Shengchao Liu | Computer Science | Research Excellence Award

Dr. Shengchao Liu | Computer Science | Research Excellence Award

The Chinese University | Hong Kong

Shengchao Liu is a tenure-track Assistant Professor in the Department of Computer Science and Engineering at The Chinese University of Hong Kong, whose research lies at the intersection of machine learning, geometry, and scientific discovery. His work focuses on developing foundation models and physics-inspired learning frameworks for molecules, proteins, and materials, with the long-term goal of accelerating discovery in chemistry, biology, and materials science. By integrating multi-modal data, symmetry principles, and domain knowledge, his research bridges theoretical advances in AI with real-world experimental impact. A central theme of Dr. Liu’s research is geometric and symmetry-informed representation learning. He has pioneered group-equivariant and manifold-constrained generative models that respect the underlying physical laws of molecular and material systems. His contributions include SE(3)-invariant pretraining methods, group-symmetric stochastic differential equation models, and rigid flow matching techniques, which have significantly improved the fidelity and interpretability of molecular generation and dynamics modeling. These methods form a unifying framework for learning across molecules, proteins, and crystalline materials, as demonstrated in his influential works at ICLR, ICML, NeurIPS, and AISTATS. Dr. Liu’s work is deeply collaborative and interdisciplinary. He has worked closely with leading researchers across academia and industry, including Mila, UC Berkeley, NVIDIA Research, and national laboratories. As a Principal Investigator, he has led NERSC-supported projects on foundation models for material discovery, leveraging large-scale GPU resources to push the frontier of generative AI for science. His research has also contributed widely used open-source resources, including geometric graph learning benchmarks and toolkits adopted by the broader AI-for-science community.

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Featured Publications


Pre-training Molecular Graph Representation with 3D Geometry

– International Conference on Learning Representations , 2021 | Cited by 574


N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules

– Advances in Neural Information Processing Systems, 2019 | Cited by 295


A text-guided protein design framework

– Nature Machine Intelligence, 2025 | Cited by 225

 

Christos Bouras | Computer Science | Research Excellence Award

Prof. Christos Bouras | Computer Science | Research Excellence Award

Prof. Christos Bouras | University of Patras | Greece

Professor Christos Bouras is a distinguished academic leader and renowned computer engineering expert, currently serving as Professor in the Department of Computer Engineering and Informatics and Rector of the University of Patras, Greece. He holds a Diploma and a PhD in Computer Engineering and Informatics from the University of Patras. Over the course of his career, he has made substantial contributions to advanced networking technologies, digital communications, and distributed systems while leading major academic, administrative, and international initiatives. His research expertise spans and Beyond Networks, performance analysis of networking and computer systems, mobile and wireless communications, telematics, QoS and pricing mechanisms, e-learning technologies, and networked virtual environments. As an active member of IEEE and ACM, Professor Bouras has built a global reputation for innovative contributions and collaborative research. He has also held several prestigious roles, including Honorary Professor at the College of Information Engineering, Sichuan Agricultural University, China, and President of the University of Patras Property Utilization & Management Company. His long-standing academic leadership is matched by a major international presence in scholarly events. Professor Bouras has participated extensively in international conference committees for more than three decades, contributing to global research dialogue in computing, networking, and educational technologies. His committee roles span top-tier conferences such as ACM STOC, ICALP, IEEE ICALT, ICL, ICWN, ICOMP, GRID Computing, and numerous specialized workshops across Europe, Asia, and North America. His involvement includes organizing committees, program committees, keynote speaking, and advisory roles in areas such as distributed algorithms, multimedia systems, web-based learning, virtual environments, mobile technologies, simulation and modeling, and entertainment computing. Widely respected for his research excellence, international collaboration, and academic leadership, Professor Bouras continues to advance global innovation in computer networks, digital systems, and technology-enhanced learning.

Profiles: Google Scholar

Featured Publications

Jurgelionis, A., Fechteler, P., Eisert, P., Bellotti, F., David, H., Laulajainen, J. P., Bouras, C., … (2009). Platform for distributed 3D gaming. International Journal of Computer Games Technology, 2009(1), Article 231863.

Bouras, C., Kollia, A., & Papazois, A. (2017). SDN & NFV in 5G: Advancements and challenges. In 2017 20th Conference on Innovations in Clouds, Internet and Networks (ICIN) (pp. xx–xx). IEEE.

