Yang Xianglin 「杨芗琳」
I'm now a fourth-year PhD candidate at the National University of Singapore supervised by Prof. Dong Jin Song. I received my Bachelor from Fudan University in 2016.
My research interests lie in robust and trustworthy machine learning techniques. Recently I am interested in AI Agent and LLM.
I'm open to discussion or collaboration. Feel free to drop me an email if you're interested in my research.
RECENT NEWS 🧅
- 01/2024. I become a research intern at Lenovo working on AI Agent!
- 11/2023. I was honored to receive the Dean’s Graduate Award from NUS. Thanks Prof. Dong for the nomination and support!
- 07/2023. Our paper DeepDebugger: An Interactive Time-Travelling Debugging Approach for Deep Classifiers has been accepted to ESEC/FSE 2023!
- 05/2023. Our paper Thompson Sampling with Less Exploration is Fast and Optimal has been accepted to ICML 2023!
- 09/2022. Our paper Debugging and Explaining Metric Learning Approaches: An Influence Function Based Perspective has been accepted to NeurIPS 2022!
- 04/2022. Our paper Temporality Spatialization: A Scalable and Faithful Time-Travelling Visualization for Deep Classifier Training has been accepted to IJCAI 2022!
- 03/2022. Our paper Inferring Phishing Intention via Webpage Appearance and Dynamics: A Deep Vision Based Approach has been accepted to USENIX 2022!
- 02/2022. Our paper DeepVisualInsight: Time-Travelling Visualization for Spatio-Temporal Causality of Deep Classification Training has been accepted to AAAI22 with oral presentation (4%)!
PUBLICATIONS
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[new]
Xianglin Yang, Yun Lin, Yifan Zhang, Linpeng Huang, Jin Song Dong, Hong Mei.
DeepDebugger: An Interactive Time-Travelling Debugging Approach for Deep Classifiers. ESEC/FSE 2023 . -
Tianyuan Jin, Xianglin Yang, Xiaokui Xiao, Pan Xu.
Thompson Sampling with Less Exploration is Fast and Optimal. ICML 2023 . -
Ruofan Liu, Yun Lin, Xianglin Yang, Jin Song Dong.
Debugging and Explaining Metric Learning Approaches: An Influence Function Based Perspective. NeurIPS 2022 . -
Xianglin Yang, Yun Lin, Ruofan Liu, Jin Song Dong.
Temporality Spatialization: A Scalable and Faithful Time-Travelling Visualization for Deep Classifier Training. IJCAI 2022 . [code] [website] -
Ruofan Liu, Yun Lin, Xianglin Yang, Siang Hwee Ng, Dinil Mon Divakaran, Jin Song Dong.
Inferring Phishing Intention via Webpage Appearance and Dynamics: A Deep Vision Based Approach. USENIX Security 2022 . [code] [website] -
Xianglin Yang#, Yun Lin#, Ruofan Liu, Zhenfeng He, Chao Wang, Jin Song Dong, and Hong Mei.
DeepVisualInsight: Time-Travelling Visualization for Spatio-Temporal Causality of Deep Classification Training. AAAI 2022. [oral presentation, 4.5%]. [paper] [video] [code] [website]
WORKING EXPERIENCE
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(JAN 2024 - ) Research Intern @ Lenovo, Beijing, China
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(Jul 2019 - Oct 2020) Research Assistent @ National University of Singapore, Singapore
EDUCATION
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(Aug 2020 - ) PhD candidate @ NUS, School of Computing
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(Sep 2016 - Jul 2020) B.S. @ Fudan University, School of Computer Science and Technology
AWARDS
- Dean's Graduate Research Excellence Award
- First prize in Research Prototype Competition in ChinaSoft with "Deep Classifier Oriented Interactive Debugger". video
- NUS SOC Research Achievement Award in Sem 2 AY2021/2022
- 2nd Prize - Scholarship of Fudan University for Outstanding Students (15%) 2019-2020
- 2nd Prize - Scholarship of Fudan University for Outstanding Students (15%) 2017-2018
- 3rd Prize - Scholarship of Fudan University for Outstanding Students (30%) in 2017-2018
- 1st Prize - The Preliminary Test of The 29th Chinese Chemistry Olympiad (Fujian) in 2015
- Rank 1 - 2013 National Chemistry Quality and Experiment Ability Competition for Junior Middle School Students (Xiamen)
CONTACT
Computing 2,
15 Computing Drive,
National University of Singapore,
Singapore, 117418
Email: xianglin[at]u[dot]nus[dot]edu
© 2022 YANG Xianglin | Powered by Skeleton and Jiarui Gan's template | Updated 2022-05-16