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Team

Will

Co-Founder

Dr. William Wu studied EECS at Berkeley, followed by an M.S. in mathematics and Ph.D. in EE at Stanford. Trained both as a researcher and an engineer, he has +12 years of experience in building novel scientific computing solutions for organizations with complex data needs, including computer vision and NLP startups, bioinformatics research centers, and NASA JPL. Today he directs QED’s mission to amplify knowledge and information transparency in developing countries. He is passionate about all things clever and strives to build cultures of innovation that are both practical and sustainable.

Will

Dr. William Wu studied EECS at Berkeley as an undergraduate, followed by a master’s degree in math and doctoral studies in EE at Stanford. Having been trained both as a researcher and as an engineer, he has developed a broad range of research interests about all things clever, including efficient algorithms, computer vision, NLP, and recreational puzzles, and has helped many companies achieve their MVPs for R&D projects.

WW is a former member of the NASA Jet Propulsion Laboratory, where he worked as a telecommunications researcher and engineer, and developed DSP algorithms and software for various space missions including OPALS, MRO, GRAIL, and Curiosity. Some of the research initiatives pursued at JPL included leveraging Hadoop + EC2 to build cheap and scalable telecom decoders, and compressed sensing for radar. He has also worked at Apple and NEC Research Labs China, the latter at which he developed PTAS convex optimization algorithms for dynamically assigning frequencies to access points in WLANs in order to boost throughput.

WW has served as a technical consultant for several industrial projects and startups, including computer vision algorithms for multiple smartphone applications, large-scale machine learning in the cloud, EMR software for streamlining workflows in bioinformatics labs that have yielded savings upwards of +$150K/yr, and NLP and data visualization tools for extracting insights from large unstructured text corpuses. WW is also the creator of wuriddles.com, an old but still popular archive of mathematical puzzles from 2002 with an active forum of +10,000 registered members.

Publications

Using Cloud Computing To Build Flexible Low-Cost Telecom Decoders. Wu, W.; Cheng, M.. NASA Spontaneous Research and Technology Development program, FY2012.
Discrete Sampling and Interpolation: Universal Sampling Sets for Discrete Bandlimited Spaces. Osgood, B.; Siripuram, A.; Wu, W. IEEE Trans. on Information Theory, vol. 58, no. 7, July 2012.
Global Cloud Cover for Assessment of Optical Satellite Observation Opportunities: A HyspIRI Case Study. Mercury, M.; Green, R.; Hook, S.; Oaida, B.; Wu., W.; Gunderson, A.; Chodas, M. Remote Sensing of Environment 126 (2012) 62-71.
A Fast Algorithm for Sparse Matrix Computations Related to Inversion. Li, S.; Wu, W. Accepted to Journal of Computational Physics on 3/9/2013.
Twenty Questions Games Always End With Yes. Wu, W.; Gill, J. JPL IPN Progress Reports, August 15, 2011.
Delay-Rate Tradeoﬀs for Ergodic Interference Alignment in the Gaussian Case. Koo, J.; Wu, W.; Gill, J. 48th Annual Allerton Conf. on Communication, Control, and Computing, Monticello, IL, Sept. 29 – Oct. 1, 2010.
Measurement-Based Channel Management in WLANs. Liu Y.; Wu, W.; Bo, W.. IEEE Wireless Communications & Networking Conference 2010.
100 Prisoners and a Light Bulb – Logic and Computation. Ditsmarch, H.; Eijck, J.; Wu, W. KR 2010 (Principles of Knowledge, Representation, and Reasoning).
Verifying 100 Prisoners and a Light Bulb. Ditsmarch, H.; Eijck, J.; Wu, W. JANCL 2010 (Journal of Applied Non-Classical Logics).
Falling Factorials, Generating Functions, and Conjoint Ranking Tables. Wu, W.; Osgood, B. Journal of Integer Sequences, Vol. 12, 2009, Article 09.7.8.
Dynamic Channel Assignment in Wireless LANs. Bo, W.; Wu, W.; Liu, Y. Power Electronics and Intelligent Transportation Systems (PEITS), 2008.

