Our Team

Dr Atsushi Nitanda is a Principal Scientist at A*STAR Centre for Frontier AI Research (A*STAR CFAR). He also holds a joint appointment as an Associate Professor in the College of Computing and Data Science (CCDS) at Nanyang Technological University, Singapore (NTU Singapore).

Prior to his current position, he was an Associate Professor at the Kyushu Institute of Technology and an Assistant Professor at the University of Tokyo. Previously, he worked at NTTDATA-MSI in Japan as a researcher. He obtained his Ph.D. in Information Science and Technology from the University of Tokyo in 2018.

His research primarily focuses on the mathematical foundations of machine learning, stochastic optimisation, and sampling methods, with the goal of understanding the capabilities of machine and deep learning models through the lens of optimisation dynamics and sampling-based approaches.

For example, he has worked on stochastic gradient descent, acceleration methods, and the learning theory of neural networks. In particular, he has made significant contributions to the theoretical foundations of mean-field Langevin dynamics, including convergence analysis and the propagation of chaos.

In 2021, he received the Outstanding Paper Award at ICLR and the Dean’s Awards from the University of Tokyo for academic achievement in doctoral and master’s research in 2019 and 2009 respectively. Following his selection as a TMLR expert reviewer, he has served as an action editor for TMLR, editorial board reviewer for JMLR, editorial board member for IEICE Transactions, and IBISML committee member.

Basura Fernando is a research scientist at A*STAR Centre for Frontier AI Research (A*STAR CFAR). He is a National Research Foundation (Singapore) Fellowship (NRF-F-2022) recipient and a visiting PhD supervisor at The University of Edinburgh. He was an honorary lecturer at the Australian National University (ANU) and a research fellow at the Australian Centre for Robotic Vision (ACRV), the Australian National University. He obtained PhD from the VISICS group of KU Leuven, Belgium in 2015. He is interested in Computer Vision and Machine Learning research.

Dr He Tiantian is a Senior Scientist and Early-Career PI at A*STAR Center for Frontier AI Research (A*STAR CFAR). He is also an adjunct Senior Scientist at A*STAR Singapore Institute of Manufacturing Technology (A*STAR SIMTech). Before joining A*STAR, he was a Research Fellow at Nanyang Technological University (NTU Singapore). Dr He received MSc and PhD degrees from the Department of Computing, Hong Kong Polytechnic University in 2012 and 2017 respectively. His research is at the forefront of AI, with a particular focus on graph (deep) learning, federated learning, bioinformatics, and foundation models.

In 2019, Dr He received the Best Paper Award from the IEEE International Conference on Tools with Artificial Intelligence. To date, Dr He has published more than 50 papers, most of which are in top-tier venues, including NuerIPS, ICML, AAAI, ICDM, AIJ, TKDE, TFS, TCYB, and TSC. His research, which has been funded by several national organisations, such as the National Natural Science Foundation of China and A*STAR I&E GAP, has made significant contributions to the field. He has served as PC member or Area Chair for top conferences, including NeuIPS, ICML, ICLR, ECAI, and IJCNN, and invited reviewer for prestigious journals, such as TPAMI, AIJ, TKDE, TNNLS, TFS, TCYB, and TKDD. Besides these, he is also an Associate Editor for Memetic Computing.

>> View Dr He's list of publications here.

Dr Nancy F. Chen is an ISCA Fellow (2025), AAIA Fellow (2025), and A*STAR Fellow (2023), and a recipient of the Asian Women Tech Leaders Award (2025). She was also inducted into IEEE Eta Kappa Nu (HKN), the IEEE honour society recognising outstanding engineers.

At A*STAR, Dr Chen leads the Multimodal Generative AI group and the AI for Education Programme. A serial Best Paper Award winner at leading international conferences - including ICASSP, ACL, EMNLP, MICAAI, COLING, APSIPA, SIGDIAL and EACL – her research spans applications in education, healthcare, neuroscience, social media, security and forensics. Her multimodal and multilingual AI technologies have also led to commercial spin-offs and adoption by Singapore’s Ministry of Education.

An active international research leader, Dr Chen has served as Programme Chair for top-tier AI conferences such as NeurIPS and ICLR, and has delivered international keynote addresses at major forums worldwide. She is also an IEEE Signal Processing Society Distinguished Lecturer (2023 – 2024), contributing to the advancement and inspiration of the global research community.

