Shengchao Liu | Computer Science | Research Excellence Award

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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

 

Kun He | Computer Science | Research Excellence Award

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Assoc Prof Dr. Kun He | Computer Science | Research Excellence Award 

Renmin University | China

Dr. Kun He is an accomplished computer scientist and currently serves as an Associate Professor at Renmin University of China (since January 2023). His academic journey reflects a strong foundation in theoretical computer science, backed by extensive research experience across leading Chinese institutions. Before joining Renmin University, he worked at the Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS), first as an Assistant Researcher (2021–2022) and later as an Associate Researcher (2022). He also completed a postdoctoral fellowship at Shenzhen University between 2019 and 2021. Dr. He earned his Ph.D. in Computer Science from ICT, CAS in 2019 under the supervision of Prof. Xiaoming Sun. He also holds a Master’s degree from ICT, CAS and a Bachelor of Engineering in Computer Science from Wuhan University. His research centers on the theory of computing, with particular emphasis on probabilistic methods, sampling algorithms, quantum computing, combinatorial structures, and theoretical machine learning. His work has significantly advanced algorithmic techniques related to the Lovász Local Lemma (LLL), Holant problems, and random constraint satisfaction. Over the years, Dr. He has received numerous prestigious awards recognizing the impact and quality of his research. These include the New Hundred Stars of ICT (2021), the Outstanding Doctoral Dissertation Award of the China Computer Federation (2020), the Special Award for the President of CAS (2019), and the National Scholarship of China (2018). These honors highlight his early and sustained contributions to theoretical computer science. Dr. He has published extensively in top-tier venues such as SODA, STOC, FOCS, ITCS, and Random Structures & Algorithms. His notable works include breakthroughs on the Moser–Tardos algorithm, deterministic counting versions of the Lovász Local Lemma, sampling solutions to random CNF formulas, and quantum extensions of classical combinatorial frameworks. Several of his papers have been widely cited and recognized, including a top-downloaded publication in Random Structures & Algorithms (2020). Recently, his research continues to push theoretical boundaries, with upcoming papers on the phase transition of the Sinkhorn–Knopp algorithm and efficient approximation schemes for Holant problems. Dr. He also actively works on emerging topics involving perfect sampling and permutation constraints within the Lopsided LLL regime, with multiple manuscripts currently under submission. With strong expertise, a prolific publication record, and multiple high-impact contributions, Dr. Kun He stands as a leading figure in modern theoretical computer science.

Profiles: Scopus | Google Scholar

Featured Publications

He, K., Li, L., Liu, X., Wang, Y., & Xia, M. (2025). Variable version Lovász Local Lemma: A tale of two boundaries. Information and Computation, 105386.

He, K. (2025). Phase transition of the Sinkhorn-Knopp algorithm. arXiv preprint arXiv:2507.09711.

He, K., Li, Z., Qiu, G., & Zhang, C. (2025). FPTAS for Holant problems with log-concave signatures. In Proceedings of the 2025 Annual ACM–SIAM Symposium on Discrete Algorithms (SODA).

He, K., Qiu, G., & Sun, X. (2024). Sampling permutations satisfying constraints within the lopsided local lemma regime. arXiv preprint arXiv:2411.02750.

He, K., Qiu, G., & Sun, X. (2024). Sampling permutations satisfying constraints within and beyond the local lemma regime. arXiv e-prints, arXiv:2411.02750.

He, K., Li, Q., & Sun, X. (2023). Moser-Tardos algorithm: Beyond Shearer’s bound. In Proceedings of the 2023 Annual ACM–SIAM Symposium on Discrete Algorithms (SODA).

He, K., Wang, C., & Yin, Y. (2023). Deterministic counting Lovász Local Lemma beyond linear programming. In Proceedings of the 2023 Annual ACM–SIAM Symposium on Discrete Algorithms (SODA).

He, K., Wu, K., & Yang, K. (2023). Improved bounds for sampling solutions of random CNF formulas. In Proceedings of the 2023 Annual ACM–SIAM Symposium on Discrete Algorithms (SODA).

