's Top 2% Scientists (2024, 2025); 14 US patents; IEEE Senior Member; President, AAIFS; Lead, TRU HorAIzon AI for Health & Healing. Full profile →

Check co-authored publications (134) →

Dr. Jaafar Alghazo USA

Dr. Jaafar Alghazo

Associate Professor, Software Engineering & IT Management, University of Minnesota Crookston (formerly Virginia Military Institute; founding Dean, PMU College of Computer Engineering & Science). Ph.D., Southern Illinois University. Machine learning, medical image processing, and assistive technology — co-author on 60+ joint works and co-editor of the ICICET proceedings.

Check co-authored publications (74) →

Dr. Ghassen Ben Brahim Saudi Arabia

Dr. Ghassen Ben Brahim

Dean, College of Computer Engineering & Sciences, Prince Mohammad Bin Fahd University. Ph.D., Western Michigan University; former Systems Analyst at Boeing Integrated Defense Systems and research visitor at the US Naval Research Lab. Machine learning, network security, and QoS routing — co-inventor on multiple AIRL-affiliated patents.

Check co-authored publications (19) →

Prof. Arfan Jaffar Pakistan

Prof. Arfan Jaffar

Professor and Dean, Superior University (Gold Campus), Lahore. Ph.D., FAST-NUCES; former Research Professor at the Gwangju Institute of Science & Technology, Korea. Image processing and computational intelligence; joint PhD supervision on breast-cancer histopathology and federated-learning healthcare research.

Check co-authored publications (9) →

Dr. Nazeeruddin Mohammad Australia

Dr. Nazeeruddin Mohammad

Associate Professor of Computer Science, University of Adelaide (formerly Director, Cybersecurity Center, PMU). Ph.D., University of Ulster; past researcher at Cisco Systems. Cybersecurity, IoT, and network protocols — co-inventor across the nine-patent writer-verification and document-forensics family.

Check co-authored publications (22) →

Prof. Dr. D.N.F. Awang Iskandar Malaysia

Prof. Dr. D.N.F. Awang Iskandar

Professor, Faculty of Computer Science & IT, UNIMAS. Ph.D., RMIT Australia; postdoctoral research at Heriot-Watt (EU CUBIST project) and Jodrell Bank Centre for Astrophysics, Manchester. Spatio-temporal image analysis and semantics in medicine, agriculture and astronomy — PhD supervision partner for AIRL's medical and surveillance AI lines.

Check co-authored publications (17) →

Dr. Saira Bano TRU · Canada

Dr. Saira Bano

Assistant Professor of Political Science, Thompson Rivers University. Co-investigator on the governance of AI-generated disinformation in Canada's defence and security sector, bringing international-security and policy expertise to AIRL's sociotechnical research.

View profile →

Prof. R. Maheswar India

Prof. R. Maheswar

Professor and Associate Director, KPR Institute of Engineering & Technology, Coimbatore. Ph.D. in Wireless Sensor Networks, Anna University. WSNs, queueing theory and performance evaluation — collaborator on IoT, smart-systems, and agricultural-drone research.

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Dr. Abul Bashar Saudi Arabia

Dr. Abul Bashar

Associate Professor, College of Computer Engineering & Sciences, PMU. Ph.D., University of Ulster; Osmania University Engineering Gold Medalist. Machine learning for networks and health — co-author on COVID-19 diagnostics, malicious-PDF detection, and federated-learning IoMT research.

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Dr. Khaled Fawagreh Saudi Arabia

Dr. Khaled Fawagreh

Lecturer in Information Technology, PMU. Ph.D., Robert Gordon University, UK; M.Sc. Dalhousie and B.Sc. York University, Canada. Data mining and machine learning — collaborator on education analytics and AI-text detection.

Check co-authored publications (3) →

Dr. Roxane Elias Mallouhy Saudi Arabia

Dr. Roxane Elias Mallouhy

Assistant Professor of Computer Science, Al Yamamah University, Riyadh. Ph.D. (2023), Université Bourgogne Franche-Comté / FEMTO-ST Institute — Predictive analysis of time series in various application contexts. Telecommunications engineering (Antonine University) and mobile & distributed computing (Université de Franche-Comté). Data mining, machine learning and time-series forecasting — co-author on AIRL’s agriculture-AI research.

