Tara V Anand

Causal Inference for Healthcare. PhD Student in Biomedical Informatics @Columbia. Previously Computer Science @BarnardCollege (‘20).

[Tara V Anand @taravanand]

Looking forward to presenting our paper "Causal Discovery over Clusters of Variables in Markovian Systems" this week at NeurIPS. Come talk with me at my poster (#2601) on Thursday from 4:30pm-7:30pm.

[Elias Bareinboim @eliasbareinboim]

5/8 “Causal Discovery over Clusters of Variables in Markovian Systems” (joint w/ @taravanand, @adelehr, Jin Tian, Gregory Hripcsak)
Thu, 7:30 pm (#2601)
Link: https://t.co/dpqydz3JzE

We study causal discovery when variables come grouped into clusters, a setting where standard algorithms often fail due to ambiguous independence patterns. We characterize the Markov equivalence classes of cluster DAGs (C-DAGs) and introduce CLOC, the first sound and complete constraint-based algorithm for discovering causal structure directly at the cluster level.

[Columbia DBMI @ColumbiaDBMI]

Proud mentor George Hripcsak joins his two #AMIA2024 honorees, @taravanand and @Z_Linying!

[Columbia DBMI @ColumbiaDBMI]

🎉🎉 Congratulations to our PhD trainee Tara Anand (@taravanand) on earning 2nd place in the #AMIA2024 Student Paper Competition!

Title: Leveraging Cluster Causal Diagrams for Determining Causal Effects in Medicine.

Congrats Tara! 👏👏 @ColumbiaPS @Columbia @amiainformatics

[Columbia DBMI @ColumbiaDBMI]

A full #AMIA2024 day for DBMI begins at 8:30 am as @taravanand presents "Leveraging Cluster Causal Diagrams for Determining Causal Effects in Medicine" during S21: Machine Learning Methods – Send Reinforcements (Franciscan A). @AMIAinformatics

[Columbia DBMI @ColumbiaDBMI]

Conferences like #MLHC2023 don't work without some amazing volunteers! Thank you to some of our own from DBMI! @harryreyesnieva @taravanand Young Sang Choi @mlforhc

[Tara V Anand @taravanand]

Featuring the one and only @backtoyours (check out their new album, you won’t be disappointed!)

[Tara V Anand @taravanand]

https://t.co/EypToID6rZ

[Tara V Anand @taravanand]

@yudapearl @AJAveritt @eliasbareinboim 1/C-DAGs address the problem of when only partial knowledge is available, such that a full causal diagram cannot be specified (particularly useful in high-dimensional domains, like medicine). Consider an example where the following edges are known:X→Y; Z1→X; Z1↔X; Z2→Y; Z2↔Y

[Tara V Anand @taravanand]

@yudapearl @AJAveritt @eliasbareinboim 6/ Interestingly, in application, conditional ignorability is often assumed. In fact, the above example may apply, such that this assumption is contradicted. C-DAGs help clarify where more knowledge may be necessary and allow for assumptions more nuanced than ignorability.

[Tara V Anand @taravanand]

@yudapearl @AJAveritt @eliasbareinboim 5/ Here, P(Y|do(X)) is non-ID because the effect is non-ID in a compatible causal diagram. The C-DAG motivates model refinement. More knowledge is required, perhaps to determine a mediator between X and Y for use of front-door adjustment, or to break up clusters another way.

[Tara V Anand @taravanand]

@yudapearl @AJAveritt Work can be found here! (https://t.co/cUytyZ5655)
Highlighting my recent paper with @eliasbareinboim on effect identification in C-DAGS (https://t.co/EypToID6rZ) @ AAAI 2023. I’m broadly working on ways to make existing theory more usable for applications in medicine

[Amelia J. Averitt, MPH MA PhD @AJAveritt]

My very talented TA, @taravanand, gave our second #causalinference lecture of the semester. She complemented our first lecture on #counterfactuals by covering @yudapearl’s #docalculus. Check out her amazing research in this area! #CUDBMIMLHC

[Tara V Anand @taravanand]

@oliverbdw4 @Adriennepichon1 @pooja_m_desai @kayla_schiffer @laseplov @courtneyjayned @rendocrinology @apara_kashyap1

[Tara V Anand @taravanand]

Thank you to everyone who came to the Justice Informatics Workshop at #AMIA2022! So many rich conversations on how informatics can be used to advance justice and how to protect against its abuse for injustice! Grateful for my workshop co-organizers for making this happen

[Columbia DBMI @ColumbiaDBMI]

Greetings from Tuesday's #AMIA2022 Poster Session! @taravanand

[Columbia DBMI @ColumbiaDBMI]

It's #AMIA2022 Poster Time! DBMI will be represented by Betina Idnay, Lauren Richter, Tara Anand (@taravanand) and Ahmed Elhussein during Poster Session 2 at 5 pm in Columbia Hall. Poster topics are shared on the graphics below ... hope you give them a visit!

[Columbia DBMI @ColumbiaDBMI]

@Tiff_callahan @taravanand @Z_Linying Hello to the Hripcsak Lab! #AMIA2022 @Tiff_callahan @taravanand @Z_Linying