@janadoppa

Huie-Rogers Endowed Chair Professor of CS @WSUPullman; AI, ML, Computing Systems, AI to Accelerate Science and Engineering

 Pullman, WA
eecs.wsu.edu/~jana
Joined June 2021
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📢 Come to our @NeurIPSConf tutorial on Advances in Bayesian Optimization Dec 5, Mon, 11am to 1:30pm PST bayesopt-tutorial.github.io/ Speakers: @VGAglietti, Jake Gardner, me Panelists: @StefanieJegelka, @jmhernandez233, Roman Garnett, @eytan, @syrineblk Post your questions below.
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Alan Fern@AlanPaulFern1Sep 17
I like to think that eventually an AI agent can decide how an object should move, and the right robots will make it happen. My student Bikram Pandit is making progress toward this with teams of humanoids: decmht.github.io/ Can’t wait to see what we can do with hands.
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Devendra Chaplot
@dchaplotJul 17
The mark of a great professor isn’t just the papers they publish. It’s the people they help build.
Russ Salakhutdinov
@rsalakhuJul 17
I’ve been asked several times whether Zhilin Yang, the founder of @Kimi_Moonshot was my PhD student. The answer is yes and he is absolutely brilliant. But I’ve been incredibly fortunate to work with so many outstanding PhD students over the years. So I thought I’d brag a little about them and their career paths (of course there are also many MSc and undergraduate students, sorry if I missed anyone): Founders / Founding Team Members Devendra Chaplot @dchaplot PhD, Founding Member Thinking Machines / Mistral Zhilin Yang PhD, Founder & CEO, Moonshot AI Jimmy Ba @jimmybajimmyba MSc/PhD, Co-founder xAI Hubert Tsai PhD, Co-founder Spuree, Apple Nitish Srivastava @nitishsr PhD, Co-founder Perceptual Machines; Co-founder Vayu Robotics Charlie Tang PhD, Co-founder Perceptual Machines, DE Shaw. Professors Paul Liang @pliang279 PhD, MIT Ben Eysenbach @ben_eysenbach PhD, Princeton University Ruosong Wang @RuosongW PhD, Peking University Bhuwan Dhingra @bhuwandhingra PhD, Duke University Roger Grosse @RogerGrosse Postdoc, University of Toronto Alexander Schwing Postdoc, UIUC Research Scientists Shuyan Zhou @shuyanzh36, Postdoc, Meta Superintelligence Lab Tiffany Min @SoYeonTiffMin PhD, Microsoft AI Murtaza Dalal @mihdalal PhD, Tesla AI Minji Yoon @MinjiYoon90 , PhD, Microsoft AI Shrimai Prabhumoye PhD, NVIDIA AI, Mistral Haitian Sun @sun_haitian PhD, Google DeepMind Emilio Parisotto PhD, Google DeepMind Lisa Lee PhD @rl_agent, Google DeepMind Manzil Zaheer @ManzilZaheer PhD, Google DeepMind Jamie Kiros PhD, Google Brain, OpenAI Yuri Burda PhD, OpenAI, Anthropic Cody Severinski PhD, Amazon
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Sergey Levine
@svlevineJul 10
Starting now in ASEM Ballroom 203 after a bit of AV troubles :) see you there! The talk will cover how to build up a general framework for data-driven decision making!
Sergey Levine
@svlevineJul 10
This morning at ICML 2026, I'll be speaking at the Workshop on Decision-Making from Offline Datasets. Come to ASEM Ballroom 203 at 8:15 am KST! I'll talk about foundations of data-driven decision making, from design via model-based optimization to offline RL
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Come to our @icmlconf workshop tomorrow! Location: ASEM Ballroom 203 Posters: Hall A Schedule: decision-making-offline2onli… The program consists of 4 Invited talks: @svlevine Sergey Levine, Aarti Singh, Clara Wong-Fannjiang, and Wen Sun 9 Orals 15 Spotlights 140 posters #ICML2026

Schedule | ICML 2026 Workshop

decision-making-offline2online-icml2026.github.io
Jana Doppa@janadoppaApr 3
📢Call for Papers: Decision-Making from Offline Datasets to Online Adaptation: Black-Box Optimization to Reinforcement Learning @icmlconf 2026 Website: decision-making-offline2onli… OpenReview submission site: openreview.net/group?id=ICML… Submission deadline: May 5th, AOE.
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Wonderful team of organizers: @deshwal_aryan @HarukaKiyohara_ @willieneis @htnghia1187 @syrineblk @thanhnguyentang @janadoppa
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Ben Recht@beenwrektJun 23
My teacher and friend Dimitri Bertsekas passed away earlier this month. I wrote about his broad contributions to the field of numerical optimization and his deep impact on my writing and research. argmin.net/p/a-tribute-to-di…

A Tribute to Dimitri Bertsekas

My teacher and friend Dimitri Bertsekas passed away earlier this month.