He, K., Wang, C., & Yin, Y. (2022). Sampling Lovász Local Lemma for general constraint satisfaction solutions in near-linear time. In 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS).

Hussein Alabdally | Computer Science | Best Researcher Award

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Mr. Hussein Alabdally | Computer Science | Best Researcher Award

Mr. Hussein Alabdally | University of Southern Queensland | Australia

Mr. Hussein Alabdally is a talented computer scientist, software engineer, and telecommunications specialist with diverse professional expertise spanning Australia and Iraq. With a foundation in mathematics, web development, and programming, he has contributed significantly to education, technology, and translation services. Hussein’s journey reflects his adaptability and passion for learning, from tutoring students in mathematics and English to working in IT, telecommunications, and software engineering roles. His bilingual communication skills in English and Arabic have enabled him to serve communities as an interpreter and translator, while his technical creativity continues to drive his work in coding, software design, and network systems.

Profiles

Scopus
Google Scholar

Education

Mr. Hussein’s educational path is marked by academic excellence in mathematics, computer science, and engineering studies. He earned his Bachelor of Science degree in Toowoomba, Australia, achieving outstanding results in advanced courses including operations research, numerical computing, experimental design, and web technologies. His solid foundation in mathematics and computing equipped him with analytical and problem-solving skills crucial for tackling real-world technical challenges. Alongside formal studies, he pursued professional training in web development and programming, mastering coding languages such as HTML, CSS, Python, JavaScript, and C++. Hussein also gained practical experience in website design and database management, complementing his academic knowledge with hands-on projects.

Experience

Mr. Hussein’s professional experience covers a wide range of roles across education, IT, translation, and engineering. He worked as a website developer with leading companies in Toowoomba, building digital platforms and enhancing user experience. His teaching journey as an English and mathematics tutor demonstrated his ability to simplify complex concepts for students, helping many succeed in academic pursuits. Hussein’s bilingual expertise was recognized in his work as an interpreter, supporting communication in medical, legal, and educational contexts. Transitioning into engineering roles, he contributed as an IT specialist at Dar Al-Auloom Private High School and later advanced to software engineering and telecommunications positions in Kirkuk. His diverse portfolio reflects both technical mastery and cultural adaptability.

Research Interests

Mr. Hussein’s research interests are deeply rooted in the intersection of mathematics, programming, and technology innovation. He is passionate about computational methods, web technologies, and advanced applications of mathematical modeling in computer engineering. His curiosity extends to artificial intelligence, game programming, and database systems, where he enjoys creating applications that merge creativity with technical precision. Hussein is particularly enthusiastic about designing intelligent software solutions, including document readers and chess games with AI capabilities. He also explores optimization techniques and performance computing, driven by a desire to apply theoretical knowledge to practical systems. His long-term vision is to bridge mathematics with next-generation software solutions.

Awards

Mr. Hussein’s achievements highlight his academic dedication and community engagement. He earned recognition in national and international competitions, including the Australian Statistics Competition, where he won the Queensland prize. He also secured credits in the UNSW ICAS Science and Mathematics contests, demonstrating excellence across STEM disciplines. At the University of Southern Queensland, he was actively involved in science and engineering challenges, achieving commendable rankings. Beyond academics, Hussein received awards for both academic excellence and school community participation, showcasing his commitment to leadership and service. These honors underline his consistent performance, strong analytical skills, and ability to contribute meaningfully both inside and outside the classroom.

Publication Top Notes

Empirical curvelet transform based deep DenseNet model to predict NDVI using RGB drone imagery data
Journal: Computers and Electronics in Agriculture, 
Authors: M. Diykh, M. Ali, M. Jamei, S. Abdulla, M.P. Uddin, A.A. Farooque, A.H. Labban, H. Alabdally, et al.

