Ruibo Tu
POSTDOC
Researcher
About me
I am a post doc in TMH, KTH working with Gustav Henter. During my PhD studies, I worked on causality and machine learning, supervised by Prof. Hedvig Kjellström at KTH and co-supervised by Dr. Cheng Zhang at Microsoft Research Cambridge and Prof. Kun Zhang at Carnegie Mellon University.
Recent Publications
|
Refereed Conference Papers |
|---|
|
Causality for Tabular Data Synthesis: A High-Order Structure Causal Benchmark. Under review. Ruibo Tu, Zineb Senane, Lele Cao, Cheng Zhang, Hedvig Kjellström, Gustav Eje Henter. |
|
Optimal Transport for Causal Discovery ICLR 2022 (accepted as spotlight: 5.19%).Ruibo Tu, Kun Zhang, Hedvig Kjellström, Cheng Zhang ( Paper , Poster , sldies, code ) |
|
Causal discovery from conditionally stationary time-series. ICRL workshop of UAI.Carles Balsells Rodas,Ruibo Tu , Yingzhen Li, Hedvig Kjellström. |
|
How Do Fair Decisions Fare in Long-term Qualification? NeurIPS 2020.Xueru Zhang *,Ruibo Tu *, Yang Liu, Mingyan Liu, Hedvig Kjellström, Kun Zhang, Cheng Zhang (*: joint first authors) ( Paper , Poster , Code , Video ) |
|
Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation NeurIPS 2019.Ruibo Tu, Kun Zhang, Bo Christer Bertilson, Hedvig Kjellström, Cheng Zhang ( Paper , Poster , Video , Code ) |
|
Causal Discovery in the Presence of Missing Data AISTATS 2019.Ruibo Tu *, Cheng Zhang *, Paul Ackermann, Karthika Mohan, Hedvig Kjellström, Kun Zhang * ( Paper , Poster , Code ) (*: equal contribution) |
|
Simultaneous Measurement Imputation and Outcome Prediction for Achilles Tendon Rupture Rehabilitation MLHC 2019.Charles Hamesse *,Ruibo Tu * , Paul Ackermann, Hedvig Kjellström, Cheng Zhang (Paper , Poster ) |
Professional Experience
Applied scientist internship in Amazon research (causality lab), Tuebingen (Oct. 2021 - Jan. 2022)
Visiting researcher in Microsoft Research Cambridge (Feb. 2019 - April.2019)
Academic Services
Peer-Review Conference Reviewer: NeurIPS, ICML, UAI, AISTATS, ICLR, CLeaR, IJCAI, MLHC
Journal Reviewer: Pattern Recognition, Transactionson Machine Learning Research
Courses
Deep Learning in Data Science (DD2424), assistant | Course web
Probabilistic Graphical Models (DD2420), teacher | Course web