Shengchao Liu | Computer Science | Research Excellence Award

Published on by Invention Awards

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.

Citation Metrics (Google Scholar)

4000
3000
2000
1000
  500
  100
      0

Citations
3510

Documents
40

h-index
22

Citations

Documents

h-index

View Google Scholar Profile

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

Published on by Invention Awards

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

Published on by Invention Awards

Mr. Kangwon Lee | Computer Science | Best Researcher Award

Gyeongsang National University | South Korea

Mr. kangwon lee is a senior undergraduate student in Computer Engineering at Gyeongsang National University, specializing in artificial intelligence, music technology, audio signal processing, and natural language processing. he has pursued impactful research projects, including the development of an AI-based sentiment analysis and depression risk detection platform that integrates Valence, Arousal, and Dominance (VAD) metrics for more nuanced prediction models. As a co-author, he contributed to a peer-reviewed paper on AI-based emotion detection and expert-linked platforms, published in the Journal of the Korea Information Technology Society (2025), and his work earned the Excellence Prize at the 33rd Software Contest hosted by Gyeongsang National University in 2024. Professionally, Mr. lee has demonstrated strong technical and problem-solving skills across both civilian and military roles. At Appen Limited, he currently works as a Quality Assurance specialist, where he ensures data quality and optimizes annotation processes. During his military service, he served as an RPA Developer and Convergence Systems Developer for the Republic of Korea Air Force, achieving major efficiency gains by enhancing automation workflows with Python and UiPath. Additionally, he gained hands-on IT support experience at Samdong Heungsan Co., Ltd., managing system maintenance, software deployment, and network configuration for DB Insurance. Proficient in Python, PyTorch, SQL, and UiPath, Mr. lee holds certifications such as SQLD and TOEIC Speaking (AL). His career reflects a strong commitment to integrating AI technologies into human-centered applications, advancing innovative solutions that bridge technical advancement with social impact.

Profile: Orcid 

Featured Publications

Web-Based Platform for Quantitative Depression Risk Prediction via VAD Regression on Korean Text and Multi-Anchor Distance Scoring

Development of an AI-based Sentiment Analysis and Expert-Linked Platform for Early Detection of Socially Isolated and Depression Risk Groups

Hussein Alabdally | Computer Science | Best Researcher Award

Published on by Invention Awards

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.