Bouras, C., & Tsogkas, V. (2012). A clustering technique for news articles using WordNet. Knowledge-Based Systems, 36, 115–128.

Bouras, C., & Tsiatsos, T. (2006). Educational virtual environments: Design rationale and architecture. Multimedia Tools and Applications, 29(2), 153–173.

Bouras, C., Philopoulos, A., & Tsiatsos, T. (2001). e-Learning through distributed virtual environments. Journal of Network and Computer Applications, 24(3), 175–199.

Bouras, C., Ntarzanos, P., & Papazois, A. (2016). Cost modeling for SDN/NFV based mobile 5G networks. In 2016 8th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT) (pp. xx–xx). IEEE.

Bouras, C., Konidaris, A., & Kostoulas, D. (2004). Predictive prefetching on the web and its potential impact in the wide area. World Wide Web, 7(2), 143–179.

Kangwon Lee | Computer Science | Best Researcher Award

Mrs. Mihaela Corina Radu | Reproductive Health | Excellence in Research 

Carol Davila University of Medicine and Pharmacy Bucharest, Romania.

Radu Mihaela Corina is a Romanian midwifery expert and academic dedicated to improving maternal healthcare. She currently serves as an Associate University Assistant at UMF Carol Davila Bucharest, contributing to both the Department of General and Specific Nursing and the Department of Microbiology, Parasitology, and Virology. With extensive clinical experience, she is also the Head Midwife at Dr. Constantin Andreoiu County Emergency Hospital. Beyond academia, she is actively engaged in European midwifery policy, serving as a member of the Ethics Committee of the European Midwives Association and as a National Expert for Romania in an EU-funded midwifery sectoral project.

Profile

Orcid

🎓 Education

Radu Mihaela Corina has pursued an extensive academic journey in the field of medicine and midwifery. She is currently a PhD candidate in Medicine (2021 – Present) at Carol Davila University of Medicine and Pharmacy, Romania, where she is advancing her expertise in maternal and reproductive healthcare. She holds a Master’s Degree in Medical & Public Health Management (2019 – 2021) from the same institution, graduating with a perfect 10.00 GPA, demonstrating her dedication to academic excellence and healthcare leadership. Her foundational training in midwifery was completed with a Bachelor’s Degree in Midwifery (2014 – 2018) at UMF Carol Davila, Romania, where she distinguished herself as the Class Leader, showcasing her leadership skills and commitment to the profession from the early stages of her career.

💼 Professional Experience

With a strong background in midwifery and maternal healthcare, Radu Mihaela Corina has been actively contributing to both academia and clinical practice. Since 2021, she has been serving as an Associate University Assistant at UMF Carol Davila Bucharest, where she plays a key role in training future midwives and healthcare professionals. In parallel, she holds the position of Head Midwife at Dr. Constantin Andreoiu County Emergency Hospital since 2022, overseeing maternity care and ensuring the highest standards in obstetric practice.

Her passion for maternal education led her to work as a Lecturer in Prenatal Courses at the Rhodos Proviva Family Health Education Center (2020 – 2022), where she provided essential guidance to expectant mothers. Additionally, from 2018 to 2022, she served as the Head Midwife in the Birth Block at Obstetrics and Gynecology Hospital, Ploiesti, where she played a crucial role in labor and delivery management, ensuring safe and effective maternity care. Through these roles, she continues to make a significant impact in both education and clinical midwifery.

🔬 Research Interests

Maternal and Child Health 🏥

Midwifery Education & Practice 👶

Reproductive Health & Ethics 🧬

Medical Policy and Public Health 📊

🏆 Awards & Recognitions

2025: Member of the Ethics Committee, European Midwives Association

2024: National Expert for Romania, EU Project on Midwifery Professional Standards

2022 – Present: AMI Delegate, General Council, International Confederation of Midwives

2020 – Present: Vice President, Association of Independent Midwives, Romania

📚 Selected Publications

(2025) Validation of a Questionnaire Assessing Pregnant Women’s Perspectives on Addressing the Psychological Challenges of ChildbirthNursing Reports, 15(1):8

(2024) Predictors of Pregnant Women's Decision to Opt for Cesarean Section in RomaniaCureus, 16(9)