Dr Chen's strategic vision and policy acumen are reflected in her extensive service to the global STEM community. She has served as an APSIPA Board-of-Governor member (2024–2026), ISCA Board Member (2021-2024), and was recognised as one of Singapore’s 100 Women in Tech (2021). Her professional accolades include awards from IEEE, Microsoft, Proctor & Gamble, UNESCO, L'Oréal, and the National Institute of Health (USA). Dr Chen has long advised government and industry partners on AI and emerging technologies, beginning during her tenure at MIT Lincoln Laboratory while pursuing her PhD at MIT and Harvard.

Dr Lim Joo-Hwee is a recognised AI researcher, ranked among the World’s Top 2% Scientists by Stanford University, with a portfolio of over 330 peer-reviewed publications and 30 patents. He is a trailblazer in computer vision, having independently pioneered the globally recognized bag-of-visual-words framework for image indexing and retrieval (published at ACM Digital Libraries 1999 and IEEE ICMCS 1999), based on spatial aggregation of visual keywords, and a visual query language based on visual patterns, spatial quantifiers, and Boolean operators.

His research seeded the Snap2Tell technology, which has been licensed to a dozen of companies, and successfully adopted by award-winning SMEs across the mobile learning and advertising sectors, including A*STAR spin-off (2009) which licensed the technology in 2010 and had rapidly expanded overseas with more than 100 employees.

He was knighted with the 'Chevalier dans l’ordre des Palmes Academiques' by the French Government in 2008 and received Singapore's National Day Commendation Medal in 2010. Beyond Best Paper awards at premier conferences like AAAI and ACM MMM, he is a passionate talent developer, having trained more than 15 PhD students, honoured with A*STAR’s Most Inspiring Mentor Award (2018) and the AGA STAR Mentor Award (2023).

He is currently a Team Lead at A*STAR Centre for Frontier AI Research (A*STAR CFAR), alongside his role as Senior Principal Scientist III and an Adjunct Professor at CCDS, NTU. He also serves as Associate Editor for IEEE Trans on AI, Conference Area Chairs for AAAI, NeurIPS, ICML, ICLR etc.

Dr Yin Haiyan is a senior research scientist and early career principal investigator at A*STAR Centre for Frontier AI Research (A*STAR CFAR). She received her Ph.D. in Computer Science from Nanyang Technological University (NTU Singapore) and has worked as a research scientist at Baidu Research USA and Sea AI Lab.

Her research spans agentic AI, reinforcement learning, meta-learning, and trustworthy decision-making, with a focus on building intelligent systems that generalise across tasks, adapt rapidly to new environments, and exhibit self-directed reasoning and planning. Her work on continual, resource-efficient, and trustworthy reinforcement learning has been supported by competitive research grants, and her publications appear in leading AI conferences including NeurIPS, ICLR, AAAI, IJCAI, and AAMAS.

Mr Liu Zhengyuan is currently a Team Lead in Ethical and Trustworthy AI at A*STAR Centre for Frontier AI Research (A*STAR CFAR). His research primarily focuses on Natural Language Processing, Multimodal Foundation Models, Frontier Agentic Systems, and Human-Centred AI. He also leads applied science as a co-Principal Investigator (co-PI) on projects in AI for healthcare and education. He has published over 50 research papers in top-tier AI and natural language processing conferences, including ICML, NeurIPS, ACL, NAACL, EMNLP, COLING, AAAI, ICASSP, and INTERSPEECH.

He serves as an Assistant Program Chair for NeurIPS 2025 and as Program Committee member for leading conferences, including NeurIPS, ICLR, ICML, and ACL. He also serves as a reviewer for journals such as IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP), ACM Computing Surveys (CSUR), and Neurocomputing. He has also been prompted as an IEEE Senior Member in recognition of his significant professional achievements. His honours include the Best Paper Award at SIGDIAL 2021, C3NLP in ACL 2024, and SUMEval in COLING 2025; the Outstanding Paper Award at EMNLP 2023 and EMNLP 2024, the Elfreda A. Chatman Research Award in ASIS&T 2025. 

