machine learning researcher • organizer @afciworkshop
Joined September 2018
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Awa Dieng retweeted
Avoiding common failures in AI for health and medicine
A reminder that benchmark performance is not deployment performance.
The paper focuses on erroneous outputs, unjustified performance gaps, deployment-time degradation, monitoring, and governance.
cell.com/cell/fulltext/S0092…
Awa Dieng retweeted
We’re coming out of stealth with some exciting AI-optimized compute results.
Some highlights:
1) Works on industrial-grade and consumer-grade GPUs.
2) It can optimize different compute layers, from the kernels to tokens, for higher tokens-per-watt on your GPU.
The entire industry is racing to make AI cheaper. Most people assume the answer is better chips or bigger GPU clusters. However, while the industry is buying its next 2× when there's a 1.78× speedup is sitting in the software.
We've been hard at work @unifiedsciences, building an autonomous optimization engine toward radically more efficient compute.
Today I'm very happy to share some early results where our unified engine:
1) wrote faster GEMM kernels for cuBLAS (up to 1.78x faster)
2) made an efficient AI model 6x smaller and 5x faster without any quality loss
3) optimized diverse everyday AI workloads on a consumer GPU!
Awa Dieng retweeted
Congratulations to AI2050 Early Career Fellow @adjiboussodieng on receiving an NSF CAREER Award for her research developing AI methods for materials discovery, with applications ranging from next-generation medicines to improved solar cells.
Read more: cs.princeton.edu/news/dieng-…
Awa Dieng retweeted
Thank you to the United States National Science Foundation (@NSF) for believing in the research we are pioneering @Vertaix_: a new paradigm for #AI centered on discovery.
Current AI runs into a problem I'll call 'mode collapse' which prevents it from genuine scientific discovery. My group will continue to work on a new AI paradigm called "Investigative Intelligence" that will enable novel discoveries by mitigating mode collapse. This work is based on the work we've been doing around diversity, which I believe to be the right primitive for discovery.
This award would not have been possible without the amazing grad students, postdocs, and collaborators I have had the chance to work with. Thank you all🧡 #VendiScore #AI #II #Discovery #Science
.@adjiboussodieng has won a CAREER award from the @NSF, a top honor for early career faculty!
Dieng is working to establish a new paradigm for AI, transforming it into an engine for scientific exploration that can uncover revolutionary new materials.
bit.ly/4udRPRK
ALT Adji Bousso Dieng
Awa Dieng retweeted
🚨 CFP is LIVE! 🚨
DAIH 2026 Workshop @ COLM — LLM/VLM Deployment Opportunities and Risks in Healthcare 📍 San Francisco | 📅 Oct 9, 2026
We want your research papers & real-world deployment case reports!
⏰ Deadline: June 23, 2026
🔗 daih2026.github.io/index.htm… (1/X)
Huge thanks to everyone who participated in #AFAA2026 for the insightful talks and engaging discussions!
Especial shoutout to @zeyu1tang and @prakhar_24 for your incredible work and leading the team!
Follow us at @afciworkshop for more updates soon!
That’s a wrap for #AFAA2026!!! 🎉 Thank you to all the authors, attendees, roundtable leads and speakers for the great presentations and insightful discussions!
1/4
Awa Dieng retweeted
That’s a wrap for #AFAA2026!!! 🎉 Thank you to all the authors, attendees, roundtable leads and speakers for the great presentations and insightful discussions!
1/4
For everyone heading to Rio for #ICLR2026, don’t miss the Algorithmic Fairness Workshop #AFAA2026 this Sunday!!
We have a great program planned 👇🏾
✈️ Happy #ICLR2026 week!
⏰ Join us on Sunday for the Algorithmic Fairness workshop #AFAA2026! We have an exciting program, with amazing talks/roundtables/papers and lots of time for discussions!
🔥 Schedule: afciworkshop.org/schedule
📆 April 26, 2026
📍 Room 211
Awa Dieng retweeted
Incredible work by @BediSuhana42170 and team on HealthAdminBench. Benchmarks that only measure steps will miss end-to-end performance. Great example of what it looks like to actually design for deployment conditions. arxiv.org/abs/2604.09937, Code: github.com/som-shahlab/healt…
Agent demos meet reality in healthcare.
On 𝐇𝐞𝐚𝐥𝐭𝐡𝐀𝐝𝐦𝐢𝐧𝐁𝐞𝐧𝐜𝐡, the best agent achieved only 𝟑𝟔.𝟑% end to end success. Reliability matters.
