Afrah Shaahid | Computational Systems Medicine | Research Excellence Award

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Ms. Afrah Shaahid | Computational Systems Medicine | Research Excellence Award

KFUPM | Saudi Arabia

Ms. Afrah Shaahid is an emerging AI Developer and researcher with over three years of experience in computer science, specializing in machine learning, deep learning, and computer vision. Currently pursuing a Master’s degree at King Fahd University of Petroleum and Minerals, she has developed advanced AI models including CNNs, GANs, diffusion models, and vision-language systems. Her work spans healthcare, cybersecurity, and image enhancement, with contributions to high-impact research and publications. Afrah has also led workshops, mentored students, and collaborated on multidisciplinary projects. With strong technical expertise and a passion for innovation, she is dedicated to building scalable AI solutions and advancing intelligent systems for real-world applications.

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Featured Publications

Eyachew Misganew Tegaw | AI in Personalized Medicine | Best Researcher Award

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Assist. Prof. Dr. Eyachew Misganew Tegaw | AI in Personalized Medicine | Best Researcher Award

Assistant Professor of Medical Physics at  Debre Tabor University, Ethiopia.

Dr. Eyachew Misganew Tegaw is an Assistant Professor of Medical Physics at Debre Tabor University, Ethiopia. He earned his Ph.D. from Tehran University of Medical Sciences, specializing in intraoperative radiotherapy using nanoparticles for breast cancer treatment. His research spans medical imaging, radiation therapy, nanomedicine, and AI applications in oncology. Dr. Eyachew Misganew Tegaw has published extensively in peer-reviewed journals and actively contributes to scientific advancement through research, mentorship, and international collaboration.

👨‍🎓 Educational Background:

Eyachew Misganew Tegaw holds a Ph.D. in Medical Physics from the Tehran University of Medical Sciences (TUMS), Iran, where he specialized in intraoperative radiotherapy (IORT) using nanoparticles for breast cancer treatment. His academic journey began with a B.Sc. in Applied Physics from the University of Gondar, followed by an M.Sc. in Condensed Matter Physics from Mekelle University. Across these programs, he built a strong foundation in quantum mechanics, computational physics, and radiation therapy physics, gaining multidisciplinary expertise in both theoretical and applied domains.

Profile:

👨‍🏫 Professional Experience:

With over a decade of academic service, Dr. Eyachew Misganew Tegaw currently serves as an Assistant Professor in the Department of Physics at Debre Tabor University, Ethiopia. He previously held the position of Lecturer at the same institution, actively contributing to curriculum development and student mentorship. His leadership experience includes a two-year term as Department Head and three years as Chair of the Ethiopian Space Science Society (Debre Tabor Branch), showcasing his commitment to both academic and community development.

🧪 Research Interests:

Dr. Eyachew Misganew Tegaw is a highly driven researcher with diverse interests spanning medical physics, radiotherapy technologies, medical imaging, radiation dosimetry, nanomedicine, Monte Carlo simulations, and artificial intelligence. His work integrates cutting-edge approaches like deep learning and machine learning with traditional medical physics techniques, aiming to enhance cancer treatment planning and medical imaging. He is especially passionate about nanoparticle-enhanced therapies and computational modeling for improved patient outcomes in oncology.

🔍 Areas for Improvement:

While Dr. Eyachew Misganew Tegaw has made significant strides in academic research, increased visibility through invited talks, expanded international partnerships, and higher engagement in translational clinical projects could further enhance his research impact. Diversifying funding sources and mentoring emerging researchers may also solidify his standing in the global scientific community.

📚 Scientific Contributions

Dr. Eyachew has authored and co-authored numerous peer-reviewed journal articles in high-impact scientific journals. His publications cover a wide range of topics such as Monte Carlo simulations for radiotherapy, nanoparticle-enhanced imaging and treatment, and explainable AI in oncology. Notable among his recent works is a 2025 article in Scientific Reports comparing survival outcomes in breast cancer surgery, and another accepted paper focusing on AI for lung cancer survival prediction. His systematic reviews and meta-analyses have also significantly contributed to evidence-based practice in cancer diagnosis and therapy.