argmin.net
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Congratulations to Kaiming and ResNet. ResNet is 10 years old but Kaiming remains as young and brilliant as ever! We are deeply grateful for you and for everything you have done for computer vision, Kaiming (though he refuses to be on social media)
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Avi Wigderson is the only person in history to have won both a Turing Award (computer science) and Abel Prize (math). I interviewed him all about his field. We discussed: • His intuition on a proof of P vs NP • Why we use SAT solvers for most NP problems • Zero knowledge proofs and their impact • Quantum computation and implications • Math and computer science's relationship Where to watch: • YouTube: youtu.be/5GUcvSAJcJw • Spotify: open.spotify.com/episode/4JZ… • Apple Podcasts: podcasts.apple.com/us/podcas… • Transcript: developing.dev/p/turing-awar… Thank you to this episode's sponsors for supporting my work: • WorkOS: makes your app Enterprise Ready with easy to use APIs to add SSO, SCIM, RBAC, and more in just a few lines of code, check them out at workos.com/ Timestamps: 00:00 - Intro 01:08 - P vs NP 14:51 - What if you relaxed correctness 25:38 - Why NP complete problems are equivalent 30:33 - Space vs time complexity 43:06 - Why people use SAT solvers 45:53 - Randomness is a resource 55:48 - Randomness depends on computational power 01:21:20 - Zero knowledge proofs and their significance 01:38:30 - Quantum computation and why it matters 01:56:24 - Math vs computer science 02:08:16 - Major breakthroughs and his experience 02:12:31 - Advice for his younger self 02:14:48 - Outro
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Attention @arxiv authors: Our Code of Conduct states that by signing your name as an author of a paper, each author takes full responsibility for all its contents, irrespective of how the contents were generated. 1/
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Excited to see my student’s work on Flux Matching out. It turns out you can learn a much broader class of vector fields with the data distribution as stationary (not just the score). This lets you enforce useful properties like fast mixing, and it already works on high-dimensional image datasets!
Peter Pao-Huang@peterpaohuangMay 12
Introducing Flux Matching, a generative modeling paradigm that generalizes diffusion models to vector fields that need not be the score function. Enables structural priors in the dynamics, faster sampling, interpretable generation, and more! w/ @StefanoErmon @Xiaojie_Qiu 🧵⤵️
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Ten years in academia and the best part has not been what many value most ie freedom to pursue your ideas. It’s experiencing your students grow and go on to incredible trajectories. What I’ve come to know about myself is that I value permanence, presence, and people. And for all the illusions that institutions, titles, awards etc offer, none at all come close to this: watching a human absorb, even in tiny amounts, the care and effort you’ve put into trying your best to just be there for them.
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We have extended the paper submission deadline for our @icmlconf workshop to May 7th AOE due to NeurIPS paper deadline. @deshwal_aryan @HarukaKiyohara_ @syrineblk @willieneis @htnghia1187 @thanhnguyentang
Jana Doppa@janadoppaApr 3
📢Call for Papers: Decision-Making from Offline Datasets to Online Adaptation: Black-Box Optimization to Reinforcement Learning @icmlconf 2026 Website: decision-making-offline2onli… OpenReview submission site: openreview.net/group?id=ICML… Submission deadline: May 5th, AOE.
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Cindy Zhang@cindyzhangxApr 21
I'm excited to be at #ICLR2026 this week presenting joint work with Elif Ertekin, Peter Orbanz, and @ryan_p_adams on "A Single Architecture for Representing Invariance Under Any Space Group." (1/3)
Poster describing the construction of a ML model architecture that enforces exact invariance to crystallographic symmetries using symmetry-adapted Fourier bases.

ALT Poster describing the construction of a ML model architecture that enforces exact invariance to crystallographic symmetries using symmetry-adapted Fourier bases.

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I have a postdoc position available to work on machine-learning guided antibiotic discovery. Application deadline 15 May 2026. jobs.cam.ac.uk/job/55258/
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Conformal Margin Risk Minimization: An Envelope Framework for Robust Learning under Label Noise ift.tt/4cxoMsI

Conformal Margin Risk Minimization: An Envelope Framework for...

Most methods for learning with noisy labels require privileged knowledge such as noise transition matrices, clean subsets or pretrained feature extractors, resources typically unavailable when...

arxiv.org
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📢Call for Papers: Decision-Making from Offline Datasets to Online Adaptation: Black-Box Optimization to Reinforcement Learning @icmlconf 2026 Website: decision-making-offline2onli… OpenReview submission site: openreview.net/group?id=ICML… Submission deadline: May 5th, AOE.
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The workshop will highlight both foundational advances and real-world applications in domains where online experimentation is costly, unsafe, or infeasible, including scientific discovery, engineering design, healthcare, education, recommender systems, and beyond.
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We have a great lineup of invited speakers: Jake Gardner Wen Sun Clara Wong-Fannjiang Aarti Singh Eytan Bakshy @eytan Sergey Levine @svlevine Great team of organizers: @deshwal_aryan @HarukaKiyohara_ @willieneis @htnghia1187 @syrineblk Thanh Nguyen-Tang @janadoppa
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Alan Fern@AlanPaulFern1Feb 13
We’re hiring! Oregon State University is recruiting a Tenure-Track Faculty Position in Robotics. jobs.oregonstate.edu/posting… Hard to beat the Pacific Northwest + excellent robotics graduate program combo.
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