Evelyne Viegas
Redmond, Washington, United States
5K followers
500+ connections
About
Over the years, I have had the privilege of contributing to multiple waves in the…
Experience
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Education
Licenses & Certifications
Volunteer Experience
-
Project Committee Member
UIDP
- 2 years 1 month
Science and Technology
I evaluate the proposals submitted to UIDP from a scientific and technological perspectives while ensuring the diverse voices of the community are represented.
-
Competition Judge
Technovation
- 2 years 7 months
Education
Competition Judge for the Technovation AI Challenge for Families
Technovation is a global technology-education nonprofit that brings together mentors from industry with local communities (especially girls and women) to solve pressing problems using technologies.
Some of the AI work done by families and individuals across the globe was presented at the NeurIPS 2020 workshop Challenges in Machine Learning (CiML'2020). -
Co-Founder
Challenges in Machine Learning (CiML)
- 8 years
Science and Technology
The CiML (Challenges in Machine Learning) workshop series was co-founded by Isabelle Guyon and Evelyne Viegas. It is a forum that has been bringing together workshop organizers, platform providers, and participants since 2014, to discuss best practices in organizing competitions and new methods and application opportunities to design high impact competitions. The community has been meeting yearly at NeurIPS at the CiML workshops.
We are now working on a collaborative book on "AI…The CiML (Challenges in Machine Learning) workshop series was co-founded by Isabelle Guyon and Evelyne Viegas. It is a forum that has been bringing together workshop organizers, platform providers, and participants since 2014, to discuss best practices in organizing competitions and new methods and application opportunities to design high impact competitions. The community has been meeting yearly at NeurIPS at the CiML workshops.
We are now working on a collaborative book on "AI competitions and benchmarks: the science behind the contests."
Join the community at: ciml.chalearn.org -
Publications
-
Breadth and Depth of Semantic Lexicons
E. Viegas (Ed.) / Kluwer Academic Publishers - Springer
"Most of the books about computational (lexical) semantic lexicons deal with the depth (or content) aspect of lexicons, ignoring the breadth (or coverage) aspect. This book presents a first attempt in the community to address both issues: content and coverage of computational semantic lexicons, in a thorough manner. Moreover, it addresses issues which have not yet been tackled in implemented systems such as the application time of lexical rules. Lexical rules and lexical underspecification are…
"Most of the books about computational (lexical) semantic lexicons deal with the depth (or content) aspect of lexicons, ignoring the breadth (or coverage) aspect. This book presents a first attempt in the community to address both issues: content and coverage of computational semantic lexicons, in a thorough manner. Moreover, it addresses issues which have not yet been tackled in implemented systems such as the application time of lexical rules. Lexical rules and lexical underspecification are also contrasted in implemented systems. The main approaches in the field of computational (lexical) semantics are represented in the present book (including Wordnet, CyC, Mikrokosmos, Generative Lexicon).
This book embraces several fields (and subfields) as different as: linguistics (theoretical, computational, semantics, pragmatics), psycholinguistics, cognitive science, computer science, artificial intelligence, knowledge representation, statistics and natural language processing." Springer -
Computational Lexical Semantics - Studies in Natural Language Processing
E. Viegas (Co-Editor) / Cambridge University Press
"Computational Lexical Semantics is one of the first volumes to provide models for the creation of various kinds of computerized lexicons for the automatic treatment of natural language, with applications to, among other things, machine translation, automatic indexing, database front-ends, and knowledge extraction. It focuses on semantic issues, as seen by linguists, psychologists, and computer scientists." - CUP
Other authors -
Patents
-
Semantic Search Interface For Data Collections
Issued US 10402442
Other inventors -
-
Action Broker
Issued US 9558275
Other inventors -
-
Enrichment of named entities in documents via contextual attribute ranking
Issued US 9,552,352
Other inventors -
-
Permission based query processing
Issued US 9,183,407
Other inventors -
-
Named entity (NE) interface for multiple client application programs
Issued US 7,315,810
Other inventors -
Projects
-
Agentic AI Research and Innovation
The Agentic AI Research & Innovation (AARI) program embraces the spirit of openness, collaboration, and responsible innovation to a new era of intelligent systems—AI agents capable of reasoning, planning, and collaborating safely in complex real-world environments.
AARI builds on the strong foundation of the Accelerating Foundation Model Research (AFMR), an AI global initiative with the academic community to advance the foundations of AI research together for the benefit of society. -
Accelerating Foundation Models Research (AFMR)
Accelerating Foundation Models Research (AFMR) is a global research network and a resource platform, which enables a network of researchers with different expertise to engage on solving together some of the greatest technical and societal challenges of tomorrow in AI.
AFMR includes a grant program that provides access to state-of-the-art foundation models hosted on Microsoft Azure through Microsoft Azure AI Foundry. Through AFMR our goal is to foster more collaborations across disciplines…Accelerating Foundation Models Research (AFMR) is a global research network and a resource platform, which enables a network of researchers with different expertise to engage on solving together some of the greatest technical and societal challenges of tomorrow in AI.
AFMR includes a grant program that provides access to state-of-the-art foundation models hosted on Microsoft Azure through Microsoft Azure AI Foundry. Through AFMR our goal is to foster more collaborations across disciplines, institutions, and sectors, and to unleash the full potential of AI for a wide range of research questions, applications, and societal context. -
CodaLab
- Present
CodaLab is an open-source platform that provides an ecosystem for conducting computational research in a more efficient, reproducible, and collaborative manner. There are two aspects of CodaLab: worksheets and competitions.
