Biography

Adel Bibi is a senior researcher in machine learning and computer vision at the Department of Engineering Science of the University of Oxford, a Junior Research Fellow (JRF) at Kellogg College, and a member of the ELLIS Society. Prior to that, Bibi was a senior research associate and a postdoctoral researcher with Philip H.S. Torr since October 2020. He earned his MSc and PhD degrees from King Abdullah University of Science & Technology (KAUST) in 2016 and 2020, respectively, advised by Bernard Ghanem. Bibi was awarded an Amazon Research Award in 2022 in the Machine Learning Algorithms and Theory track. Bibi received four best paper awards: a NeurIPS23 workshop, an ICML23 workshop, a 2022 CVPR workshop, and one at Optimization and Big Data Conference in 2018. His contributions include over 30 papers published in top machine learning and computer vision conferences. He also received four outstanding reviewer awards (CVPR18, CVPR19, ICCV19, ICLR22) and a notable Area Chair Award in NeurIPS23.

Currently, Bibi is interested in large scale offline and online robust and private continual learning. Robustness, in both aspects empirical and provably certifiable, here refers to deep models under $\ell_p$ bounded additive and geometric attacks. Moreover, continual learning refers to the learning from a stream of data in stringent memory and computational settings.

Download my resume

[Note!] I am always looking for strong self-motivated PhD students. If you are interested in Trustworthy Foundation Models that Continually Learn, reach out!

Interests
  • Trustworthy AI and Safety
  • Robustness and Certification
  • Continual Learning
  • Optimization
Education
  • PhD in Electrical Engineering (4.0/4.0); Machine Learning and Optimization Track, 2020

    King Abdullah University of Science and Technology (KAUST)

  • MSc in Electrical Engineering (4.0/4.0); Computer Vision Track, 2016

    King Abdullah University of Science and Technology (KAUST)

  • BSc in Electrical Engineering (3.99/4.0), 2014

    Kuwait University

Officially Co-supervised PhD Students

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Francisco Eiras

PhD Student, University of Oxford

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Csaba Botos

PhD Student, University of Oxford

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Cornelius Emde

PhD Student, University of Oxford

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Ameya Prabhu

PhD Student, University of Oxford

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Aleksandar Petrov

PhD Student, University of Oxford

Un-officially Co-supervised PhD Students

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Motasem Alfarra

PhD Student, KAUST

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Hasan Abed Al Kader Hammoud

PhD Student, KAUST

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Yasir Ghunaim

PhD Student, KAUST

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Wenxuan Zhang

PhD Student, KAUST

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Kumail Alhamoud

PhD Student, MIT

News

  • [January 21th, 2024]: Three papers accepted to ICLR24 (one as spotlight).

~~ End of 2023 ~~


  • [December 16th, 2023]: Our paper When Do Prompting and Prefix-Tuing Work? A Theory of Capabilities and imitations received the Entropic Paper Award at the NeurIPS 2023 Workshop: I Can’t Believe It’s Not Better (ICBINB): Failure Modes in the Age of Foundation Models.
  • [December 12th, 2023]: Received a Notable Area Chair Award in NeurIPS23 (awarded to 8.1% of 1223).
  • [December 9th, 2023]: One paper (SimCS: Simulation for Domain Incremental Online Continual Segmentation) accepted to AAAI24.
  • [November 2nd, 2023]: I gave two talks on trustwrothy AI to Kuwait University and Intematix, a startup based in Riyadh in Saudi Arabia.
  • [September 21st, 2023]: One paper on Language Model Tokenizers Introduce Unfairness Between Languages has been accepted to NeurIPS23.
  • [September 5th, 2023]: Invited by Dima Damen to give a talk at Bristol University.
  • [July 18th, 2023]: One robustness paper is accepted to TMLR.
  • [July 11th, 2023]: Our paper on Provably Correct Physics-Informed Neural Networks received the outstanding paper award in the Formal Verification Workshop in ICML23.
  • [July 14th, 2023]: One paper on online continual learning is accepted to ICCV 2023.
  • [July 11th, 2023]: Our paper Provably Correct Physics-Informed Neural Networks received an outstanding paper award at WFVML ICML23 workshop.
  • [June 23rd, 2023]: One paper accepted to DeployableGenerativeAI (ICML23 Workshop).
  • [June 20th, 2023]: Three papers accepted to AdvML-Frontiers (ICML23 Workshop).
  • [June 18th, 2023]: Invited to give a talk at the CLVision workshop in CVPR23. I was also part of the panel discussion.
  • [April 24th, 2023]: One paper accepted to ICML 2023.
  • [March 29th, 2023]: Four papers accepted to CLVision (CVPR23 Workshop).
  • [March 9th, 2023]: Media coverage by DOU, a Ukrainian development community focused on technologies, frameworks, and code, for my work with Taras Rumezhak.
  • [March 1st, 2023]: I am promoted to a Senior Researcher (G9) in Machine Learning and Computer Vision at Oxford.
  • [February 28th, 2023]: I will serve as an Area Chair for the NeurIPS 2023.
  • [February 27th, 2023]: Two papers accepted to CVPR 2023. One of the two papers is accepted as a highlight (2.5% of ~9K submissions).
  • [January 23th, 2023]: I will serve as an Area Chair for the ICLR 2023 Workshop on Trustworthy ML.