CV: William Wu

Computation Fluency

Languages:

C, C++, Python, Mathematica, MATLAB, Javascript

Packages:

OpenCV, GSL, scikit-learn, pandas, nltk, d3.js, cvx, MOSEK, numpy, boto

Databases: MySQL, MongoDB

Websites

wuriddles.com I wuism.net I github

Services

scientific computing I algorithm design I signal processing I image processing I machine learning I communications I tutoring and education

web programming I quantitative finance I math and optimization

JC

Co-Founder

Dr. Jiehua Chen (“JC”) received her B.Sc. in Math and Physics from Tsinghua summa cum laude, followed by an M.S. in Economics and Ph.D. in Statistics at Stanford. She has extensive experience in spatial-temporal statistics, randomized experiment design, and juxtaposing modern machine learning methods with more traditional statistical models. She has been working on development projects since 2008 and is passionate about finding proofs for problems that matter for all people, particularly in agriculture and human health.

Jiehua Chen

Dr. Jiehua Chen (“JC”) received her B.Sc. degree in Mathematics and Physics from Tsinghua, summa cum laude, followed by the M.S. in Economics and the Ph.D. in Statistics at Stanford. She has extensive experience in spatial-temporal statistics, randomized experiment design, and juxtaposing modern machine learning methods with more traditional statistical models.

JC has worked as a statistician in many non-profit and for-profit institutions around the world. Her expertise lies in spatial-temporal modeling and remote sensing analysis, as well as the theoretical design of machine learning algorithms for large datasets. She has applied these techniques to a variety of socially and environmentally conscious research projects, most of which are related to improving life in developing countries. She has extensive international field experience, often abroad for many months at a time. Her interests also include applications of statistics to public policy and bioinformatics.

Publications

“Inﬁll asymptotics with unknown mean function.” Jiehua Chen. Submitted to Statistica Sinica. (2012)
“Rao-score test for spatial correlation.” Jiehua Chen and David Siegmund. Under revision for Journal of Statistical Planning and Inference. (2012)
“Reducing intimate and paying partner VAW who exchange sex in Mongolia.” Susan S. Witte, Toivgoo Aira, Marion Riedel, Jiehua Chen, Catherine Carlson. To appear in The Journal of Interpersonal Violence. (2011).
“Multi-sector intervention to accelerate reductions in child stunting: an observational study from nine sub-Saharan African countries.” Roseline Remans et al. To appear in The American Journal of Clinical Nutrition. (2011).
“Adjusting survey weights using multilevel modeling: a case study of jatropha adoption in Mali.” Matt Basinger, Jiehua Chen, Frances Jeﬀrey-Coker, F. S. Rodriguez-Sanchez, Tim Singer, Vijay Modi. To appear in Agroforestry Systems, (DOI 10.1007/s10457-011-9426-z) (2011).
“Reducing sexual HIV/STI risk and harmful alcohol use among female sex workers in Mongolia: A randomized clinical trial.” Susan S. Witte, Batsukh Altantsetseg, Toivgoo Aira, Marion Riedel, Jiehua Chen, Katie Potocnik, Nabila El-Bassel, Elwin Wu, Louisa Gilbert, Catherine Carlson, Hanfei Yao. To appear in AIDS and Behavior (DOI: 10.1007/s10461-011-9984-0) (2011).
“Testing institutional biomass cookstoves in rural Kenyan schools for the Millennium Villages Projects.” Edwin Adkins, Jiehua Chen, Jacob Winiecki, Peter Koinei, and Vijay Modi. Energy Policy, 14, 3, 186–193, 2010.
“Comparative analysis of REML and ML estimation in spatial statistics.” Jiehua Chen. Joint Statistical Meeting Proceedings, August 2007.
“Regression models with spatially correlated residuals: applications to urban core growth in China.” Jiehua Chen. PhD Thesis, Statistics Department, Stanford University (2008).