iiinova — where your digital self keeps evolving

SHIMIZU Shohei @sshimizu2006.bsky.social · 24/09/2026

CLeaR 2027 welcomes submissions on causal learning and reasoning! Karthika and I are serving as Program Chairs, and we’d love to see your work. Submission deadline: November 16, 2026 (AoE) www.cclear.cc/2027

cclear.cc

CLeaR

021

SHIMIZU Shohei @sshimizu2006.bsky.social · 20/09/2026

Causal Newton Optimization: Online Calibration with Iterative Local Linear Modeling and Newton Updates Daigo Fujiwara, Tomonori Izumitani, Shohei Shimizu www.ijcai.org/proceedings/...

ijcai.org

Causal Newton Optimization: Online Calibration with Iterative Local Linear Modeling and Newton Updates | IJCAI

Electronic proceedings of IJCAI 2026

010

Reposted by SHIMIZU Shohei

SHIMIZU Shohei @sshimizu2006.bsky.social · 05/06/2026

Submissions are welcome! We look forward to your contributions on causal inference and causal discovery.

052

SHIMIZU Shohei @sshimizu2006.bsky.social · 21/08/2026

Toward Causal Scientific Discovery with AI RIKEN Mathematics & AI Symposium speakerdeck.com/sshimizu2006...

speakerdeck.com

Toward Causal Scientific Discovery with AI

RIKEN Mathematics & AI Symposium

021

SHIMIZU Shohei @sshimizu2006.bsky.social · 08/08/2026

From Prediction to Understanding: Causal Discovery for Data Science and AI Applications EcoSta2026 speakerdeck.com/sshimizu2006... #speakerdeck

speakerdeck.com

From Prediction to Understanding: Causal Discoveryfor Data Science and AI Applications

EcoSta2026

011

SHIMIZU Shohei @sshimizu2006.bsky.social · 06/08/2026

因果探索の発展と展望統計サマーセミナー2026 speakerdeck.com/sshimizu2006...

speakerdeck.com

因果探索の発展と展望

統計サマーセミナー2026

000

SHIMIZU Shohei @sshimizu2006.bsky.social · 28/06/2026

Demographic influences on investment: A causal discovery study in Japan Yi Jiang, Shohei Shimizu, Michio Yamamoto, Array, 2026 doi.org/10.1016/j.ar...

doi.org

Redirecting

010

SHIMIZU Shohei @sshimizu2006.bsky.social · 05/06/2026

Submissions are welcome! We look forward to your contributions on causal inference and causal discovery.

052

Reposted by SHIMIZU Shohei

RD PascualMarqui @pascualmarqui.bsky.social · 01/05/2026

Causal Discovery of Synchronous Neural Oscillations based on Jacobian-informed VAR-LiNGAM Hiroshi Yokoyama, Ryosuke Takeuchi, Shohei Shimizu bioRxiv 2026.04.28.721377; doi: doi.org/10.64898/202...

The primary objective of system neuroscience is to understand the functional mapping and its causation in the dynamics of the brain network. Some experimental and methodological studies suggest that functional modularity and its hierarchical information processing in the brain network are crucial to understanding the functional role of task-specific or state-specific information flow in the brain. However, because most of the established techniques for detecting effective network structures in the neuroscience research field are strongly based on the ``Granger causality'' perspective, existing causal discovery methods specified for brain network analysis cannot identify the causal hierarchy in the modular network in the brain due to spurious correlation issues and indistinguishability of causal direction under the Gaussianity of observational noise in a linear system. To address the issues, we developed a causal discovery method for synchronous neural dynamics, called the Jacobian-informed linear non-Gaussian acyclic model, ``j-VAR-LiNGAM'', by incorporating the information of the Jacobian matrix determined from a phase-coupled oscillator model estimated from observed neural data into the VAR-LiNGAM algorithms. The method was validated by showing that it could extract causal ordering in both synthetic data and empirical neural observed data. Moreover, by analyzing the observed neural oscillatory signals obtained from mice and humans, we confirmed that our method identified causally hierarchical structures in the brain, which aligned with the neurophysiological interpretations. These findings suggested that our proposed method can reveal the neural basis of hierarchical information processing in the brain network.

