about.

Hi! I am a graduate student studying MSc. Computer Science at Stanford University, specializing in artificial intelligence (AI) and human-computer interaction (HCI).

Prior to that, I was in the pioneer batch of the MSc. Urban Science, Policy and Planning program at the Singapore University of Technology and Design. As my final project under the supervision of Prof. Lim Sun Sun, I designed an online primer to algorithmic bias - Machines Gone Wrong.

I also spent about two years as an AI researcher working on topics including privacy, meta-learning and adversarial attacks.

Contact me at sweekiat <at> stanford <dot> edu.


Publications

Few-Shot Regression via Learned Basis Functions
Yi Loo, Swee Kiat Lim, Gemma Roig, Ngai-Man Cheung
International Conference on Learning Representations (ICLR) 2019
Learning from Limited Labeled Data Workshop

DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN
Swee Kiat Lim, Yi Loo, Ngoc-Trung Tran, Ngai-Man Cheung, Gemma Roig, Yuval Elovici
IEEE International Conference on Data Mining (ICDM) 2018

MalwareTextDB: A Database for Annotated Malware Articles
Swee Kiat Lim, Aldrian Obaja Muis, Wei Lu, Chen Hui Ong
Annual Meeting of the Association for Computational Linguistics (ACL) 2017

Carbon‐Nanodot Solar Cells from Renewable Precursors
Adam Marinovic, Swee Kiat Lim, Steve Dunn, Maria‐Magdalena Titirici, Joe Briscoe
ChemSusChem 10.5 (2017): 1004-1013.

News

  • Moderated a panel on AI start-ups at Echelon Asia Summit 2017 (link)