Technical sharing session on Trustworthy AI

Technical Sharing Session on Trustworthy AI

Expand your knowledge on Trustworthy AI and engage in fruitful discussions with our experts.

Date and time
LocationInfocomm Media Development Authority
Level 4 Communal Cafe
10 Pasir Panjang Road
Mapletree Business City
Link to register Register now

About IMDA’s Technical Sharing Session

IMDA’s Technical Sharing Session is a regular platform where esteemed researchers are invited to present on the latest emerging tech topics, and attendees can expect to:

  • Gain invaluable insights from esteemed experts on the latest research and groundbreaking discoveries
  • Network with like-minded technical experts
  • Uncover opportunities for collaboration and innovation

Key takeaways

Technical sharing session

Date and time

24 Oct 2023, 2:30pm - 5:00pm


From this session, you would have the opportunity to unpack the following:

  • Examining the privacy implications of machine learning algorithms
  • Developing techniques to circumvent adversarial attacks on pretrained language models
  • Harnessing cybersecurity for AI generated content


Hear from these esteemed experts who will unpack the latest developments in this exciting field.

Dr Liu Yang from NTU

Liu Yang

AIGC and Cybersecurity, NTU


Dr. Yang Liu obtained his bachelor and ph.d degree in the National University of Singapore in 2005 and 2010, respectively. In 2012, he joined Nanyang Technological University as a Nanyang Assistant Professor. He is currently an associate professor, director of the cybersecurity lab, Program Director of HP-NTU Corporate Lab and Deputy Director of the National Satellite of Excellence of Singapore. In 2019, he received the University Leadership Forum Chair professorship at NTU. Dr. Liu specializes in cyber security and software engineering. His research has bridged the gap between the theory and practical usage of formal methods and program analysis to evaluate the design and implementation of software for high assurance and security. By now, he has more than 250 publications in top tier conferences and journals. He has received a number of prestigious awards including MSRA Fellowship, TRF Fellowship, Nanyang Assistant Professor, Tan Chin Tuan Fellowship, and 10 best paper awards and one most influence system award in top conferences like ASE, FSE and ICSE.

Luu Anh Tuan from NTU

Luu Anh Tuan

Attack and Defense Techniques for Pretrained Language Models, NTU


Dr. Luu Anh Tuan is currently an Assistant Professor at Nanyang Technological University, Singapore. Prior to that, he was a Research Fellow at MIT from 2018 to 2020. Luu’s research interests lie in the intersection of AI, Deep Learning, and NLP. He has published over 70 papers on top-tier conferences and journals including NeurIPS, ICML, ICLR, ACL, EMNLP, KDD, WWW, TACL, AAAI, etc. Dr. Luu also served as the Action Editor for Computational Linguistics and ACL Rolling Review, Senior Area Chair of EMNLP 2020, Area Chair of ACL 2021-2023, Area Chair of ICLR 2023-2024, Area Chair of NeurIPS 2023, Senior Program Committee of IJCAI 2020-2021, and Program Committee member of ICML, AAAI, etc. He got the outstanding paper award in the International Conference on Learning Representations (ICLR) 2021. He was also a recipient of the Ministry of Trade and Industry (MTI) Singapore Innovation Award 2013.

Reza Shokri from NUS

Reza Shokri

Data Protection and Privacy in Machine Learning, NUS


Reza Shokri is a NUS Presidential Young Professor of Computer Science, and a part-time research consultant at Microsoft. He is an Asian Young Scientist Fellow. His research focuses on data privacy and trustworthy machine learning. He is a recipient of the IEEE Security and Privacy (S&P) Test-of-Time Award 2021, for his paper on quantifying location privacy, and the Caspar Bowden Award for Outstanding Research in Privacy Enhancing Technologies in 2018, for his work on analyzing the privacy risks of machine learning algorithms. He received the Best Paper Award at ACM Conference on Fairness, Accountability, and Transparency (FAccT) 2023 for his work on analyzing fairness in machine learning. He has also received the NUS Early Career Research Award 2019, VMWare Early Career Faculty Award 2021, Meta (Facebook) Faculty Research Award 2021, Google Faculty Award on Data Protection and Privacy 2021, and Intel Faculty Research Award (Private AI Collaborative Research Institute) 2021---2023. He obtained his PhD from EPFL.