• Aim to start conversations, deepen interactions and foster closer collaborations between the School of Computing (SoC) and Faculty of Science (FoS).
• Encourage collaborative projects involving SoC and FoS researchers targeting the AI research grant call to seed high-quality research efforts aimed at developing AI and adjacent technologies.
| 8.50 am – 9.00 am | Welcome address Prof Bing Sheng HE and A/P Giorgia PASTORIN |
| 9.00 am – 9.20 am | Graph deep learning for science A/P Xavier BRESSON |
| 9.20 am – 9.40 am | Recent advances in spatial transcriptomic technology Asst Prof Boxiang LIU |
| 9.40 am – 10.00 am | TBC Prof Lim Soon WONG |
| 10.00 am – 10.20am | TBD A/P Utkur MIRSAIDOV |
| 10.20 am – 10.40 am | Coffee break |
| 10.40 am – 11.00 am | AI-Science collaboration in scientific document processing A/P Min-Yen KAN |
| 11.00 am – 11.20 am | Bringing natural history into the 21st century - challenges and opportunities of machine learning in biodiversity science Asst Prof Jun Ying LIM |
| 11.20 am – 11.40 am | Scaling up the implementation of nature-based climate solutions across Southeast Asia Asst Prof Yiwen ZENG |
| 11.40 am – 12.00 pm | Closing |
| 12.00 pm onwards | Lunch networking session |
A/P Xavier Bresson will briefly introduce graph neural networks and their applications to drug discovery (halicin antibiotic, drug-target interaction), drug design, biology (protein/rna folding, protein interaction and function) and genetics (genome assembly).
Bio: Xavier Bresson is an Associate Professor in the Department of Computer Science at the National University of Singapore (NUS). His research focuses on Graph Deep Learning, a new framework that combines graph theory and neural networks to tackle complex data domains. In 2017, he received the USD 2M NRF Fellowship, the largest individual grant in Singapore, to develop this new framework. He was also awarded several research grants in the U.S. and Hong Kong. He co-authored one of the most cited works in this domain (10th most cited paper at NeurIPS) and has significantly contributed to mature these emerging techniques. He has organized several conferences, workshops and tutorials on graph deep learning such as the 2022 conference on “Learning on Graphs”, the IPAM’23 workshops on “Learning and Emergence in Molecular Systems”, the IPAM’23’21 workshops on “Deep Learning and Combinatorial Optimization”, the MLSys’21 workshop on “Graph Neural Networks and Systems”, the IPAM’19 and IPAM’18 workshops on “New Deep Learning Techniques”, and the NeurIPS’17, CVPR’17 and SIAM’18 tutorials on “Geometric Deep Learning on Graphs and Manifolds”. He has been a regular invited speaker at universities and companies to share his work. He has also been a speaker at the NeurIPS’22, KDD’21, AAAI’21 and ICML’20 workshops on “Graph Representation Learning”, and the ICLR’20 workshop on “Deep Neural Models and Differential Equations”. He has taught undergraduate and graduate courses on Deep Learning and Graph Neural Networks since 2014.
Bio: Boxiang LIU is an Assistant Professor with the Department of Pharmacy and Department of Biomedical Informatics, NUS. He obtained his MS in Statistics and PhD in Bioinformatics from Standard University. After a research stint at Baidu Research Institute, he joined NUS as a faculty member in 2022. His research focuses on the development of statistical methods, machine learning models (especially deep learning models), and visualization techniques to address novel scientific questions and data modalities. The computational techniques developed by his research group are rooted in biological questions, but often borrow ideas from other domains such as natural language processing and computer vision.
Bio: Wong Limsoon is Kwan-Im-Thong-Hood-Cho-Temple Professor in the School of Computing at the National University of Singapore (NUS). He was also a professor (now honorary) of pathology in the Yong Loo Lin School of Medicine at NUS. Before coming to NUS, he was the Deputy Executive Director for Research at A*STAR’s Institute for Infocomm Research. He currently works mostly on knowledge discovery technologies and their application to biomedicine. He has also done, in the earlier part of his career, significant research in database query language theory and finite model theory, as well as significant development work in broad-scale data integration systems. Limsoon is a Fellow of the ACM, inducted for his contributions to database theory and computational biology. Some of his other awards include the 20 03 FEER Asian Innovation Gold Award for his work on treatment optimization of childhood leukemias, the 2006 Singapore Youth Award Medal of Commendation for his sustained contributions to science and technology, and the ICDT 2014 Test of Time Award for his work on naturally embedded query languages. He co-founded Molecular Connections in India, and has served as its chairman for over a decade, seeing the company growing progressively to some 2,000 information curators, software engineers, research scientists.
Bio: pending
Science is a runaway success. The production of new knowledge has become so fast-paced that effective aids are needed for scholars to track and make sense of newly-published work. AI can help with this, through the production of aids that help scholars track science macroscopically through its record by its publications, authors, institutions, as well as microscopically through methods, datasets, reagents, formulas and discipline-specific notation. Our group’s scholarly document processing subgroup seeks collaborators looking to co-develop new AI means to aid the sensemaking workflows of their discipline’s scholarly works. Examples include document summarization, author and topic tracking and accompanying data visualizations. We describe our work in SciWING and SciAssist, two scholarly document processing toolkits developed in our group – the Web Information Retrieval and Natural Language Processing Group (WING).
Bio: Min-Yen Kan is an associate professor at the National University of Singapore. He served the University as a Deputy Director (Research) in the NUS Institute of the Application of Learning Sciences and Education Technology (ALSET). Min is an active member of the Association of Computational Linguistics (ACL) and was the inaugural recipient of the Distinguished Service Award in 2019. His research interests include digital libraries and applied natural language processing and information retrieval. He is recognized as a distinguished speaker by the ACM for natural language processing and digital libraries research. Specific projects include work in the areas of discourse analysis, instructor intervention prediction, online forum analysis and automatic summarization. http://wing.comp.nus.edu.sg/
Bio: Jun Ying LIM is an Assistant Professor with the Department of Biological Sciences, NUS and a principal investigator at the Centre for Nature-based Climate Solutions. He studied and trained at Imperial College London (2009–2013), later receiving a Ph.D. in Integrative Biology from University of California, Berkeley (2013–2018). After post-doctoral stints at the University of Amsterdam and Nanyang Technological University, he joined NUS as a faculty member in 2021. His research focuses on the ecology, evolution and biogeography of tropical ecosystems, with a focus on plant-animal interactions.
Bio: Yiwen ZENG is a Research Assistant Professor with the Centre for Nature-based Climate Solutions, NUS. He is a conservation ecologist and geospatial modeller who is focused on conservation science and policy, particularly within the tropics. A large part of his research is aimed at finding ways to conserve nature and biodiversity that are both socially responsible and ecologically sound. His goal is to develop research that can be used to increase the implementation of conservation interventions across biodiverse regions such as Southeast Asia.
All talks will be held in Executive Classroom, #04-02, building and Networking session will be held in Multipurpose Space, #04-01, in the NUS School of Computing, COM2 building.
