Sifan Wu (吴思凡)
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About
I am a forth-year PhD student at Mila - Québec AI Institute, University of Montreal. I am furtunate to be supervised by Prof. Bang Liu. Previously, I received M.Eng and B.Eng degrees in Computer Science from Tsinghua University in 2021 and from Tongji University in 2018, respectively.
I am dedicated to developing reliable LLM. My research covers multimodal large language models, neural symbolic reasoning and AI4Science.
News
- [Jul. 2024] One paper about ai4healthcare was accepted by PAKDD 2024!
- [Jul. 2024] One paper about multimodal LLM was accepted by ECCV 2024!
- [Jun. 2024] Start Applied Scientist intern in Microsoft Turing, Redmond!
- [Dec. 2023] One paper about CAD LLM was accepted by NeurIPS 2023 workshop!
Research Experiences
- Microsoft Turing, Applied Scientist Intern. June 2024 - Sep. 2024, Redmond, US
- Autodesk AI Lab, Research Intern. May 2023 - Sep. 2023, Toronto, Canada
- Tencent Jarvis Lab, Research Intern. May. 2021 - Dec. 2021, Shenzhen, China
- Microsoft Bing, Machine Learning Engineer Intern. Jul. 2020 - Sep. 2020, Beijing, China
- Tencent AI Lab, Research Intern. Aug. 2019 - June. 2020, Shenzhen, China
Publications & Preprints
(* denotes equal contributions)CadVLM: Bridging Language and Vision in the Generation of Parametric CAD Sketches.
Sifan Wu, Amir Khasahmadi, Mor Katz, Pradeep Kumar Jayaraman, Yewen Pu, Karl Willis, Bang Liu.
ECCV 2024.
CAD-LLM: Large Language Model for CAD Generation.
Sifan Wu, Amir Khasahmadi, Mor Katz, Pradeep Kumar Jayaraman, Yewen Pu, Karl Willis, Bang Liu.
NeurIPS 2023 Workshop. [Paper]
Identify Event Causality with Knowledge and Analogy.
Sifan Wu, Ruihui Zhao, Yefeng Zheng, Jian Pei, Bang Liu .
AAAI 2023. [Paper]
Adversarial Sparse Transformer for Time Series Forecasting.
Sifan Wu, Xi Xiao, Qianggang Ding, Peilin Zhao, Ying Wei, Junzhou Huang.
NeurIPS 2020. [Paper]
Improving Clinical Note Generation from Complex Doctor-Patient Conversation.
Yizhan Li, Sifan Wu,Christopher Smith, Thomas Lo, Bang Liu.
PAKDD 2024. [Paper]
Knowledge Refinery: Learning from Decoupled Label.
Qianggang Ding, Sifan Wu, Tao Dai, Hao Sun, Jiadong Guo, Zhang-Hua Fu, Shutao Xia.
AAAI 2021. [Paper]
Hierarchical Multi-Scale Gaussian Transformer for Stock Movement Prediction.
Qianggang Ding *, Sifan Wu *, Hao Sun, Jiadong Guo, Jian Guo.
IJCAI 2020. [Paper]
ConvDroid: Lightweight Neural Network based Andoird Malware Detection.
Sifan Wu, Xi Xiao.
ICONIP 2019. [Paper]
Awards
- Outstanding Graduate of the department of Computer Science, Tsinghua University, 2021.
- Outstanding Students Scholarship, Tongji University. 2015 & 2016.