I am currently a research fellow at the University of Melbourne, where I work with Prof. Trevor Cohn and Assoc Prof. Benjamin Rubinstein on issues around adversarial learning for NLP (understanding vulnerabilities of NLP systems, such as machine translation). Prior to this, I was a CSIRO Early Research Career (CERC) postdoctoral fellow at CSIRO Data61, where I worked with Dr. Cecile Paris and others on opinion mining in social media. I obtained PhD in Computer Science from Nanyang Technological University, under the supervision of Assoc Prof. Jie Zhang, and a master degree from the University of Chinese Academy of Sciences.
- My research interests lie in the general area of natural language processing, artificial intelligence, and cybersecurity, particularly in developing explainable and robust models for various NLP tasks, such as text classification and machine translation. I am also interested in machine learning and deep learning techniques applied to those tasks, such as probabilistic graphical models (e.g., MRFs, VAEs, GANs, etc.).[Google Scholar]
- March 2020: our paper “DeepMnemonic: Password Mnemonic Generation via Deep Attentive Encoder-Decoder Model” was accepted by TDSC 2020.
- Jan 2020: our paper “DAN: Dual-View Representation Learning for Adapting Stance Classifiers to New Domains” was accepted by ECAI 2020.
- August 2019: Our paper “STRIP: A Defence Against Trojan Attacks on Deep Neural Networks” was accepted by ACSAC 2019.
- May 2019: Our paper “Recognising Agreement and Disagreement between Stances with Reason Comparing Networks” was accepted by ACL 2019.
- May 2018: Our paper “Cross-Target Stance Classification with Self-Attention Networks” was accepted by ACL 2018.
- April 2017: Our paper “Online Reputation Fraud Campaign Detection in User Ratings” was accepted by IJCAI 2017.
- Feb 2017: Our paper “Large-Scale Wi-Fi Hotspot Classification via Deep Learning” was accepted as a poster by WWW 2017.
- Aug 2015: Our paper “Towards Collusive Fraud Detection in Online Reviews” was accepted by IEEE ICDM 2015.
- Jan 2015: Our paper “Combating Product Review Spam Campaigns via Multiple Heterogeneous Pairwise Features” was accepted by SIAM SDM 2015.