~~ End of 2022 ~~


  • [December 9th, 2022]: I will serve as a Senior Program Committee (Area Chair/Meta Reviewer) for IJCAI 2023.
  • [November 3rd, 2022]: Joined the ELLIS Society as a member.
  • [October 11th, 2022]: One paper accepted to WACV23.
  • [October 10th, 2022]: Recieved an Amazon Research Award.
  • [September 14th, 2022]: Our paper N-FGSM accepted to NeurIPS22.
  • [August 28th, 2022]: Our paper ANCER was accepted in Transactions on Machine Learning Research (TMLR).
  • [August 15th, 2022]: Our paper on Tropical Geometry was accepted to appear in the IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
  • [July 11th, 2022]: I will serve as a Senior Program Committee (Area Chair/Meta Reviewer) for AAAI23.
  • [May 26th, 2022]: Three papers accepted to the Adversarial Machine Learning Frontiers ICML2022 workshop! Papers will be coming on arXiv soon.
  • [May 16th, 2022]: Our paper titled Data Dependent Randomzied Smoothing is accepted to UAI22.
  • [April 22nd, 2022]: I was selected as the Highlighted Reviewer of ICLR 2022 and received a free conference registration.

~~ End of 2021 ~~



~~ End of 2020 ~~


  • [November 8th, 2020]: New paper on robustness is on arXiv.
  • [November 8th, 2020]: New paper on randomized smoothing is on arXiv.
  • [October 15th, 2020]: I joined the Torr Vision Group working with Philip Torr at the University of Oxford.
  • [July 2nd, 2020]: Gabor layers enhance robustness paper accepted to ECCV20 arXiv.
  • [June 30th, 2020]: One paper is out on new expressions for the output moments of ReLU based networks with various new appliactions arXiv.
  • [June 24th, 2020]: New paper with SOTA results, backed with theory, on training robust models through feature clustering arXiv.
  • [March 31st, 2020]: I have sucessfully defended my PhD thesis.

~~ End of 2019 ~~


  • [Dec 20th, 2019]: One paper accepted to ICLR20.
  • [Nov 11th, 2019]: One spotlight paper accepted to AAAI20.
  • [Sept 25th, 2019]: Recognized as outstanding reviewer for ICCV19. Link.
  • [August 5th, 2019]: I was invited to give a talk about the most recent research in computer vision and machine learning from the IVUL group at PRIS19, Dead Sea, Jordan. I also gave a 1 hour long workshop about deep learning and pytorch. Slides1/Slides2/Material.
  • [July 6th, 2019]: I was invited to give a talk at the Eastern European Conference on Computer Vision, Odessa, Ukraine. Slides.
  • [June 28th, 2019]: I gave a talk at the Biomedical Computer Vision Group directed by Prof Pablo Arbelaez, Bogota, Colombia. Slides.
  • [June 15th, 2019]: Attended CVPR19.
  • [June 9th, 2019]: Recognized as an outstanding reviewer for CVPR19. This is the second time in a row for CVPR. Check it out. :)
  • [May 26th, 2019]: A new paper is out on derivative free optimization with momentum with new rates and results on continuous controls tasks. arXiv.
  • [May 25th, 2019]: New paper! New provably tight interval bounds are derived for DNNs. This allows for very simple robust training of large DNNs. arXiv.
  • [May 11th, 2019]: How to train robust networks outperforming 2-21x fold data augmentation? New paper out on arXiv.
  • [May 6th, 2019]: Attended ICLR19 in New Orleans.
  • [Feb 4th, 2019]: New paper on derivative-free optimization with importance sampling is out! Paper is on arXiv.