Publications:

  1. Diagnostic performance of mammography and ultrasound in breast cancer: A systematic review and meta-analysis
    Journal of Ultrasound, 2023

  2. Dosimetric characteristics of the INTRABEAM® system with spherical applicators in the presence of air gaps and tissue heterogeneities
    Radiation and Environmental Biophysics, 2020

  3. Techniques for generating attenuation map using cardiac SPECT emission data only: A systematic review
    Annals of Nuclear Medicine, 2019

  4. Molecular imaging approaches in the diagnosis of breast cancer: A systematic review and meta-analysis
    Iranian Journal of Nuclear Medicine, 2020

  5. Comparison of organs at risk doses between deep inspiration breath-hold and free-breathing techniques during radiotherapy of left-sided breast cancer: A meta-analysis
    Polish Journal of Medical Physics and Engineering, 2022

  6. Gold-nanoparticle-enriched breast tissue in breast cancer treatment using the INTRABEAM® system: A Monte Carlo study
    Radiation and Environmental Biophysics, 2022

  7. Dosimetric effect of nanoparticles in the breast cancer treatment using INTRABEAM® system with spherical applicators in the presence of tissue heterogeneities: A Monte Carlo study
    Biomedical Physics & Engineering Express, 2021

  8. A comparison between EGSnrc/Epp and MCNP in simulation of dosimetric parameters for radiotherapy applications
    Journal of Biomedical Physics & Engineering, 2021

  9. Explainable machine learning to compare the overall survival status between patients receiving mastectomy and breast conserving surgeries
    Scientific Reports, 2025

  10. Attenuation correction for dedicated cardiac SPECT imaging without using transmission data
    Molecular Imaging and Radionuclide Therapy, 2023

  11. Comparative study between EPID and CBCT for radiation treatment verifications
    Iranian Journal of Medical Physics, 2018

Nazanin Zounemat-Kermani | Computational Systems Medicine | Best Researcher Award

Published on by Computational Biologists

Dr Nazanin Zounemat-Kermani | Computational Systems Medicine | Best Researcher Award

Dr. Nazanin Zounemat-Kermani is an accomplished biomedical data scientist whose research stands at the forefront of precision medicine, respiratory disease, and artificial intelligence. Currently serving as a Postdoctoral Research Associate at both the National Heart and Lung Institute (NHLI) and the Data Science Institute (DSI) at Imperial College London, she has earned international recognition for her leadership in multi-omics data integration and machine learning applications in health sciences.

Profile:

🎓 Educational Background:

Dr. Kermani’s academic journey reflects a rare interdisciplinary blend of computer science and biomedical research. She holds a PhD in Biomedicine from Imperial College London (2020), following dual master’s degrees in Artificial Intelligence from the University of Amsterdam (2011) and Machine Learning and Robotics from the University of Tehran (2004). Her academic roots trace back to a Bachelor of Engineering in Software Engineering from Ferdowsi University of Mashhad (2002).

💼 Professional Experience:

Since 2020, Dr. Kermani has worked as a Postdoctoral Research Associate at Imperial College London, after several years as a Research Assistant and PhD candidate in Zoltan Takats’ Lab. Her academic trajectory within one of the world’s top institutions reflects both her scientific rigor and leadership capabilities.

🎓🤝 Academic Mentorship:

Dr. Nazanin Zounemat-Kermani is widely respected not only for her scientific contributions but also for her unwavering commitment to mentorship and academic leadership. Throughout her career, she has actively nurtured the growth of early-career scientists, postdoctoral researchers, and graduate students. As a senior member of interdisciplinary consortia such as AI-RESPIRE, PRISM, and U-BIOPRED, she has led cross-functional teams spanning clinical science, data engineering, and machine learning—mentoring junior colleagues in both technical development and scientific publishing. Her leadership style is inclusive and empowering, emphasizing hands-on guidance in areas such as statistical modeling, research communication, and responsible data science.

