Mehnaz Tabassum | Computer Science and Artificial Intelligence | Women Researcher Award

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Dr. Mehnaz Tabassum | Computer Science and Artificial Intelligence | Women Researcher Award

University of Sydney | Australia

Dr. Mehnaz Tabassum is an accomplished researcher in Computational Neurosurgery and Health Innovation, with core expertise in medical image analysis, artificial intelligence, and brain tumor diagnostics. Her research integrates deep learning, radiomics, and neuroimaging to enhance the precision of tumor segmentation, classification, and recurrence prediction in neuro-oncology. Her scholarly contributions include 14 Scopus-indexed publications, with a total of 87 citations and an h-index of 4 (Scopus metrics). She has published in prestigious journals such as Cancers, European Radiology, and Neuro-Oncology Advances, and has presented her findings at leading international conferences including IEEE EMBC and IEEE ISBI. Dr. Mehnaz Tabassum’s recent research explores cross-modality medical image synthesis, MRI-to-PET generation using diffusion and GAN-based models, and meta transfer learning for brain tumor segmentation. Her innovative work advances computational solutions for precision medicine and AI-assisted neuroimaging. She has received multiple distinctions, including the Pro-Vice Chancellor’s Research Excellence Scholarship and the Henry Sutton Postgraduate Research Scholarship, alongside a Best Paper Award for excellence in scientific contribution. Her interdisciplinary research continues to impact the fields of AI-driven diagnostics, eye-tracking in medical imaging, and computational modeling for neurosurgical innovation, reflecting her commitment to advancing data-driven healthcare and translational neuroscience.

Profiles: Scopus | Google Scholar | ORCID | ResearchGate | Staff Page

Featured Publications

  • Tabassum, M., Suman, A. A., Suero Molina, E., Pan, E., Di Ieva, A., & Liu, S. (2023). Radiomics and machine learning in brain tumors and their habitat: A systematic review. Cancers, 15(8), Article 2034. https://doi.org/10.3390/cancers15082034

  • Ghose, P., Alavi, M., Tabassum, M., Ashraf Uddin, M., Biswas, M., Mahbub, K., … & Hassan, M. (2022). Detecting COVID-19 infection status from chest X-ray and CT scan via single transfer learning-driven approach. Frontiers in Genetics, 13, 980338. https://doi.org/10.3389/fgene.2022.980338

  • Moradizeyveh, S., Tabassum, M., Liu, S., Newport, R. A., Beheshti, A., & Di Ieva, A. (2024). When eye-tracking meets machine learning: A systematic review on applications in medical image analysis. arXiv preprint arXiv:2403.07834. https://arxiv.org/abs/2403.07834

  • Tabassum, M., Suman, A. A., Russo, C., Di Ieva, A., & Liu, S. (2023). A deep learning framework for skull stripping in brain MRI. Neurocomputing (Under review).

  • Afrin, F., Al-Amin, M., & Tabassum, M. (2015). Comparative performance of using PCA with K-means and fuzzy C means clustering for customer segmentation. International Journal of Scientific and Technology Research, 4(8), 70–74.

Wenbo Shen | Computer Science and Artificial Intelligence | Best Researcher Award

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Assoc. Prof. Dr. Wenbo Shen | Computer Science and Artificial Intelligence | Best Researcher Award

Zhejiang University | China

Dr. Wenbo Shen is a tenured Associate Professor at the College of Computer Science and Technology, Zhejiang University. He is a highly regarded researcher in computer software and system protection, with expertise in program analysis, operating system security, and energy-efficient system defense. With a career spanning academia and industry, Dr. Shen has established himself as an innovative scholar whose work has advanced the field of computer security on a global scale.

Professional Profile

Scopus

Google Scholar

ORCID

Education

Dr. Wenbo Shen earned his Ph.D. in Computer Science from North Carolina State University, where his dissertation focused on wireless security and physical layer signal design under the supervision of distinguished professors. Prior to this, he obtained his Bachelor of Science degree in Software Engineering from the Harbin Institute of Technology, graduating in the top tier of his class. This solid academic foundation has shaped his excellence in research and teaching.

Experience

Dr. Wenbo Shen’s professional journey reflects a balance of academic leadership and industrial innovation. He began his career as a Senior Research Scientist at Samsung Research America, where he contributed to advanced security solutions for operating systems. He later joined Zhejiang University, first as an Assistant Professor and then progressing to a tenured Associate Professor. His teaching and supervision experience has nurtured the next generation of scholars, while his leadership in funded research projects has strengthened collaborations between academia and industry.

Research Interest

Dr. Wenbo Shen’s research focuses on protecting computer software and systems through advanced program analysis techniques. His contributions span detecting software bugs in major operating systems such as Linux, FreeBSD, and Fuchsia, while also developing lightweight protection mechanisms for mobile systems, containerized environments, and edge computing. He is particularly known for creating resource- and energy-friendly defense strategies, bridging theoretical innovation with practical application in real-world computing systems.

Awards

Dr. Wenbo Shen has been recognized with multiple Distinguished Paper Awards from top international security conferences, including the European Symposium on Research in Computer Security, the Annual Computer Security Applications Conference, ACM Asia Conference on Computer and Communications Security, and the Network and Distributed System Security Symposium. These honors highlight the significance and impact of his research contributions in advancing secure computing.

Publication

Dr. Wenbo Shen has contributed extensively to high-impact journals and conferences in computer security, with his works widely cited by international researchers.

  • Title: Hypervision across worlds: Real-time kernel protection from the arm trustzone secure world
    Published on: 2014
    Citation: 400

  • Title: SKEE: A lightweight Secure Kernel-level Execution Environment for ARM
    Published on: 2016
    Citation: 126

  • Title: Ally friendly jamming: How to jam your enemy and maintain your own wireless connectivity at the same time
    Published on: 2013
    Citation: 101

  • Title: {PeX}: A permission check analysis framework for linux kernel
    Published on: 2019
    Citation: 98

  • Title: Is link signature dependable for wireless security?
    Published on: 2013
    Citation: 75

  • Title: Ptrix: Efficient hardware-assisted fuzzing for cots binary
    Published on: 2019
    Citation: 68

  • Title: NORAX: Enabling execute-only memory for COTS binaries on AArch64
    Published on: 2017
    Citation: 65

Conclusion

Dr. Wenbo Shen’s career reflects excellence in scholarship, innovation in security research, and dedication to advancing computer system protection. His pioneering contributions in operating system defense, his recognition through prestigious international awards, and his consistent high-impact publications make him a deserving nominee for the Best Researcher Award. His work continues to influence the field globally, shaping both academic research and practical applications in secure computing.