~~ End of 2018 ~~


  • [Dec 22nd, 2018]: One paper accepted to ICLR19, Louisiana, USA.
  • [Nov 6th, 2018]: One paper accepted to WACV19, Hawaii, USA.
  • [July 3rd, 2018]: One paper accepted to ECCV18, Munich, Germany.
  • [June 19th, 2018]: Attended CVPR18 and gave an oral talk on our most recent work on analyzing piecewise linear deep networks using Gaussian network moments. Tensorflow, Pytorch and MATLAB codes are released.
  • [June 17th, 2018]: Received a fully funded scholarship to attend the AI-DLDA 18 summer school in Udine, Italy. Unfortunately, I won’t be able to attend for time constraints. Link
  • [June 15th, 2018]: New paper out! “Improving SAGA via a Probabilistic Interpolation with Gradient Descent”.
  • [April 30th, 2018]: I’m interning for 6 months at the Intel Labs in Munich this summer with Vladlen Koltun.
  • [April 22nd, 2018]: Recognized as an outstanding reviewer for CVPR18. I’m also on the list of emergency reviewers. Check it out. :)
  • [March 6th, 2018]: One paper accepted as [Oral] in CVPR 2018.
  • [Feb 5, 2018]: Awarded the best KAUST poster prize in the Optimization and Big Data Conference.

~~ End of 2017 ~~


  • [Decemmber 11, 2017]: TCSC code is on github.
  • [October 22, 2017]: Attened ICCV17, Venice, Italy.
  • [July 22, 2017]: Attened CVPR17 in Hawaii and gave an oral presentation on our work on solving the LASSO with FFTs, July 2017.
  • [July 16, 2017]: FFTLasso’s code is available online.
  • [July 9, 2017]: Attended the ICVSS17, Sicily, Italy.
  • [June 15, 2017]: Selected to attend the International Computer Vision Summer School (ICVSS17), Sicily, Italy.
  • [March 17, 2017]: 1 paper accepted to ICCV17.
  • [March 14, 2017]: Received my NanoDegree on Deep Learning from Udacity.
  • [March 3, 2017]: 1 oral paper accepted to CVPR17, Hawai, USA.

~~ End of 2016 ~~


  • [October 19, 2016]: ECCV16’s [code](https://github.com/adelbibi/ Target-Response-Adaptation-for-Correlation-Filter-Tracking) has been released on github.
  • [October 8, 2016]: Attended ECCV16, Amsterdam, Netherlands.
  • [July 11, 2016]: 1 spotlight paper accepted to ECCV16, Amsterdam, Netherlands.
  • [June 26, 2016]: Attended CVPR16, Las Vegas, USA. Two papers presented.
  • [May 13, 2016]: ICCVW15 code is now avaliable online.
  • [April 11, 2016]: Successfully defended my Master’s Thesis.
  • [March 2, 2016]: 2 papers (1 spotlight) accepted to CVPR16, Las Vegas, USA.

~~ End of 2015 ~~


  • [November 20, 2015]: 1 paper acceted to ICCVW15, Santiago, Chile.
  • [June 8, 2015]: Attended CVPR15, Boston, USA.

Awards

Recent & Upcoming Talks

Trustworthy AI
Trustworthy Deep Learning
Trustworthy and Safe Deep Learning

Contact

  • adel.bibi@eng.ox.ac.uk
  • 20.16, Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