CRA-I Blog

The CRA-I Blog frequently shares news, timely information about the computing research industry community, and items of interest to the general community. Subscribe to blog emails here to stay connected.

Register to attend CRA-I’s GenAI for Research and Science Roundtable on May 1st!

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The Computing Research Association-Industry (CRA-I) is hosting a virtual roundtable event on May 1st, from 3-4:30 PM ET, focusing on Generative AI (GenAI) for Research and Science. Please register to attend here.

Generative Artificial Intelligence (GenAI) is at the forefront of technological advancement and has the potential to transform and accelerate research across diverse fields. The goal of this roundtable is to discuss examples of new frontiers of GenAI in both academia and industry, consider the impact on scientific discovery and the R&D community, and discuss how to ensure responsible use and development. The roundtable will look at use cases from various fields such as biomedical, energy, and materials science. The aim is to inspire and enlighten the broad research community, while emphasizing the importance of caution to ensure that advancements benefit everyone.

Don’t miss this opportunity to be part of this transformative conversation! Please register to attend here.

Theo Drane (Intel) Joins CRA-Industry Council

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CRA-Industry (CRA-I) is delighted to announce that Theo Drane (Intel) has joined the CRA-I Council. He joins a growing list of Council members, led by CRA-I Council Chair Divesh Srivastava (AT&T), that will continue to work closely with the CRA-I Steering Committee to identify future committee directions, connect with the community, and achieve the goals of CRA-I.

“Theo is a passionate advocate for joint academic/industrial PhDs, and we look forward to Theo helping CRA-I build strong bridges between computing research in industry and academia,” said Srivastava. 

Dr. Theo Drane is a Principal Engineer at Intel Corporation where he founded and runs the Numerical Hardware and System Level Design Group within Intel Graphics. He worked for the Datapath consultancy, Arithmatica, after completing a Mathematics degree from the University of Cambridge. Moving to Imagination Technologies, he founded their Datapath team while studying for a PhD at Imperial College London’s Electrical and Electronic Engineering Department. After a stint within Cadence Design System’s Logic Synthesis division, Genus, he joined Intel’s 3D Compute and Graphics division. His Intel team is an applied research group acting as an internal consultancy working within the division and Intel at large. The group focuses on all aspects of architecting, implementing, optimizing and formally verifying math intensive hardware and system level design in general. The group offers and promotes ‘Acadustrial’ PhDs – simultaneous full time industrial employment and PhD enrollment; driving knowledge creation and transfer. Dr. Drane has served as Program co-Chair for IEEE International Symposium on Computer Arithmetic.

Please help the industry research community by continuing to nominate outstanding colleagues for the CRA-I Council. Read more here and send nominations to industryinfo@cra.org.

Welcome, Theo!

Request for Information from Industry – Countering Bias in AI/ML Datasets

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This post benefited from significant contributions by Petruce Jean-Charles, Communications Associate for the Computing Community Consortium (CCC).

The U.S. Air Force Chief Scientist’s inter-agency working group on unintended AI bias is exploring the topic of bias in Artificial Intelligence (AI) and Machine Learning (ML) algorithms, with particular focus on datasets. They recently released a request for information (RFI) on countering bias in AI and ML datasets. As the landscape of AI expands, diverse domains present unique challenges concerning unintended bias. In this case, they seek insights from commercial and non-profit organizations harnessing data for AI development, encompassing both “narrow AI” and generative AI.

They are soliciting information to better understand:

  • The datasets and domain areas with prominent AI bias, including in government datasets
  • Ongoing efforts to address unintended bias in AI and ML datasets
  • Current partnerships between industry and government or academic institutions to study, identify, and mitigate AI bias
  • Existing limitations and obstacles to mitigating such bias
  • Areas of need for further research

Responses should be submitted through the Tradewindai.com portal by May 15, 2024 and should be a maximum of 5 pages.­ More information, including the full RFI, can be found here.

Academics intrigued by contributing their insights on these challenges are encouraged to engage with the group through a complementary Request for Information tailored for academia. They welcome responses from academic institutions, with a special emphasis on minority serving institutions (MSIs) and historically black colleges and universities (HBCUs).