Check co-authored publications (1) →

Dr. Mohsin Butt Saudi Arabia

Dr. Mohsin Butt

Program Coordinator, King Fahd University of Petroleum & Minerals. Completed his Ph.D. (2025, UNIMAS) on deep learning for diabetic retinopathy under AIRL-affiliated co-supervision. Image and video processing, compression, and parallel computing — co-author on MEDCnet and multiple medical-imaging works.

Check co-authored publications (13) →

Dr. Sherif E. Abdelhamid USA

Dr. Sherif E. Abdelhamid

Assistant Professor, Computer and Information Sciences, Virginia Military Institute. Ph.D., Virginia Tech; formerly Assistant Professor at AAST (Egypt) and Infrastructure Software Engineer at the Center for Open Science. Services-based high-performance computing, digital educational technologies, and network analysis of complex systems — a frequent co-author on AIRL's medical-imaging and assistive-technology research.

Check co-authored publications (10) →

Dr. Majid Ali Khan Saudi Arabia

Dr. Majid Ali Khan

Associate Professor and Chair of the Computer Science and Software Engineering programs, Prince Mohammad Bin Fahd University. Ph.D., University of Central Florida; former software engineer at Hewlett-Packard and NetSol Technologies. Machine learning and distributed/parallel computing for computer vision — lead co-inventor on the writer-verification patent family.

Check co-authored publications (7) →

Dr. Kevin Bouchard UQAC · Canada

Dr. Kevin Bouchard

Full Professor, Université du Québec à Chicoutimi (UQAC), and researcher at the LIARA ambient-intelligence laboratory; leads the CYNERGIA team, partly funded by Hydro-Québec. Former scientist at the UCLA Center for SMART Health and postdoctoral fellow at Washington State University (CASAS). Ambient intelligence, activity recognition, machine learning, and health technologies — collaborator on the lab's AI-based mineral-recognition research.

Check co-authored publications (2) →

Dr. Runna Alghazo USA

Dr. Runna Alghazo

Assistant Professor, Rehabilitation and Human Services, University of North Dakota. Ph.D. in Rehabilitation Counseling and Administration, Southern Illinois University Carbondale; Certified Rehabilitation Counselor (CRC). Student success in higher education, inclusive teaching grounded in Universal Design, and ethical, inclusive applications of AI in education, disability, and counseling — co-author on AIRL's assistive-technology and learning-analytics studies.

Check co-authored publications (7) →

Highly Qualified Personnel

Current HQP (10)

Graduate and undergraduate researchers currently supervised or co-supervised by the Director, with their research projects and co-authored publications.

Graduate Current HQP (5)

  1. Rifat Saeed — Wildfire & Air Quality Prediction using Quantum-Inspired Machine Learning (Ph.D., UNIMAS, 2026–2029)
  2. Muhammad Zain — Transformer-based Hate-Speech Detection for English & Low-Resource Languages (Ph.D., IPN Mexico, 2025–2028)
  3. Irum Nehvi — Automatic Blood-Cancer Detection from Microscopic Images using Deep Learning (Ph.D., UNIMAS, 2025–2027)
    Co-authored publication (1)
  4. Faizan Ahmad — Cross-Attention CNN & Vision Transformers for Breast Histopathology (Ph.D., Superior University, 2022–2026)
    Co-authored publication (1)
  5. Zafar Kazmi — Advanced Surveillance for Robbery Detection in Smart Cities (Ph.D., UNIMAS, 2024–2027)
    Co-authored publications (5)

Undergraduate Current HQP (5)

  1. Jone Eng Tan — Optimization-Driven Deep Learning for Skin Cancer Detection & Classification (TRU Internal Research Fund, TRU, 2025–2026)
  2. Andrii Klymov — Garbage Classification System using Deep Learning & IoT (UREAP Grant, TRU, 2025–2026)
  3. Gursahib Singh — Local LLM for TRU: Privacy-Preserving Student Support & Mental Health Navigation (RA under Health & Healing Ingenious Project Grant & UREAP Grant, TRU, 2025–2026)
  4. Deeparsh Singh Dang — Comparative Evaluation of Retrieval-Augmented Generation Pipelines across Domains & LLMs; AI-Powered Wildfire Risk, Air Quality & Community Preparedness Platform, Thompson-Okanagan (UREAP Grant & TRU Sustainability Grant, TRU, 2025–2026)
  5. Pooja Verma — AI-Driven Wildfire Management: Post-Fire Reforestation Analysis; Diabetic Retinopathy Detection & Classification from Fundus Images with Optimized Deep Learning (TRU Sustainability Grant & UREAP Grant, TRU, 2025–2026)
    Co-authored publication (1)
Alumni

Past HQP (47)

Former graduate students, undergraduate research teams and Mitacs Globalink interns. Years shown for undergraduate alumni reflect their co-authored publications with the Director.

