Mountain View, CA
2024–present
Co-founder
- Leading product design and development for a portfolio of AI-powered software, from early prototypes through implementation.
Geoff Davis
geoff@geoffdavis.net • github.com/geoff-davislinkedin.com/in/geoff-m-davis • geoffdavis.net
I’m the co-founder of Keksi AI, an independent product studio building thoughtful, practical applications of AI. Previously, I was a Staff Data Scientist at Google. Across applied mathematics, software, data science, and machine learning, my work has centered on turning difficult technical ideas and messy real-world data into useful systems.
Experience
Mountain View, CA
2023–2024
Staff Data Scientist, Lead, Core ML Data Science
- Identified anomalies in large-scale LLM training data, assessed human-rater performance for reinforcement learning from human feedback (RLHF), and ran an internal seminar on methods for assessing data quality at scale.
2017–2023
Staff Data Scientist, Google Research
- Led development of an internal PaLM 2 application that helped users construct complex SQL queries over large datasets.
- Applied machine learning to microscopy images from a large-scale antimalarial drug screen, identifying previously undetected hits (code).
- Developed and evaluated an experimental optimal-transport approach to correcting batch effects in cellular assays; contributed the implementation to the open-source Optimal Transport Tools library.
2014–2017
Staff Data Scientist, Verily / Google [x]
- Led development of Verily's RNA-seq quality-assurance and processing pipelines.
- Developed a novel method for estimating DNA contamination in RNA-seq samples.
2012–2014
Staff Data Scientist, Search Infrastructure
- Analyzed how mobile app use affected search query volume and presented the findings to Google's senior vice presidents; the analysis informed Google's decision to promote native apps on Android.
- Created long-term forecasts for global query volume to guide decisions on the placement of future data centers.
2007–2012
Staff Quantitative User Experience Researcher,
Google AdWords
- Built AdWords user metrics and the data infrastructure needed to combine signals from multiple sources.
- Created a new AdWords help format, secured development resources, and demonstrated its effectiveness; Gmail, AdSense, and Webmaster Tools later adopted it.
Collected Insight
San Francisco, CA; Raleigh, NC
2001–2007
Founder
- Core developer for Plone, an open source content management system. Member of the board of directors of the Plone Foundation, 2004–2006.
- Created a data-driven graduate school guide using government sources that served roughly 100,000–200,000 users per month.
- Principal investigator for a national survey of 7,600 postdoctoral researchers at 47 institutions. Secured grants from the Alfred P. Sloan Foundation and the Burroughs Wellcome Fund.
4charity
San Francisco, CA
2000–2001
Senior Software Engineer
Redmond, WA
1999–2000
Researcher,
Signal Processing Group,
Microsoft Research
- Researched methods for the efficient storage and transmission of digital multimedia.
1998–1999
Researcher / Software Engineer, Semantic Platform Group
- Developed algorithms and software for analyzing and manipulating semantically annotated data.
Houston, TX
1997
Texas Instruments Visiting Assistant Professor,
ECE Department
Hanover, NH
1996–1998
Assistant Professor,
Mathematics Department
1994–1996
John Wesley Young Research Instructor,
Mathematics Department
Corporate Communication Group
New York, NY
1992
Senior Programmer, Interactive Technologies
- Designed and implemented an unencumbered third-person virtual reality software platform in C++ and received a related patent.
Skills
- Core: Python; applied machine learning; LLM data quality and evaluation
- Data and systems: SQL; large-scale data processing; statistical analysis and experimentation
- Product development: AI prototyping; product design; end-to-end implementation
Education
New York, NY
Ph.D., Mathematics,
Courant Institute
- Thesis: Adaptive Nonlinear Approximations. Advisor: Stèphane Mallat.
- Office of Naval Research / ASEE Graduate Fellowship.
Durham, NC
B.S., double major in Mathematics and Physics
- Graduated magna cum laude, with honors. Phi Beta Kappa.
- Honors thesis: Mathematical Models for Urban-Suburban Spread of Disease. Advisor: Leah Edelstein-Keshet.
Awards
- IEEE Leon K. Kirchmayer Prize Paper Award (best paper in an IEEE journal by an author under 30), 2000.
- IEEE Signal Processing Society Young Author Best Paper Award, 1999.
- NSF Mathematical Sciences Postdoctoral Research Fellowship, 1996–1998.
Earlier Professional Activities
- Committee on Developing Science, Technology, and Innovation Indicators for the Future, National Research Council, 2011–2012.
- Wertheim Fellow, Labor and Worklife Program, Harvard Law School, 2004, 2007.
- Technical Advisory Board Member, Berkeley Electronic Press, 2007.
- Member of the Science and Engineering Workforce Project, National Bureau of Economic Research, 2001–2007.