102

Reposted by SHIMIZU Shohei

Sara Magliacane hiring PhDs at UvA @smaglia.bsky.social · 09/04/2026

11 more days to apply to these positions! Come join us in Amsterdam to work on #causality #XAI and #AI #safety

053

SHIMIZU Shohei @sshimizu2006.bsky.social · 21/03/2026

Statistical Causal Discovery in Developing Adverse Outcome Pathway (AOP) Kyoshiro Hiki , Thong Pham , Michio Yamamoto , Takehiko I Hayashi , Shohei Shimizu Environmental Toxicology and Chemistry, 2026 doi.org/10.1093/etoj...

academic.oup.com

Statistical Causal Discovery in Developing Adverse Outcome Pathway (AOP)

Abstract. Statistical causal discovery (SCD) has the potential to advance the development and evaluation of Adverse Outcome Pathways (AOPs) by inferring ca

053

Reposted by SHIMIZU Shohei

uai2026 @auai.org · 27/01/2026

Submissions are now open for UAI 2026 in Amsterdam. Deadline is February 25th, 2026 (23:59 AoE). Call for papers here: www.auai.org/uai2026/call...

auai.org

Uncertainty in Artificial Intelligence

0118

Reposted by SHIMIZU Shohei

Sara Magliacane hiring PhDs at UvA @smaglia.bsky.social · 27/01/2026

Best conference with the best people and in the best place 😎 😜 Also the submission deadline is conveniently one month later than #ICML2026, just in case you needed it 😅

0154

Reposted by SHIMIZU Shohei

TMLR Published Papers @tmlr-pub.bsky.social · 20/11/2025

Differentiable Causal Discovery of Linear Non-Gaussian Acyclic Models Under Unmeasured Confounding Yoshimitsu Morinishi, Shohei Shimizu Action editor: Sergey Plis openreview.net/forum?id=HR7MFlW73I #causal #models #generalized

041

Reposted by SHIMIZU Shohei

uai2026 @auai.org · 15/01/2026

What’s going on behind the scenes of #UAI2026? 👀 Meet the wonderful people working hard for this year’s edition ❤️ 👉 www.auai.org/uai2026/orga...

074

SHIMIZU Shohei @sshimizu2006.bsky.social · 17/12/2025

[CFP] Recent Advances in Causal Inference, Causal Discovery, and Applications Coordinating Editors: Shohei Shimizu Manabu Kuroki Aapo Hyvärinen Submission Due Date: February 1, 2027 Intended Publication Date: September 1, 2027 link.springer.com/journal/4208...

link.springer.com

Japanese Journal of Statistics and Data Science

Japanese Journal of Statistics and Data Science is an international forum publishing original articles in statistical theories and diverse fields related to ...

041

Reposted by SHIMIZU Shohei

uai2026 @auai.org · 16/12/2025

Ready to bike along the canals? 🚲 The 42nd Conference on Uncertainty in AI will be in Amsterdam, August 17-21! 🇳🇱 CfP is out 👉 auai.org/uai2026/call... 🚨 Feb 25: Paper submission 🗣️ Apr 23–May 2: rebuttal period 🎉💀 Jun 1: Author notification #UAI2026 #ML #stats #learning #reasoning #uncertainty #AI

02614

Reposted by SHIMIZU Shohei

Dan Malinsky @danielmalinsky.bsky.social · 16/12/2025

Excited to be serving as Program co-Chair of UAI 2026 with Ema Perkovic! We are busy working on facilitating an excellent program. In my unbiased opinion UAI is an ideal venue at the intersection of stats & CS: good size, good science, good vibes. Please submit your work!

082

Reposted by SHIMIZU Shohei

Dan Malinsky @danielmalinsky.bsky.social · 16/12/2025

Proposed* official UAI2026 conference taglines: "UAI2026: gotta be crazy to be certain about AI these days" "UAI: 2 uncertain 2 AI" "I went to UAI2026 and all I got was this lousy uncertainty" Vote for your fav or propose your own! www.auai.org/uai2026/ (*by me, under consideration by no one)

101

Reposted by SHIMIZU Shohei

Sara Magliacane hiring PhDs at UvA @smaglia.bsky.social · 16/12/2025

A fantastic opportunity to join us in #Amsterdam for some hardcore #uncertainty in #AI 🦾🚲🌷✖️✖️✖️ #causality #tractable #probabilistic #models #neurosymbolic #imprecise #probabilities #statistical #methods and more

22410

SHIMIZU Shohei @sshimizu2006.bsky.social · 08/11/2025

Released code for TS-LSNM github.com/gkikuchi/TSL... Kikuchi & Shimizu (2023) Structure Learning for Groups of Variables in Nonlinear Time-series Data with Location-scale Noise In Proc. 2023 Causal Analysis Workshop Series, PMLR

github.com

GitHub - gkikuchi/TSLSNM: A python implementation of Time-Series Location-Scale Noise Model

A python implementation of Time-Series Location-Scale Noise Model - gkikuchi/TSLSNM

