Junjie Yang
About Me
Since July 2025, I have been a postdoctoral researcher at LPSM, Sorbonne University in collaboration with Califrais, working with Adeline Fermanian(Califrais), Claire Boyer(Paris-Saclay University) and Gérard Biau (Sorbonne University). I work currently on time series forecasting.
Before that, I obtained my PhD from Télécom Paris, IP Paris, under the supervision of Florence d’Alché-Buc and Matthieu Labeau. My research focused on structured prediction, with applications in graph prediction. You can find my PhD thesis here.
Previously I earned my Diplôme d’Ingénieur from Ecole d’ingénieurs Paris SJTU and a Master’s degree from Shanghai Jiao Tong University.
Research Interests
I have a broad interest in Machine Learning and am currently focusing on:
- Time Series Forecasting
- Structure Prediction
- Optimal Transport
- Kernel Methods
- Deep Learning
- Natural Language Processing
News
Publications
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Preprint
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NeurIPS 2024
The Thirty-Eighth Annual Conference on Neural Information Processing Systems -
ECML PKDD 2024
Joint European Conference on Machine Learning and Knowledge Discovery in Databases -
AAAI-21 SDU Workshop
The AAAI-21 Workshop on Scientific Document Understanding -
AAAI-21
The Thirty-Fifth AAAI Conference on Artificial Intelligence
TMLR
Teaching
During my PhD (2021-), I have been a teaching assistant at Télécom Paris for the following courses:
- Machine Learning (SD-TSIA210)
- Structured Data: Learning and Prediction (MAP670I)
- Natural Language Processing (IA312)
- Machine Learning for Text Mining (SD-TSIA214)
- Introduction to Practical Machine Learning : An Algorithmic Approach (SI221-B)
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