🏆 Awards and Honors:

Dr. Kermani has received numerous accolades, including the MSACL Young Investigator Award (2016), Scholar Awards from the American Thoracic Society (2022, 2023), and multiple research grants from prestigious bodies such as the UKRI, MRC, and EPSRC. She has also been invited to present her research by eminent scholars at institutions like Oxford University and Amsterdam UMC.

🌍 Global Projects and Leadership

Dr. Kermani has led and contributed to numerous high-impact international projects, including:

  • RASP-UK: She developed a robust data management platform supporting clinical and omics data integration for asthma research.

  • PIONEER: Co-led machine learning initiatives in prostate cancer, resulting in a key senior-author publication.

  • U-BIOPRED: Coordinated Europe’s largest severe asthma cohort study, publishing over 20 peer-reviewed articles and acting as corresponding author on influential multi-omics studies.

  • UK-Korea PRISM: Leads cross-national efforts in asthma pathophysiology using advanced analytics and single-cell data.

  • AI-RESPIRE: Heads AI model development for environmental and physiological time-series data, mentoring early-career researchers.

  • DeVENT and PROmics: Oversees analysis in critical care and deep learning integration in patient-reported outcomes.

📚 Publications:

  1. CC16 Confers Protection Against Influenza A Virus Infection in Human Airway Epithelium
    H. Kimura, N.Z. Kermani, N. Kimura, M.M. Siddiq, D. Francisco, I.M. Adcock, et al.
    American Journal of Respiratory and Critical Care Medicine, Vol. 211 (Abstracts), 2025.

  2. Distinct Single-Cell Transcriptional Profile in CD4⁺ T-Lymphocytes Among Obese Children With Asthma
    V. Tejwani, R. Wang, A. Villabona-Rueda, K. Suresh, T.D. Wu, I.M. Adcock, et al.
    American Journal of Physiology – Lung Cellular and Molecular Physiology, Vol. 328(3), 2025.

  3. Female Sex Hormones and the Oral Contraceptive Pill Modulate Asthma Severity Through GLUT-1
    A.C. Brown, O.R. Carroll, J.R. Mayall, N. Zounemat-Kermani, S.L.E. Vinzenz, et al.
    Mucosal Immunology, 2025.

  4. Neutrophilic Inflammation in Sputum or Blood Does Not Define a Clinically Distinct Asthma Phenotype in ATLANTIS
    P.J.M. Kuks, T.M. Kole, M. Kraft, S. Siddiqui, L.M. Fabbri, K.F. Rabe, A. Papi, et al.
    ERJ Open Research, Vol. 11(1), 2025.

  5. The Role of WNT5a and TGF‐β1 in Airway Remodelling and Severe Asthma
    T. Daud, S. Roberts, N. Zounemat-Kermani, M. Richardson, L.G. Heaney, et al.
    Allergy, 2025.

  6. Clinical Importance of Patient-Reported Outcome Measures in Severe Asthma: Results from U-BIOPRED
    R. Meys, F.M.E. Franssen, A.J. Van ‘t Hul, P.S. Bakke, M. Caruso, B. Dahlén, et al.
    Health and Quality of Life Outcomes, Vol. 22(1), Article 109, 2024.

  7. Radiomultiomics: Quantitative CT Clusters of Severe Asthma Associated With Multiomics
    N.Z. Kermani, K.F. Chung, G. Macis, G. Santini, F.A.A. Clemeno, A. Versi, K. Sun, et al.
    European Respiratory Journal, Vol. 64(5), 2024.

  8. S12 Association Between Disease Duration and FEV1 in Severe Asthma Phenotypes and Endotypes
    F. Yang, N. Zounemat-Kermani, P. Dixey, I.M. Adcock, C.I. Bloom, K.F. Chung
    Thorax, Vol. 79(Suppl 2), A15–A16, 2024.