Improving Dry-Bulb Air Temperature Prediction Using a Hybrid Model Integrating Genetic Algorithms with a Fourier–Bessel Series Expansion-Based LSTM Model
Journal: Forecasting, 
Authors: H. Alabdally, M. Ali, M. Diykh, R.C. Deo, A.A. Aldhafeeri, S. Abdulla, et al.

ECT-DLM: Deep Learning Based Empirical Curvelet Transform Approach for Thoracic Disease Diagnosis from X-RAY Images
Conference: ICTIS
Authors: S. Abdulla, S.K. Alkhafaji, H. Marhoon, M. Diykh, M.A. Majed, J. Sadiq, H. Alabdally, et al.

Physical Human Activity Recognition Based on Spectral Graph Wavelet Transforms Integrated with Machine Learning Model
Conference: International Conference on Health Information Science,
Authors: S. Abdulla, A.S. Majeed, A.B. Al-Khafaji, W. Alsalman, M. Diykh, A. Sahi, H. Alabdally, et al.

Robust Approach for Human Activity Recognition Using Decomposing Technique Based Machine Learning Models
Conference: International Conference on Health Information Science,
Authors: S.Z. Hmoud, M. Diykh, S. Abdulla, H. Alabdally, A. Sahi

Conclusion

Mr. Hussein Alabdally represents a professional who blends education, technical skill, and cultural versatility. His journey reflects resilience, adaptability, and a deep passion for mathematics and technology. Whether teaching students, translating across languages, or designing digital systems, Hussein demonstrates excellence in every role he undertakes. His dual citizenship in Australia and Iraq positions him as a global professional with a multicultural perspective. With his diverse experience in tutoring, web development, software engineering, and telecommunications, Hussein continues to grow as a researcher and practitioner in the field of computer science. His career trajectory shows promise for future contributions to both academia and industry.

Mr. Rami Farhat | Marketing | Best Researcher Award

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Mr. Rami Farhat | Marketing | Best Researcher Award

University of Science and Technology Beijing, Lebanon.

Dr. Rami Farhat is a dedicated researcher and academic with expertise in digital marketing strategies, social media advertising, and e-commerce optimization. With a strong background in business administration and technology adoption in marketing, he focuses on consumer behavior in digital platforms. Driven by curiosity and a passion for innovation, he collaborates with interdisciplinary researchers to solve industry challenges.

Profile

Orcid

Education 🎓

Dr. Rami Farhat is currently pursuing a Ph.D. in Business Administration (2021 – 2025) at the University of Science and Technology Beijing, China, where he focuses on digital marketing strategies and consumer behavior in online platforms. Prior to his doctoral studies, he earned a Master’s in International Business Administration (IMBA) (2018 – 2020) from the University of International Business and Economics, Beijing, China, gaining expertise in global business strategies and e-commerce optimization. His academic journey began with a B.S. in Business Administration (Finance Concentration) (2014 – 2017) from the Lebanese American University, Beirut, Lebanon, where he developed a strong foundation in finance, market analysis, and business administration principles. Throughout his education, Rami has demonstrated a keen interest in integrating technology and innovation into business practices, making him a dynamic and forward-thinking researcher in the field.

Professional Experience 💼

Dr. Rami Farhat has a diverse background in digital marketing, business analysis, and research, with experience spanning multiple industries and regions. As a Media Executive at Interesting Times (Lebanon, 2022–2023), he managed and optimized marketing campaigns across the GCC, leveraging social media, TV, and programmatic advertising. Previously, as a Marketing Officer at Ampersand Education (2022), he developed digital branding strategies and high-quality content. His role as a Market Research Analyst at Achi Scaffolding (2021–2022) involved conducting SWOT analyses and consumer behavior research. Dr. Farhat also worked as a Freelancer at Pactera EDGE (China, 2020–2021), focusing on software quality assurance and data optimization. Earlier, he was a Data Entry Specialist at NetEase (China, 2019–2020), translating Arabic, English, and Chinese content for localization. His professional journey began as an Administrative Assistant at Lebanese American University (2014–2017), where he handled marketing and administrative tasks. His expertise spans digital strategy, research, and content management in international markets.

