BU AIR

BU AIR

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Boston University's Artificial Intelligence Research (BU-AIR) group is the community of researchers at BU working on machine intelligence.

Here’s Who BU Invited to Join the Class of 2026 04/12/2022

Among those accepted is a (high school) student who developed an app to detect Parkinson's disease from facial photographs. Impressive, indeed.

Here’s Who BU Invited to Join the Class of 2026 With 80,794 students applying for 3,100 openings, the University’s acceptance rate was 14 percent

AI4ALL | Home 04/05/2022

Are you a high school student (identifying as female) interested in AI? Consider applying to AI4ALL to get some hands-on experience and boost your resume for college applications!

AI4ALL | Home

02/25/2022

Our new building taking shape!

A typical New England day at BU! ❄️☃️🥶

[📸 credit: oschapov via Instagram]

12/02/2021

Reminder that this is tomorrow! Still not too late to register: shorturl.at/jvwF1

12/01/2021

📢 NeurIPS Challenge Workshop! 📢

Join us next Tuesday, Dec. 7th 20:00 GMT; we will be presenting the results of ViSDA 2021 -- a competition on universal domain adaptation! Expect great speakers and presentations from winners.

More details at http://ai.bu.edu/visda-2021/

How Scientists Drew Weissman (MED'87, GRS'87) and Katalin Karikó Developed the Revolutionary mRNA Technology Inside COVID Vaccines 11/27/2021

Drew Weissman along with Katalin Karikó developed the key changes required to make RNA vaccines work in humans without adverse reactions, which laid the foundations for the development of the safe and effective Pfizer/BioNTech and Moderna MRNA vaccines for COVID-19 we have today.

How Scientists Drew Weissman (MED'87, GRS'87) and Katalin Karikó Developed the Revolutionary mRNA Technology Inside COVID Vaccines It started with a chance encounter, and led to worldwide acclaim for the two researchers

10/19/2021

Save the date! Distinguished speaker, Samory Kpotufe, Associate Professor of Statistics at Columbia University, will be presenting at the BU-AIR Seminar on Monday, Nov 1, 10:45 am to 12 pm ET.
Link to register: shorturl.at/ikzV4

10/12/2021

Check out the work on tuning hyper-parameters in unsupervised domain adaptation without labels by Kuniaki Saito, Donghyun Kim, Piotr Teterwak, Stan Sclaroff, Trevor Darrell, and Kate Saenko. Poster at ICCV tomorrow at 8 am and Friday at 3pm ET.
Paper: https://arxiv.org/abs/2108.10860
Joint work from Boston University, MIT-IBM Watson AI Lab, and UC Berkeley.

10/12/2021

Check out the work from BU AIR in collaboration with Massachusetts Institute of Technology (MIT) (MIT-IBM Watson AI) at ICCV 2021.
AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition by Rameswar Panda, Chun-Fu Chen, Quanfu Fan, Ximeng Sun, Kate Saenko, Aude Oliva, and Rogerio Feris.
Project page: https://rpand002.github.io/adamml.html

10/12/2021

Check out instance-aware video quantization that decides what precision to use per frame for efficient video inference. Joint work by Ximeng Sun, Rameswar Panda, Chun-Fu Chen, Aude Oliva, Rogerio Feris, and Kate Saenko presented at ICCV 2021!

Project Page: https://cs-people.bu.edu/sunxm/VideoIQ/project.html

Joint work between Boston University, Massachusetts Institute of Technology (MIT), MIT-IBM Watson AI Lab.

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Boston, MA
02215