Bridger (Waleed) Ammar has been leading top-tier, high-impact data-modeling projects since 2006 in research, education, engineering and product.

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Bridger (Waleed) Ammar has been leading top-tier, high-impact data-modeling projects since 2006 in research, education, engineering and product.

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Bridger’s Bio

Bridger (Waleed) Ammar has been leading top-tier, high-impact data-modeling projects since 2006 in research, education, engineering and product. A few experiences which particularly helped shape his thinking: - Co-founded the ACM chapter at Alexandria University.

Defended his PhD in Language-Universal Large Models (L-ULM), in 2016, with Tom Mitchell and Kuzman Ganchev as examiners. - Taught at Alexandria University, Carnegie Mellon University, and University of Washington.

Published at Nature, JAMA, NeurIPS, ACL, EMNLP among other top-tier venues. - Advised mission-critical organizations on AI strategy, including the NSF (USA), SDAIA (KSA), a leading gaming platform (USA), a leading freight forwarding platform (KSA).

At King Saud university, he learned the holistic power of safely integrating different cultures for global good. - At Alexandria University, he contributed to a digital model for historical artifacts, in collaboration with the Alexandria Library.

At P&G, he learned the holistic power of mapping the manufacturing process in a data model. - At IBM, he contributed to the state of the art (SOTA) in using statistics to model biological sequences, in collaboration with DARPA. - At eSpace, he learned the basics of building sustainable businesses, in collaboration with Alexandria University. - At Microsoft, he contributed to the then-SOTA in statistical machine translation models, in collaboration with the Cairo Microsoft Innovation Center.

At Carnegie Mellon University, as a Google PhD fellow, he developed the SOTA in language-universal models (L-UMs). - At Google Shopping, he contributed to the SOTA in mixing random forests with neural networks. - At the Allen Institute for Artificial Intelligence, he learned the SOTA in managing science from his mentor Oren Etzioni, then developed the SOTA in modeling science.

At Google Health, he contributed to the SOTA in building the digital manifestation of living cells in species-agnostic models. - At Google Research, he learned the SOTA in cost-effective scaling of LLM inference to a Billion users. - At Google Assistant, he learned the SOTA in scalable distribution of data products. - At Burning Man, he learned how to safely integrate freedom and self expression.

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