Abhishek is an IEEE Senior Member. He received the Ph.D. degree in Engineering Science from the University of Auckland, New Zealand, in 2014. He has diverse research experience in computational science, ranging from mathematical and numerical modeling in engineering to topics in computational intelligence. His current research interest lies in data-lean transfer and multitask optimization, neuroevolution, and scientific machine learning, with application to manufacturing system planning under uncertainty and complex engineering design. Abhishek received the 2019 IEEE Transactions on Evolutionary Computation Outstanding Paper Award for pioneering work on multitask evolutionary computation, and in 2021 he received the IEEE Transactions on Emerging Topics in Computational Intelligence Outstanding Associate Editor Award. 

Liang Kaicheng is a Principal Investigator and Senior Scientist at A*STAR’s Institute of Bioengineering and Bioimaging (IBB). He graduated with a PhD in Electrical Engineering from the Massachusetts Institute of Technology (MIT) in 2018. Funded by the National Research Foundation Fellowship (2021-2026), his lab focuses on optical techniques and imaging algorithms for obtaining real-time histological information from tissue immediately after resection during surgery, or in vivo before resection. This approach empowers clinicians with rapid feedback, potentially guiding biopsies and expediting clinical decisions.

Kaicheng’s efforts have spanned the full translational pathway, from benchtop prototypes to validation in large animals and humans. There is tremendous growth in developing specialised machine learning techniques to enhance the performance, speed and resolution of optical imaging hardware technology. The multi-megapixel/gigavoxel per sec data rates of modern imaging modalities, coupled with neural networks as powerful function approximators, motivate real-time, data-driven approaches to efficient computational imaging. These fresh research directions marrying hardware and software have bountiful potential to generate not only impactful fundamental and interdisciplinary research, but also clinical value in a broad range of specialties, where his lab’s vertical integration from bench to bedside ensures the quickest path towards clinical proof of concept translation.

Lam Ping Koy is a renowned experimental physicist in the research field of quantum information and metrology. He has made many scientific contributions in using laser to generate quantum states of light, slow and stop light, study quantum entanglement, encrypt information and perform precision measurements. Ping Koy started his career as an engineer for Sony and Hewlett-Packard before completing his PhD at the Australian National University in 1999. He was awarded two Australian Eureka Prizes, in recognition of his research in quantum teleportation and quantum encryption in 2003 and 2006, respectively. In 2007, Ping Koy co-founded QuintessenceLabs –  an award winning Australian company that commercialises quantum communication technology. More recently, Ping Koy was awarded the Australian Institute of Physics Alan Walsh Medal in recognition of his contribution to Australian Industry and was made a Laureate Fellow of the Australian Research Council. In 2020, he was elected as a Fellow of the Australian Academy of Science. Ping Koy has published close to 300 scientific articles with more than 50 papers appearing in Physical Review Letters, Science and the Nature research journal suite. He is currently the Chief Quantum Scientist at A*STAR.

Lee Hwee Kuan’s current research work involves the development of Artificial Intelligence (AI) research for clinical and biological applications. His laboratory focus on diverse research activities, including more basic AI centric research as well as AI applications. Theoretical AI development activities in Hwee Kuan’s laboratory is mostly inspired by impactful clinical use cases. Clinical application areas include, diagnostics in cancers, cardiology, dermatology and  interventional radiology. In the area of biology, Hwee Kuan’s laboratory develops bioinformatics pipelines in spatial omics and single cell analysis, and in the development of AI in protein science and drug discovery. Hwee Kuan’s primary appointment is as the Deputy Director for Training and Talent development in the Bioinformatics Institute. He also holds multiple adjunct and joint appointments in the local universities and other research institutions.

Sebastian Maurer-Stroh studied theoretical biochemistry at the University of Vienna and wrote his master and PhD thesis at the Institute of Molecular Pathology (IMP). After FEBS and Marie Curie fellowships at the VIB-SWITCH lab in Brussels, he has been leading the sequence analytics portfolio in the A*STAR Bioinformatics Institute (A*STAR BII) since 2007 and Infectious Disease Programme since 2010. He is the Executive Director of BII since January 2021. His computational team is well known for successes at the public-private interface in Singapore from Precision Medicine to Consumer Product and Food Safety and of course for his critical contributions to national and global viral pathogen surveillance through the GISAID data science initiative that has become the single most important source for virus outbreak data sharing and analysis in this pandemic powering public health responses globally.