  9. S120 Post-Hoc Analysis of Transcriptomic and Clinical Predictors of Remission in the ATLANTIS Cohort
    A.A. Kumar, T.M. Kole, M.C. Nawijn, K.F. Rabe, A. Papi, C. Brightling, D. Singh, et al.
    Thorax, Vol. 79(Suppl 2), A83–A84, 2024.

  10. Discovery and Validation of a Volatile Signature of Eosinophilic Airway Inflammation in Asthma
    R. Peltrini, R.L. Cordell, M. Wilde, S. Abuhelal, E. Quek, N. Zounemat-Kermani, et al.
    American Journal of Respiratory and Critical Care Medicine, Vol. 210(9), pp. 1101–1112, 2024.

  11. Cardiovascular Events in CML Patients Treated With Nilotinib: Validation of the HFA-ICOS Baseline Risk Score
    M. Andres, F. Fernando, S. Claudiani, N. Kermani, G. Ceccarelli, J. Apperley, et al.
    European Heart Journal, Vol. 45(Suppl 1), ehae666.3169, 2024.

  12. Scientific Business Abstracts
    F. Cooles, G. Vidal-Pedrola, N. Naamane, A. Pratt, B. Barron-Millar, et al.
    QJM: An International Journal of Medicine, Article hcae157, 2024.

  13. A Severe Asthma Phenotype of Excessive Airway Haemophilus influenzae Relative Abundance Associated With Sputum Neutrophilia
    A. Versi, A. Azim, F.X. Ivan, M.I. Abdel-Aziz, S. Bates, J. Riley, M. Uddin, et al.
    Clinical and Translational Medicine, Vol. 14(9), e70007, 2024.

  14. Host-Microbial Interactions Differ With Age of Asthma Onset
    A. Versi, A. Azim, F.X. Ivan, M.I. Abdel-Aziz, S. Bates, J. Riley, et al.
    European Respiratory Journal, 2024.

  15. Cardiovascular Events in CML Patients Treated With Nilotinib: Validation of the HFA-ICOS Baseline Risk Score
    F. Fernando, M.S. Andres, S. Claudiani, N.Z. Kermani, G. Ceccarelli, A.J. Innes, et al.
    Cardio-Oncology, Vol. 10(1), Article 42, 2024.

  16. Endotypes of Severe Neutrophilic and Eosinophilic Asthma From Multi-Omics Integration of U-BIOPRED Sputum Samples
    N.Z. Kermani, C.X. Li, A. Versi, Y. Badi, K. Sun, M.I. Abdel-Aziz, M. Bonatti, et al.
    Clinical and Translational Medicine, Vol. 14(7), e1771, 2024.

  17. IL-33 Induced Gene Expression in Activated Th2 Effector Cells Is Dependent on IL-1RL1 Haplotype and Asthma Status
    A.K.S. Jayalatha, M.E. Ketelaar, L. Hesse, Y.E. Badi, N. Zounemat-Kermani, et al.
    European Respiratory Journal, Vol. 63(6), 2024.

  18. Comparison of Asthma Phenotypes in Severe Asthma Cohorts (SARP, U-BIOPRED, ProAR and COREA) From Four Continents
    S.Y. Park, S. Fowler, D.E. Shaw, I.M. Adcock, A.R. Sousa, R. Djukanovic, et al.
    Allergy, Asthma & Immunology Research, Vol. 16(4), p. 338, 2024.

  19. Enose-Derived Response Clusters in Severe Asthmatics Treated With Anti-IL5/5R Biologics
    P. Dixey, N. Zounemat-Kermani, K. Raby, P.K. Bhavsar, K.F. Chung
    B16. Novel Insights Into Asthma Pathogenesis, A3013, 2024.

  20. Association of CC16 Expression in the Airways With Signature Expression of Multi-Omics Data
    H. Kimura, N.Z. Kermani, I.M. Adcock, K.F. Chung, M. Kraft
    D91. Bridging the Gap: Translational Studies in ARDS, Pneumonia, and Sepsis, 2024.