Paper
arxiv.org/abs/2604.09937
Leaderboard
healthadminbench.stanford.ed…
@stai_research @StanfordAILab
Awa Dieng retweeted
Hey world! I am looking for a Research Scientist (L4) team match at @GoogleDeepMind and @Google 🚀
I build things with RLHF, Model Evaluation, and Computer Using Agents — from agentic pipelines to RL systems.
If you're recruiting, let's talk! My DM is OPEN
Awa Dieng retweeted
We've been working on the Waxal dataset project since 2021, aiming to enhance the amount of data available for African languages. This public speech dataset initially covers 27 Sub-Saharan African languages spoken by over 100 million speakers across more than 26 countries. 🌍
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Awa Dieng retweeted
Schmidt Sciences grantees @adjiboussodieng, an AI2050 Fellow, and @Yoshua_Bengio, a Science of Trustworthy AI grantee, were recently appointed by the @UN General Assembly to serve on the inaugural Independent International Scientific Panel on AI: un.org/independent-internati…
Awa Dieng retweeted
On Feb 12, the @UN General Assembly formally appointed the 40 members of the first Independent International Scientific Panel on AI. I am honored to join this historic effort to place science at the heart of global #AI governance, ensuring this technology benefits all of humanity.
Learn more about the panel members here: lnkd.in/eyVQg7p3
#AI #Science #Governance #Service
The UN General Assembly has appointed 40 experts of the Independent International Scientific Panel on AI. 🏛️
This body begins its work as a scientifically-grounded foundation, ensuring global understanding is driven by evidence-based scientific assessments.
#DigitalCooperation
Awa Dieng retweeted
Faculty members @adjiboussodieng and @korolova have been named to the @UN Independent International Scientific Panel on AI.
Composed of 40 experts, the panel is the first global scientific body dedicated entirely to artificial intelligence.
bit.ly/3MuPGRY
ALT Adji Bousso Dieng and Aleksandra Korolova
Awa Dieng retweeted
Singular Bayesian Neural Networks
Mame Diarra Toure, David A. Stephens
arxiv.org/abs/2602.00387 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶 𝚜𝚝𝚊𝚝.𝙰𝙿]
Awa Dieng retweeted
🚨 Deadline Extended to Feb 5 (AoE)!
CFP still OPEN for the #AFAA2026 Workshop at @iclr_conf — on fairness across alignment & agentic AI systems.
Full & tiny papers welcome • Interdisciplinary work encouraged!
🔗 afciworkshop.org
#ICLR2026 #AFAA2026
🚨 CFP OPEN!
We’re launching the #AFAA2026 Workshop at @iclr_conf on fairness across alignment and agentic AI systems.
Submit full or tiny papers!
Interdisciplinary work especially welcome :D
🗓 Deadline: Jan 31 (AoE) | 🔗 afciworkshop.org/
#AFAA2026 #ICLR2026
🚨The deadline has been extended to February 05!! 🚨
Consider submitting your drafts, either to the full paper track (6-9 pages) or the tiny paper track (1-3 pages).
We accept dual submissions to other conferences.
See details at afciworkshop.org
🚨 CFP OPEN!
We’re launching the #AFAA2026 Workshop at @iclr_conf on fairness across alignment and agentic AI systems.
Submit full or tiny papers!
Interdisciplinary work especially welcome :D
🗓 Deadline: Jan 31 (AoE) | 🔗 afciworkshop.org/
#AFAA2026 #ICLR2026
Awa Dieng retweeted
Major release from our group today: “End-to-End Test-Time Training” (TTT-E2E). We show that continual learning enables strong long context performance without changing the underlying architecture!
LLM memory is considered one of the hardest problems in AI.
All we have today are endless hacks and workarounds. But the root solution has always been right in front of us.
Next-token prediction is already an effective compressor. We don’t need a radical new architecture. The missing piece is to continue training the model at test-time, using context as training data.
Our full release of End-to-End Test-Time Training (TTT-E2E) with @NVIDIAAI, @AsteraInstitute, and @StanfordAILab is now available.
Blog: nvda.ws/4syfyMN
Arxiv: arxiv.org/abs/2512.23675
This has been over a year in the making with @arnuvtandon and an incredible team.
Awa Dieng retweeted
Princeton researchers have developed a new tool to speed the discovery of advanced materials known as metal organic frameworks potentially leading to better battery chemistry, more efficient carbon capture and improved access to clean water. bit.ly/4ptp3u6