(2024) Exploring Factors Influencing Pregnant Women’s Perceptions and Attitudes Towards Midwifery Care in Romania – Nursing Reports, 14(3), 1807-1818

(2024) COVID-19 and Flu Vaccination in Romania: Post-Pandemic LessonsPLoS ONE, 19(3)

(2023) Similarities in Midwifery Education, Regulation, and Practice Across EuropeEuropean Journal of Midwifery, 7(Supplement 1)

 

 

 

Dr. James C. L. Chow | Quantum Computing | Best Researcher Award

Dr. James C. L. Chow | Quantum Computing | Best Researcher Award

Princess Margaret Cancer Centre, Canada.

Dr. James Chun Lam Chow, PhD, FCCPM, FInstP, FIET, SMIEEE, PPhys, CPhys, CSci, is a distinguished medical physicist specializing in radiation oncology and artificial intelligence applications in healthcare. He is currently an Associate Professor in Material Science and Engineering at the University of Toronto and a Clinician Investigator at the Princess Margaret Cancer Research Institute. With over two decades of experience in medical physics, his research focuses on AI-driven healthcare solutions, radiation therapy optimization, and Monte Carlo simulations for cancer treatment.

Profile

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Education🎓

Dr. James C. L. Chow earned his PhD in Physics from the University of Hong Kong in 1995 under the supervision of Prof. Peter Fung, following a BSc in Applied Physics (First Class Honours) from City University of Hong Kong in 1992. He was awarded a Croucher Postdoctoral Fellowship at the University of Cambridge (1995-1997), then continued his research as a Postdoctoral Researcher at the University of Toronto (1997-1998) and later as a Postdoctoral Fellow at McMaster University (1998-2000). Transitioning into medical physics, he completed his Medical Physics Residency at the London Regional Cancer Centre (2000-2002), gaining clinical expertise in radiation therapy and medical imaging.

Professional Experience🌟

Dr. James C. L. Chow is an accomplished medical physicist and academic with extensive experience in radiation oncology and materials science. He is currently an Associate Professor in the Department of Materials Science and Engineering at the University of Toronto (2025–Present) and has been an Associate Professor in the Department of Radiation Oncology at the University of Toronto since 2019. In addition to his academic roles, he serves as a Medical Physicist at Princess Margaret Cancer Centre (2005–Present), where he also leads as the Physics On-Call Lead (2010–Present). His research contributions are further reflected in his role as a Clinician Investigator at the Princess Margaret Cancer Research Institute (2023–Present) and his affiliation with the Acceleration Consortium at the University of Toronto (2024–Present).

Previously, Dr. Chow held multiple key positions, including Assistant Professor in Radiation Oncology at the University of Toronto (2006–2019) and Medical Physics Site Lead for Skin Cancer at Princess Margaret Cancer Centre (2010–2015). Before joining Princess Margaret, he worked as a Medical Physicist and Deputy Radiation Safety Officer at Grand River Regional Cancer Centre (2002–2005). He has also contributed to academia as an Adjunct Professor at Ryerson University and the University of Waterloo (2005–2010). His career reflects a deep commitment to advancing medical physics, cancer treatment, and interdisciplinary research in materials science and engineering.

Research Interests📚

Dr. Chow’s research focuses on:

Radiation Oncology & Medical Physics: Treatment optimization using Monte Carlo simulations

Artificial Intelligence in Healthcare: AI-driven diagnostic tools and chatbot applications in oncology

Nanotechnology in Radiation Therapy: Gold nanoparticle-enhanced radiotherapy

Clinical Data Analysis: Predictive modeling for cancer treatment outcomes

Awards & Recognitions🏆

2024 Outstanding Reviewer, Nuclear Engineering and Technology Journal

2024 Most-Viewed Article, JMIR Cancer

2024 Outstanding Author of the Year, AIMS Biophysics Journal

2019 Top Peer Reviewer, Web of Science Group

2012 Outstanding Reviewer, Medical Physics Journal

2010 SciNet Local Resource Allocation Award (1 million supercomputing hours for Monte Carlo simulations)

Selected Publications📖

Gold nanoparticles for drug delivery and cancer therapy
S Siddique, JCL Chow
Applied Sciences 10(11), 3824 (2020) – Cited: 382

