About me

Senior research scientist @ Google Deepmind in Zurich.

Welcome to my page! I am a senior research scientist at Google Deepmind, focusing on deep learning and ethical AI. Previously, I founded and led the Advanced Analytics team at Saudi Aramco, managed the company’s Enterprise Analytics program, and was a technical lead at its digital transformation program. Check out my resume for further details.

Education

• Ph.D. in Computer Science at KAUST (2012 - 2017), GPA: 4.0 / 4.0.
  • Thesis Title: Learning via Query Synthesis, Committee: X. Zhang, X. Gao, D. Keyes (KAUST), and W. Wang (UCLA).
• M.S. in Electrical Engineering at Stanford University (2009 - 2011), GPA: 4.15 / 4.0.
• B.S. in Computer Engineering at University of Nebraska, Lincoln (2000 - 2005), GPA: 3.98 / 4.0.
  • Highest Distinction, Superior Scholarship Award, Minor in Economics.

Selected Activities

• Program committee member at NeurIPS, ICML, ICLR, AAAI, CVPR, and IJCAI.
• Member of the S20 Task Force (Digital Revolution), 2020.
• Chair of AI track of the 2019 Arab-American Frontiers Symposium, 2019.

Books

Ibrahim Alabdulmohsin, Summability Calculus: A Comprehensive Theory of Fractional Finite Sums, Springer, 2018.

Recent Preprints

• Amr Khalifa, Michael C. Mozer, Hanie Sedghi, Behnam Neyshabur, Ibrahim Alabdulmohsin: “Layer-Stack Temperature Scaling,” arXiv:2211.10193, 2022.

Recent Publications

• Dehghani, M., Djolonga, J., Mustafa, B., Padlewski, P., Heek, J., Gilmer, J., Steiner, A., Caron, M., Geirhos, R., Alabdulmohsin, I., et al. “Scaling Vision Transformers to 22 Billion Parameters.” ICML, 2023.
• Lucas Beyer, Pavel Izmailov, Alexander Kolesnikov, Mathilde Caron, Simon Kornblith, Xiaohua Zhai, Matthias Minderer, Michael Tschannen, Ibrahim Alabdulmohsin, Filip Pavetic: “FlexiViT: One Model for All Patch Sizes,” CVPR, 2023.
• Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D’Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai: “Adapting to Latent Subgroup Shifts via Concepts and Proxies,” AISTATS, 2023.
• Ibrahim Alabdulmohsin, Behnam Neyshabur, Xiaohua Zhai: “Revisiting Neural Scaling Laws in Language and Vision,” NeurIPS, 2022.
• Ibrahim Alabdulmohsin, Jessica Schrouff, Oluwasanmi Koyejo: “A Reduction to Binary Approach for Debiasing Multiclass Datasets,” NeurIPS, 2022.
• Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo, Ibrahim Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D’Amour: “Maintaining fairness across distribution shift: do we have viable solutions for real-world applications?”, NeurIPS, 2022.
• Alexander Soen, Ibrahim Alabdulmohsin, Sanmi Koyejo, Yishay Mansour, Nyalleng Moorosi, Richard Nock, Ke Sun, Lexing Xie: “Fair Wrapping for Black-box Predictions,” NeurIPS, 2022.