Hello!

I am currently a final-year PhD Candidate in Natural Language Processing (NLP) at Nanyang Technological University in Singapore, in NTU-NLP group. I am advised by Dr. Shafiq Joty and Dr. Aixin Sun. Through my SINGA scholarship, I am also attached at A*STAR I2R ALI Lab, where I am supervised by Dr. Nancy Chen.

My PhD focus is on abstractive text summarization. Specifically, I am interested in how to build better summarization systems by going beyond the standard framework of MLE with token-level cross-entropy loss and teacher forcing. For instance, I have explored in depth how to learn summarization at the entire summary level (see my papers SummaReranker, SummaFusion, and SummScore on this topic). I am currently focusing on analyzing large language models (LLMs), including their behavior on summarization tasks. See my recent work on analizing the lost-in-the-middle phenomenon for LLMs in the task of summarization. I am also working on core issues in LLMs, including: scaling context length, evaluating open-source LLMs, and contamination. For our work LOCOST on using state-space models to scale the context length of the encoder, we won the Best Paper Award at the EACL 2024 conference (congrats Florian!). In Spring 2023, I interned in Huawei Noah Ark’s lab in Singapore under the supervision of Dr. Zhang Hao, where I worked on improving conversational recommender systems with language models. In Spring 2024, I interned at Lingjun Investment, a Chinese hedge fund, where I worked on index re-balancing stategies.

I am extremely passionate about machine learning, having been in this area since 2016. Before PhD, I obtained a MSc in Applied Computing (MScAC) from University of Toronto Department of Computer Science in 2018 and a B.Eng and M.Eng from Ecole Centrale Paris (a leading French Engineering School now known as CentraleSupelec and part of the newly formed Paris Saclay University) in 2015 and 2018, respectively. I also worked full-time from 2018 to 2020 as Machine Learning Research Scientist at Layer 6 AI, TD Bank’s AI lab in Toronto, where my research in machine learning applied to healthcare (diabetes) was featured in Nature. During my M.Eng, I interned at Thales and A*STAR I2R Visual Computing Lab in Singapore, where I worked on video classification. In my spare time, I like participating in machine learning competitions like those hosted by Kaggle.

Research Community Service:
Reviewer (journals): IEEE/ACM TASLP (2021-)
Reviewer (conferences): ACL Rolling Review (2023-), CoNLL 2023, SIGDIAL 2023, AACL 2023