Graduate Past HQP (6)

  1. Mohsin Butt — Diabetic Retinopathy Detection using Deep Learning (Ph.D., UNIMAS, completed 2025)
    Co-authored publications (13)
  2. Mohammed Danial Shaikh — LLMs and AI in Education (Master in Data Science, TRU, 2026)
  3. Melissa Fraser-Arnott — AI-Supported Misinformation Identification, Library of Canada's Parliament (UFred EMBA-AI, 2025)
  4. Caroline Reid — AI for Change-Management Metrics & KPI Tracking, Service Canada (UFred EMBA-AI, 2025)
  5. Elizabeth Modersohn — AI Risk Management & Governance in Financial Institutions: Assiniboine Credit Union (UFred EMBA-AI, 2025)
  6. Michel Ouellette — Canadian Medical Protective Association AI Needs Assessment (UFred EMBA-AI, 2025)

Undergraduate Past HQP (38)

  1. Ahmed Abul Hasanaath — Deep Learning for Medical Image Diagnosis: Knee Osteoarthritis & Leukemia Detection (2023–2024)
    Co-authored publications (2)
  2. Abdul Sami Mohammed — Deep Learning for Medical Image Diagnosis: Knee Osteoarthritis & Leukemia Detection (2023–2024)
    Co-authored publications (2)
  3. Ghadah Alhabib — AI-Powered Arabic Braille Learning System & Seismic Image Classification (2022–2023)
    Co-authored publications (3)
  4. Khalid Alnujaidi — AI-Powered Arabic Braille Learning System & Date-Fruit Disease Recognition (2022–2023)
    Co-authored publications (3)
  5. Danyah A. Alghmgham — Autonomous Arabic Traffic Sign Detection & Recognition using Deep CNN (2019–2023)
    Co-authored publications (2)
  6. Roaa AlKhalaf — Arabic Sign Language Recognition using Deep CNN (ArASL Dataset) (2019–2020)
    Co-authored publications (2)
  7. Rawan AlKhalaf — Arabic Sign Language Recognition using Deep CNN (ArASL Dataset) (2019–2020)
    Co-authored publications (2)
  8. Emaan Nazeeruddin — Malicious URL Detection & Skin-Lesion Classification using Machine Learning (2024–2025)
    Co-authored publications (2)
  9. Maria Alabdulrahman — Arabic Offensive Text Detection in Social Networks (2024)
    Co-authored publication (1)
  10. Lara Alotaibi — Arabic Offensive Text Detection in Social Networks (2024)
    Co-authored publication (1)
  11. Abeer M. Alenazy — Oil Spill Identification using Deep CNN (2022)
    Co-authored publication (1)
  12. Rafiq Ibrahim Alhaddad — Email Fraud Detection through Text Analysis & Machine Learning (2021)
    Co-authored publication (1)
  13. F. Sahwan — Email Fraud Detection through Text Analysis & Machine Learning (2021)
    Co-authored publication (1)
  14. A. Aboalmakarem — Email Fraud Detection through Text Analysis & Machine Learning (2021)
    Co-authored publication (1)
  15. Batool Alsalem — Automatic Fruit Calorie Estimation using CNN (2020)
    Co-authored publications (2)
  16. Wejdan Mubarky — Automatic Fruit Calorie Estimation using CNN (2020)
    Co-authored publications (2)
  17. Ayyah Abdulhafith Mahmoud — Smart Nursery: Infant Sound Classification (2020)
    Co-authored publication (1)
  18. Intessar Nasser A Alawadh — Smart Nursery: Infant Sound Classification (2020)
    Co-authored publication (1)
  19. Eman Shaikh — Automated Grading of Handwritten Answer Sheets using CNN (2019)
    Co-authored publication (1)
  20. Iman Mohiuddin — Automated Grading of Handwritten Answer Sheets using CNN (2019)
    Co-authored publication (1)
  21. Ayisha Manzoor — Automated Grading of Handwritten Answer Sheets using CNN (2019)
    Co-authored publication (1)
  22. Maitham A Al-Dobais — Physical Layout Analysis of Scanned Arabic Books (2018)
    Co-authored publication (1)
  23. Fahad Abdulrahman G Alrasheed — Physical Layout Analysis of Scanned Arabic Books (2018)
    Co-authored publication (1)
  24. Saleh Al-Faraj — CNN-Based Alphabet Identification & Sorting Robotic Arm (2021)
    Co-authored publication (1)
  25. Mustafa Albahrani — CNN-Based Alphabet Identification & Sorting Robotic Arm (2021)
    Co-authored publication (1)
  26. Saeed A. AlGhamdi — CNN-Based Alphabet Identification & Sorting Robotic Arm (2021)
    Co-authored publication (1)
  27. Marwan Rafie — CNN-Based Alphabet Identification & Sorting Robotic Arm (2021)
    Co-authored publication (1)
  28. Shurouq Alufaisan — Arabic Braille Recognition using Deep Learning (2020–2022)
    Co-authored publications (3)
  29. Wafa Albur — Arabic Braille Recognition using Deep Learning (2020–2022)
    Co-authored publications (3)
  30. Shaikha Alsedrah — Arabic Braille Recognition using Deep Learning (2020–2022)
    Co-authored publications (3)
  31. Mariam Alabkari — Lung Cancer Detection from LDCT Images using Deep CNN (2021)
    Co-authored publication (1)
  32. Fatima Aljishi — Lung Cancer Detection from LDCT Images using Deep CNN (2021)
    Co-authored publication (1)
  33. Shahad Abdullah Alghamdi — Arabic Handwritten Word Recognition & Lung Cancer Detection using Deep CNN (2019–2021)
    Co-authored publications (2)
  34. Lama Adel Boubshait — Arabic Handwritten Word Recognition using Deep CNN (2019)
    Co-authored publication (1)
  35. Reem Ali Alsadiq — Arabic Handwritten Word Recognition using Deep CNN (2019)
    Co-authored publication (1)
  36. Nouf Aljasim — Oil-Pipe Defect Detection using Autonomous Robots & Image Analysis (2019)
    Co-authored publication (1)
  37. Ayat Alali — Oil-Pipe Defect Detection using Autonomous Robots & Image Analysis (2019)
    Co-authored publication (1)
  38. Zahra Alhamad — Oil-Pipe Defect Detection using Autonomous Robots & Image Analysis (2019)
    Co-authored publication (1)