Research Interests 🔬

Digital Marketing Strategies – Exploring innovative ways to enhance online advertising effectiveness.

Social Media Advertising – Studying engagement and conversion strategies on social platforms.

E-Commerce Optimization – Improving online shopping experiences for higher satisfaction.

Consumer Behavior in Digital Platforms – Understanding customer decision-making in online environments.

Technology Adoption in Marketing – Analyzing AI-driven marketing trends.

Awards & Distinctions 🏆

Chinese Government Scholarship Award (2018) – For pursuing a Master’s degree.

Chinese Government Scholarship Award (2021) – For pursuing a Ph.D. in Business Administration.

Reviewer – 5th International Conference on Modern Management based on Big Data.

Publications 📚

Published Papers:

Entrepreneurs’ Adoption of Social Media Winning Platform(s) in Emerging Markets (2024) – International Journal of Internet Manufacturing and Services (IJIMS)
DOI: 10.1504/IJIMS.2025.10064254 (EI, Scopus)

A/B Split Test for Social Media Marketing Optimization: Comparing Creative Components Using Facebook Ads Manager (2024) – International Journal of Internet Manufacturing and Services (IJIMS)
DOI: 10.1504/IJIMS.2026.10067399 (EI, Scopus)

E-commerce for a Sustainable Future: Integrating Trust, Product Quality Perception, and Online Shopping Satisfaction (2024) – Journal of Sustainability
DOI: 10.3390/su17041431 (SSCI, Q2, IF: 3.3)

 

 

 

Assoc. Prof. Dr. Djamchid ASSADI | Digital Tech Management |Best Researcher Award

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Assoc. Prof. Dr. Djamchid ASSADI | Digital Tech Management |Best Researcher Award

Burgundy School of Business, France.

Prof. Djamchid Assadi is a distinguished academic and researcher affiliated with CEREN, EA 7477, at the Burgundy School of Business - Université Bourgogne Franche-Comté. He holds an Accreditation to Supervise Research (HDR), demonstrating his expertise in guiding advanced research. His work focuses on the intersection of business models, artificial intelligence, and financial inclusion, contributing significantly to academic and industry advancements.

Profile

Scopus
Orcid

Education 🎓

Prof. Assadi earned his Accreditation to Supervise Research (HDR) and has been deeply involved in research across multiple disciplines, enhancing his academic and professional footprint.

Experience 🌟

Prof. Assadi serves as the Director & Researcher at CEREN, EA 7477, Burgundy School of Business, where he leads impactful research initiatives. He is also a Guest Editor for various international academic journals, contributing his expertise to the advancement of scholarly publications. Additionally, he is an Academic Advisory Board Member at IMS Ghaziabad & GL Bajaj Institute of Management and Research, guiding academic and research activities in these institutions. As a PhD Co-Supervisor, he has mentored numerous doctoral candidates across various universities, playing a crucial role in shaping research in business and financial studies.

Research Interests 🔬

The Role of Artificial Intelligence in Strategic Development, Business Models, Consumer Behavior, and Financial Inclusion

Organizational Ecosystems: Governance of Interactions and Transactions

Collaborative, Sharing, and Platform Economy

Influence of Non-Price Factors on Purchasing Decisions and Strategic Behavior

Economic and Geostrategic Analysis of Rent-Seeking Behavior

Awards & Honors 🏆

Prof. Assadi has been recognized for his outstanding contributions to business research and financial inclusion, with multiple accolades in the field of strategic and digital entrepreneurship.

Publications 📚

📄 Fighting Fire with Fire: Combating Criminal Abuse of Cryptocurrency with a P2P Mindset

Journal: Information Systems Frontiers

Published Year: 2024

DOI: 10.1007/s10796-024-10498-7

Contributors: Galit Klein, Djamchid Assadi, Moty Zwilling

📚 Digital Sustainable Entrepreneurship Business Model and Its Contribution to Sustainable Development Goals

Contributors: Surabhi Singh, Urvashi Makkar, Djamchid Assadi