Selected Publications
Google Applied Science
Applied machine learning in biology, energy, and drug discovery.- Kevin McCloskey, Sixing Chen, Vincent R. Meijer, Joe Yue-Hei Ng, Geoff Davis, Carl Elkin, Christopher Van Arsdale, Scott Geraedts "Estimates of broadband upwelling irradiance from GOES-16 ABI," Remote Sensing of Environment, Volume 285, 1 February 2023, 113376. DOI: 10.1016/j.rse.2022.113376
- Marco Cuturi, Laetitia Meng-Papaxanthos, Yingtao Tian, Charlotte Bunne, Geoff Davis, Olivier Teboul "Optimal Transport Tools (OTT): A JAX Toolbox for all things Wasserstein," January 2022.
- Ali Bashir, Qin Yang, Jinpeng Wang, Stephan Hoyer, Wenchuan Chou, Cory McLean, Geoff Davis, Qiang Gong, Zan Armstrong, Junghoon Jang, Hui Kang, Annalisa Pawlosky, Alexander Scott, George E. Dahl, Marc Berndl, Michelle Dimon, B. Scott Ferguson, "Machine learning guided aptamer refinement and discovery," Nature Communications 12, Article number: 2366 (2021).
Science Workforce
Empirical studies of labor markets and training practices in science and mathematics.- Geoffrey M. Davis, "Improving the Postdoctoral Experience: An Empirical Approach." In Richard B. Freeman and Daniel L. Goroff (Eds.), Science and Engineering Careers in the United States: An Analysis of Markets and Employment, Chicago, IL: University of Chicago Press, 2009.
- Geoffrey M. Davis, Doctors Without Orders. American Scientist 93 (3, supplement), 2005.
- Geoffrey M. Davis, "Mathematicians and the Market," Notices of the American Mathematical Society, Vol. 44, No. 10, pp. 1307-1315, 1997.
Wavelet Design
Nonlinear transforms and multiwavelet constructions via lifting.- Roger L. Claypoole, Jr., Geoffrey M. Davis, Wim Sweldens, and Richard G. Baraniuk "Nonlinear Wavelet Transforms for Image Coding via Lifting," IEEE Transactions on Image Processing, Vol. 12 No. 12, 1449-1459, Dec. 2003. DOI: 10.1109/TIP.2003.817237
- Geoffrey M. Davis, Vasia Strela, Radka Turcajova, "Multiwavelet Construction via the Lifting Scheme," in Wavelet Analysis and Multiresolution Methods, T.-X. He (editor), Lecture Notes in Pure and Applied Mathematics, Marcel Dekker, New York, 1999.
- Roger L. Claypoole, Jr., Geoffrey M. Davis, Wim Sweldens, and Richard G. Baraniuk, "Nonlinear Wavelet Transforms for Image Coding," Asilomar Conference on Signals, Systems, and Computers, Vol. 1, 662-667, 1997. DOI: 10.1109/ACSSC.1997.680528
Image Compression
Wavelet-based coding, fractal-based coding, quantization methods, and transmission over lossy networks.- Geoffrey M. Davis, "A Wavelet-based Analysis of Fractal Image Compression," IEEE Transactions on Image Processing, Vol. 7, No. 2, 141-154, Feb. 1998. Recipient of the 2000 IEEE Leon K. Kirchmayer Prize Paper Award. DOI: 10.1109/83.660992
- Geoffrey M. Davis and Aria Nosratinia, "Wavelet-Based Image Coding: An Overview," Applied and Computational Control, Signals, and Circuits, Vol. 1, No. 1, Spring 1998.
- Geoffrey M. Davis and Sumit Chawla, "Image Coding Using Optimized Significance Tree Quantization," Proc. Data Compression Conference, 1997, 387-396, 1997. DOI: 10.1109/DCC.1997.582064
- Geoffrey M. Davis and John Danskin, "Joint Source and Channel Coding for Image Transmission Over Lossy Packet Networks," SPIE Conference on Wavelet Applications of Digital Image Processing XIX, Denver, August 1996.
- Geoffrey M. Davis, "Implicit Image Models in Fractal Image Compression," Invited paper, SPIE Conference on Wavelet Applications in Signal and Image Processing IV, Denver, August 1996.
- John Danskin, Geoffrey M. Davis, and Xiyong Song, "Fast Lossy Internet Image Transmission," ACM Multimedia, San Francisco, November 1995.
- Geoffrey M. Davis, "Adaptive Self-Quantization of Wavelet Subtrees: A Wavelet-Based Theory of Fractal Image Compression," SPIE Conference Wavelet Applications in Signal and Image Processing III, San Diego, July 1995. Earlier versions of this work appeared at the 1995 IEEE Data Compression Conference in Snowbird, Utah and at SPIE Wavelet Applications for Dual Use 1995, Orlando.
Adaptive Greedy Decompositions
Decomposing functions over redundant dictionaries of waveforms.- Geoffrey M. Davis, Stéphane Mallat, and Marco Avellaneda, "Adaptive Greedy Approximations," Journal of Constructive Approximation, Vol. 13, 57-98, 1997.
- Geoffrey M. Davis, Stéphane Mallat, and Zhifeng Zhang, "Adaptive time-frequency decompositions with Matching Pursuit," Optical Engineering, Vol. 33, No. 7, pp. 2183-2191, July 1994.
- Geoffrey M. Davis, Adaptive Nonlinear Approximations, Ph.D. dissertation, 1994.