Mitacs Globalink Research Internship (GRI) HQP (3)

  1. Hania Rasheed — Privacy-Preserving LLMs for Personalized Academic Assistance (Mitacs GRI, 2026)
  2. Mubasher Ahmed — AI-Enabled Braille Learning for the Visually Impaired (Mitacs GRI, 2026)
  3. Hasaan Hamid — Vision & AI Memory-Recall Assistant for Dementia Patients (Mitacs GRI, 2026)
Community of examiners

External PhD examinations (2026)

The Director served as external examiner for five doctoral dissertations spanning Alzheimer's ensemble classification, IoT-edge healthcare monitoring, NDN caching, big-data energy management for smart cities, and privacy in cyber-physical systems.

  1. PhD thesis examiner — “Multi-modal Deep CNN-based Ensemble Classification of Alzheimer's Disease”Ms. Samina Akram · University of Central Punjab, Pakistan (2026)
  2. PhD thesis examiner — “IoT and Edge Computing-Based Healthcare Monitoring Systems Using Machine Learning”Mr. Muhammad Izhar · Superior University, Pakistan (2026)
  3. PhD thesis examiner — “Cache Management Strategy to Enhance the Performance of NDN based IoT Environment”Ms. Qaizar Javed · Superior University, Pakistan (2026)
  4. PhD thesis examiner — “Big Data Analytics Enabled Energy Management Systems for Smart Cities”Mr. Nasir Nauman · Superior University, Pakistan (2026)
  5. PhD thesis examiner — “Privacy Protection in Cyber Physical Systems at Upstream Nodes”Mr. Muhammad Ejazulghaffar · Superior University, Pakistan (2026)

Want to join our research lab?

We always welcome leading researchers from around the world to collaborate on research grants and build strong research networks.

We also recruit undergraduate and graduate students, research assistants, and Mitacs interns every year.

See opportunities