Dr. Furqan Khan received his B.S. in Electrical Engineering from COMSATS University of Technology, Pakistan in 2009, M.S. in Computer Science and Engineering from Ajou University, South Korea in 2012 and Ph.D. (Communication Networks) from University of Queensland, Australia in 2020. His academic career include teaching as a Lecturer and Postgraduate tutor at Lahore Leads University, Pakistan and University of Queensland, Australia, respectively. He also has extensive industrial experience working in different notable R&D organizations and research institutions namely Data61/CSIRO and Insitec. His areas of expertise comprise 4G/5G communications networks, Internet-of-Things, and sensor networks, particularly, network control, resource management, and security.
Assistant Professor, Department of Computer Engineering, National University of Technology (NUTECH) (2025–Present)
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- Teach undergraduate and graduate courses in Computer Communication and Networking.
- Advise graduate students on research projects related to communication and networking.
Research Engineer, Insitec Pty. Ltd. (2021–2024)
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- Networked software design, development, and testing.
- Address multiple challenges such as scalability, security, etc.
- Collaborated with other teams for system integration.
- Established production-ready software version via CI/CD.
Internship - IoT Project, Siemens Australia (2017–2019)
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- Worked on investigating the ANT/ANT+/BLE system performance and devising new mechanisms for its enhancement to improve the operational capability of the Siemens Fuse-saver product.
Postgraduate Course Tutor, University of Queensland (2017–2019)
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- Undertook tutor training program and was involved in lecturing, tutoring, curriculum development, and assessment of two large units related to networking.
Lecturer, Department of Computer Science, Lahore Leads University (2015)
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- Developed new course materials and taught Digital Logic Design and Artificial Intelligence courses to undergraduate students.
- Taught data structures and computer programming courses, including C/C++ and Python.
Academia:
- Ph.D. in Computer Engineering, University of Queensland (2020)
- M.Sc. in Computer Science and Engineering, Ajou University (2012)
- B.Sc. in Electrical Engineering, COMSATS University (2009)
I have published over 15 peer-reviewed papers in top-tier journals and conferences, such as Elsevier Computer Networks, Springer WINET, IET Communications, IEEE SECON, IEEE DCoSS, etc. I also serve as a reviewer for prominent academic journals in the field of Wireless Communication, Networking, and Machine Learning.
Trainings
- AI and Deep Learning Training, Coursera (2019)
- Advanced Machine Learning with TensorFlow, Udacity (2020)
- Data Science for Healthcare, Harvard Online (2021)
My research focuses on the intersection of machine learning, natural language processing, and computer vision. I am currently working on several projects that apply AI techniques to healthcare, such as developing algorithms for automated diagnosis and personalized treatment recommendations. I have received research funding from both the National Science Foundation (NSF) and private tech companies for my work on deep learning models for medical imaging.
Ongoing Research Projects:
- AI for early-stage cancer detection using computer vision
- Predictive analytics for mental health disorders using machine learning
Publications:
- Doe, J., et al. (2023). "Deep Learning for Medical Image Classification: A Case Study." Journal of Machine Learning Research.
- Doe, J., et al. (2022). "Natural Language Processing in Healthcare: Current Applications and Future Directions." International Conference on AI.
AI-Powered Diagnostic Tool (2020–Present): Led the development of an AI tool that assists doctors in diagnosing rare diseases using medical images. The tool is currently in clinical trials with promising results.
Predictive Analytics for Patient Readmission (2019): Developed a machine learning model to predict patient readmission risks based on electronic health records. This project helped reduce readmissions by 10% in a pilot hospital.
Smart Campus System (2018): Collaborated with a team to develop a smart campus system that uses AI to optimize resource allocation and improve campus security. The project was deployed across XYZ University's main campus.