Chatbot for health care and oncology applications using artificial intelligence and machine learning: Systematic review
L Xu, L Sanders, K Li, JCL Chow
JMIR Cancer 7(4), e27850 (2021) – Cited: 375

Application of nanomaterials in biomedical imaging and cancer therapy
S Siddique, JCL Chow
Nanomaterials 10(9), 1700 (2020) – Cited: 325

Irradiation of gold nanoparticles by X‐rays: Monte Carlo simulation of dose enhancements and the spatial properties of secondary electron production
MKK Leung, JCL Chow, BD Chithrani, MJG Lee, B Oms, DA Jaffray
Medical Physics 38(2), 624-631 (2011) – Cited: 311

Machine learning in healthcare communication
S Siddique, JCL Chow
Encyclopedia 1(1), 220-239 (2021) – Cited: 142

 

 

Prof. Wen Jiang | Artificial Intelligence | Best Researcher Award

Prof. Wen Jiang | Artificial Intelligence | Best Researcher Award

Northwestern Polytechnical University, China.

Prof. Wen Jiang is a distinguished researcher and academic with a Ph.D. from Northwestern Polytechnical University, Xi’an, China (2009). She currently serves as a professor in the School of Electronics and Information at Northwestern Polytechnical University. Her work focuses on cutting-edge areas like information fusion, artificial intelligence, remote sensing image processing, and intelligent algorithm security, making her a leader in her field.

Profile

Scopus

Orcid

Education 🎓

Prof. Wen Jiang has an impressive academic background in information systems and engineering. She earned her Ph.D. in Information Systems from Northwestern Polytechnical University, Xi’an, China, in 2009, where her research focused on innovative data systems and intelligent technologies. Prior to that, she completed her Master’s degree in Information Engineering at Information Engineering University, Zhengzhou, China, in 1997, gaining in-depth knowledge of advanced engineering concepts. She began her academic journey with a Bachelor’s degree in Information Engineering from the same university in 1994, building a strong foundation for her pioneering contributions to the field.

Experience 🏫

Prof. Wen Jiang is a Professor at the School of Electronics and Information, Northwestern Polytechnical University, where she has made a significant impact in academia. She is highly regarded for mentoring aspiring researchers and leading innovative projects in advanced technologies. Her leadership and expertise have been instrumental in driving forward research in areas like artificial intelligence, information fusion, and algorithm security..

Research Interests 🔍

Information Fusion:
Integrating data from diverse sources to enable smarter and more efficient decision-making processes, crucial for applications in defense, healthcare, and industry.

Artificial Intelligence:
Advancing machine learning and intelligent systems to solve complex problems and enhance automation across various domains.

Remote Sensing Image Processing:
Developing cutting-edge tools for environmental monitoring, urban planning, disaster management, and mapping applications.

Intelligent Algorithm Security:
Ensuring the robustness, reliability, and safety of AI-driven solutions to address vulnerabilities in critical systems.

Publications Top Notes 📚

A New Data Augmentation Method Based on Mixup and Dempster-Shafer Theory IEEE Transactions on Multimedia, 2024
Contributors: Zhuo Zhang, Hongfei Wang, Jie Geng, Xinyang Deng, Wen Jiang. Link

A Novel Air Target Intention Recognition Method Based on Sample Reweighting and Attention-Bi-GRU IEEE Systems Journal, 2024
Contributors: Yu Zhang, Weichen Ma, Fanghui Huang, Xinyang Deng, Wen Jiang. Link

Causal Intervention and Parameter-Free Reasoning for Few-Shot SAR Target Recognition IEEE Transactions on Circuits and Systems for Video Technology, 2024, Contributors: Jie Geng, Weichen Ma, Wen Jiang. Link

CMSE: Cross-Modal Semantic Enhancement Network for Classification of Hyperspectral and LiDAR Data IEEE Transactions on Geoscience and Remote Sensing, 2024, Contributors: Wenqi Han, Wang Miao, Jie Geng, Wen Jiang. Link

Dual-Path Feature Aware Network for Remote Sensing Image Semantic Segmentation IEEE Transactions on Circuits and Systems for Video Technology, 2024, Contributors: Jie Geng, Shuai Song, Wen Jiang. Link