050

Reposted by SHIMIZU Shohei

Alexander Marx @a-marx.bsky.social · 05/11/2025

I am excited to share that I am looking for a #postdoc with an interest in causal machine learning to join my lab at TU Dortmund University and RC Trust. #hiring #causality #ML #AI 📅 03.12.25 Group: rc-trust.ai/groups/causa... Details: tinyurl.com/4622p6at

rc-trust.ai

Causality

063

SHIMIZU Shohei @sshimizu2006.bsky.social · 29/09/2025

少ないコミュ力が尽きたので、回復日が必要

100

Reposted by SHIMIZU Shohei

Moritz Schauer @mschauer.bsky.social · 17/09/2025

Very nice by Jun Otsuka @junotk.bsky.social and Hayato Saigo: link.springer.com/article/10.1... about causal interventions/do calculus via string diagram surgery

092

SHIMIZU Shohei @sshimizu2006.bsky.social · 26/07/2025

生命科学でもどんどん因果探索を doi.org/10.1038/s415...

010

Reposted by SHIMIZU Shohei

Jun Otsuka @junotk.bsky.social · 25/07/2025

All titles of Cambridge Elements in the Philosophy of Biology, including mine The Role of Mathematics in Evolutionary Theory, are downloadable for free till the 25th. www.cambridge.org/core/element...

cambridge.org

The Role of Mathematics in Evolutionary Theory

Cambridge Core - Philosophy of Science - The Role of Mathematics in Evolutionary Theory

0113

SHIMIZU Shohei @sshimizu2006.bsky.social · 16/07/2025

材料で因果探索とかどんと盛り上がったりしないかしらと思いながら読んだ (聞いた): Causal Analysis of Factors for Li Ionic Conductivity in Olivine-Type LiMXO4 Materials Using LiNGAM | The Journal of Physical Chemistry C pubs.acs.org/doi/10.1021/...

pubs.acs.org

Causal Analysis of Factors for Li Ionic Conductivity in Olivine-Type LiMXO4 Materials Using LiNGAM

All-solid-state batteries are increasingly examined to improve the safety of lithium-ion batteries. Considerable efforts are being made to develop solid electrolyte materials with high ionic conductiv...

130

Reposted by SHIMIZU Shohei

TMLR Published Papers @tmlr-pub.bsky.social · 19/06/2025

Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach MASAYUKI TAKAYAMA, Tadahisa OKUDA, Thong Pham et al. Action editor: Fabio Stella openreview.net/forum?id=Reh1S8rxfh #causal #knowledge #inference

032

Reposted by SHIMIZU Shohei

uai2026 @auai.org · 26/06/2025

Are you student 🎓 attending #UAI2025? Apply for a ✨ scholarship for free or reduced conference registration ✨! Don't miss out! Deadline is July 2nd, AoE. Apply here: forms.gle/CQG1BLy2Mvd3...

forms.gle

UAI 2025 Application for Student Scholarships

Applications for scholarships for students attending UAI 2025 held in Rio de Janeiro, Brazil. Key Dates: Application Deadline: July 2nd, 23:59 AoE Notification of Acceptance: July 10th

035

Reposted by SHIMIZU Shohei

uai2026 @auai.org · 26/06/2025

ready to Rio 🇧🇷? Here 👉 www.auai.org/uai2025/loca... are some useful tips on: - find an accommodation 🏡🌴 - travel from the airport ✈️🚗 - print your posters 📊 - and more!

auai.org

Uncertainty in Artificial Intelligence

0104

SHIMIZU Shohei @sshimizu2006.bsky.social · 06/06/2025

千中から阪大へのバスがむっちゃ減っててびっくりした

020

Reposted by SHIMIZU Shohei

uai2026 @auai.org · 22/05/2025

053

Reposted by SHIMIZU Shohei

Sara Magliacane hiring PhDs at UvA @smaglia.bsky.social · 12/05/2025

New PhD position at the University of Amsterdam in @amlab.bsky.social on learning concepts with theoretical guarantees using #causality and #RL with me, Frans Oliehoek (TU Delft) and Herke van Hoof 💥 Deadline: 15 June werkenbij.uva.nl/en/vacancies...

werkenbij.uva.nl

Vacancy — PhD Position on Learning Concepts with Theoretical Guarantees Using Causality and RL

Are you interested in improving the interpretability, robustness and safety of current AI systems? If the answer is yes, please continue reading!

0218

Reposted by SHIMIZU Shohei

Sara Magliacane hiring PhDs at UvA @smaglia.bsky.social · 17/04/2025

Exciting new PhD position at Utrecht University on the #causal effects of communication in #multi-agent #RL with Shihan Wang, Mehdi Dastani and me 🎉 This is part of www.hybrid-intelligence-centre.nl, which aims at combining human and machine intelligence. Deadline 20 May www.uu.nl/en/organisat...

uu.nl

PhD Position on Causal Effects of Communication in MARL

Join us to work on the causal effects of communication in multi-agent reinforcement learning (MARL).

1144