- Worksheets allow you to capture complex research pipelines in a reproducible way and create "executable papers". Use any data format or programming language — great for the power user! Check out: https://worksheets.codalab.org/
- Competitions bring together the…CodaLab is an open-source platform that provides an ecosystem for conducting computational research in a more efficient, reproducible, and collaborative manner. There are two aspects of CodaLab: worksheets and competitions.
- Worksheets allow you to capture complex research pipelines in a reproducible way and create "executable papers". Use any data format or programming language — great for the power user! Check out: https://worksheets.codalab.org/
- Competitions bring together the entire community to tackle the most challenging data and computational problems today. You can win prizes and also create your own competition. Check out: https://competitions.codalab.org/
Other creators -
-
Project Malmo
-
The Malmo platform is an open source sophisticated Artificial Intelligence experimentation platform built on top of Minecraft, and designed to support fundamental research in artificial intelligence.
Try it today: https://github.com/Microsoft/malmo#getting-startedOther creators -
-
TryF#
-
TryF# is a new tool from Microsoft Research Connections that enables the learning of the F# programming language in an interactive browser-based environment. TryF# makes F# accessible to users with Windows and Macs when using common browsers. TryF# also has an online training tool to introduce users to F# and it provides a portal for information about the language and its growing community, linking them through Facebook and Twitter. TryF# was developed by Microsoft Research Connections…
TryF# is a new tool from Microsoft Research Connections that enables the learning of the F# programming language in an interactive browser-based environment. TryF# makes F# accessible to users with Windows and Macs when using common browsers. TryF# also has an online training tool to introduce users to F# and it provides a portal for information about the language and its growing community, linking them through Facebook and Twitter. TryF# was developed by Microsoft Research Connections Engineering and Computer Science teams, in collaboration with Microsoft Research Cambridge, and the Visual Studio F# development team.
Other creators -
-
Web N-gram Services
-
Web N-gram services, made available via a cloud-based platform, help drive discovery and innovation in web search, natural language processing, speech, and related areas by conducting research on real-world web-scale data, taking advantage of regular data updates for projects that benefit from dynamic data.
Other creators -
Languages
-
English
Full professional proficiency
-
French
Native or bilingual proficiency
-
Spanish
Full professional proficiency
Other similar profiles
Explore more posts
-
Jon Salisbury
Gödel Test: Can Large Language Models Solve Easy Conjectures? Authors Moran Feldman Amin Karbasi Abstract Recent announcements from frontier AI model labs have highlighted strong results on high-school and undergraduate math competitions. Yet it remains unclear whether large language models can solve new, simple conjectures in more advanced areas of mathematics. We propose the Gödel Test: evaluating whether a model can produce correct proofs for very simple, previously unsolved conjectures. To this end, we study the performance of GPT-5 on five conjectures in combinatorial optimization. For each problem, we provided one or two source papers from which the conjecture arose, withheld our own conjecture, and then assessed the model's reasoning in detail. On the three easier problems, GPT-5 produced nearly correct solutions; for Problem 2 it even derived a different approximation guarantee that, upon checking, refuted our conjecture while providing a valid solution. The model failed on Problem 4, which required combining results from two papers. On Problem 5, a harder case without a validated conjecture, GPT-5 proposed the same algorithm we had in mind but failed in the analysis, suggesting the proof is more challenging than expected. Although our sample is small, the results point to meaningful progress on routine reasoning, occasional flashes of originality, and clear limitations when cross-paper synthesis is required. GPT-5 may represent an early step toward frontier models eventually passing the Gödel Test. Link to paper: https://lnkd.in/gZD8xDsz #ai #test #benchmark #math
1 Comment -
Risto Miikkulainen
Fine-tuning LLMs with evolution strategies (an alternative to gradient descent) has turned out to be a productive research direction! Four new papers from Cognizant AI Lab evaluate it in several new tasks including Math and ARC-AGI, extend it to fine-tuning quantized models, demonstrate how LLMs can be trained to know what they know, and show why high dimensionality of models is a blessing (not a curse) in fine-tuning. Overview blog: https://cgnz.at/6005QZNMb Papers: https://cgnz.at/6007QZN13 (tasks) https://cgnz.at/6003QZNHN (quantized) https://cgnz.at/6002QZNGG (metacognition) https://cgnz.at/6000QZNyI (blessing) Animated illustration: https://lnkd.in/gUUaYVAT
3 Comments -
ACM, Association for Computing Machinery
🎙️ New #ACMByteCast Alert! ACM Fellow Michael J. Freedman talks with Rashmi Mohan about building Coral CDN, co-founding Timescale, and turning research into real-world impact. 💡 From peer-to-peer systems to databases for real-time analytics—don’t miss this deep dive into scalable tech. Listen now here or wherever you get your podcast: https://buff.ly/R2fFGLJ #DistributedSystems #TechInnovation
-
Timothy Cook
The Semantic Data Charter (SDC) is a semantic interoperability framework that fundamentally changes how organizations manage data integration and exchange. By separating structural validation from semantic meaning through a two-level modeling approach, SDC eliminates the costly data migration cycles that plague traditional systems while enabling true cross-organizational interoperability. https://lnkd.in/e4QF5A4M
-
Michelângelo Viana
If you haven't heard about the Scholarly Graph yet, you should check it out! Super fascinating stuff. EBSCO's linked data experts are passionate about making research more connected — linking over 900 million scholarly entities and 3.8 billion relationships to uncover hidden connections and trace the story of scholarship. It's starting to power Citation Discovery features in EBSCO Discovery Service and EBSCOhost — and that is just the beginning! Learn more: https://ow.ly/cu8Z30sQe1I
Explore top content on LinkedIn
Find curated posts and insights for relevant topics all in one place.
View top content