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Ruibo Tu

Profile picture of Ruibo Tu

POSTDOC

Details

Address
LINDSTEDTSVÄGEN 24

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

DBLP

Refereed Conference Papers

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