We build solutions at the intersection of bits and atoms.
Edge Analytics is a boutique data science consulting company. Our PhD-level data scientists and engineers bring decades of experience in delivering elegant solutions to complex, ambiguous problems. We help our partners - who range from Fortune 500 companies to early-stage startups - turn their ideas into reality.
Relevant Work
On the cutting edge.
We specialize in data science, machine learning, and algorithm development both on the edge and in the cloud. We provide end-to-end support throughout a product’s lifecycle, from quick exploratory prototypes to production-level AI/ML algorithms.
Team
It’s in our DNA.
We are problem solvers by nature. We love breaking down problems and turning them into elegant solutions.
Alex Browne
Alex has a broad background with 10 years of experience in full stack software engineering, devops, and data science. After getting a dual degree in Electrical Engineering and Computer Science, he led major infrastructure projects at fintech company Plaid, and later at blockchain startup 0x. Alex created an experimental programming language called Fo (Functional Go).
Andrew Weitz, PhD
Andrew has worked on digital signal processing and time series analyses for over 10 years. At Stanford, he quantified brain dynamics using fMRI and worked on deep learning approaches for image processing. His work resulted in 8 high-impact peer-reviewed publications (1 cover story) and 1 patent for analysis methods.
Blayne Kettlewell, MS
Blayne was the lead hardware and embedded systems design engineer at Magnetic Insights. Previously, Blayne was the lead architect of an open source FPGA design (Trollstigen FPGA), which spanned from transistor-level design through implementation of a software toolchain to support programming the chip in Verilog.
Brinnae Bent, PhD
Brinnae completed her PhD on novel digital biomarkers of glycemic health at Duke. She was the lead software developer at the Digital Biomarker Discovery Pipeline (DBDP), as well as the maintainer of multiple open-source Python packages for analysis of wearable sensor data. Brinnae is an accomplished speaker as well as an avid runner who has competed in many ultra-races (50 miles, 24 hours, etc.).
Cherry Gao, PhD (Part-time)
Cherry used data science techniques and genetic engineering to study climate processes at MIT. Cherry designed her own fluorescent, single-cell biosensors and her PhD work was published in Nature Communications. Cherry spent 1.5 months living in Antarctica (and traveled across the roughest sea passage in the world to get there) as part of a research expedition.
Daniel Hensley, PhD
Daniel completed his PhD at UC Berkeley where he pioneered new signal encoding and reconstruction approaches in magnetic particle imaging (MPI). When a startup was spun out of the lab, Daniel became head of software and built the first production-ready software stack for the clinical scanner. Daniel’s work has resulted in 5 patents, multiple invited talks, and he is author/co-author on over 10 peer-reviewed publications.
Ken Jung, PhD
Ken has worked on machine learning and statistics for the past 30 years at multiple companies, including Genentech, Dana Farber, Stanford, and Stanford Hospital. At Stanford, Ken developed methods for using free text and structured data for risk prediction and causal inference. His work has resulted in over 60 peer reviewed publications and several patents. Ken lived in Korea, Canada, and Sudan before moving to the US.
Lina Colucci, PhD
Lina developed algorithms for a novel hydration sensor based on the same technology as MRI. This work resulted in 2 patents (algorithms + device) and the cover article of Science Translational Medicine. Lina completed her PhD at a joint program between MIT and Harvard. She has been a featured speaker at multiple SXSW and TEDx events. Lina is a ballerina who invented novel ballet pointe shoes and collaborated with Nike on the shoe design.
Ren Gibbons, MS
Ren has worked on a variety of computational problems, from improving 3D-printing processes at Stanford to electrical grid optimization at AMS. At AMS, Ren was a senior data scientist who developed algorithms controlling 50 MW of power (the equivalent of a town like Palo Alto) and, in the process, increased AMS’s revenue by $500k per month. Ren has run the Boston Marathon, the North Face 50-mile Ultramarathon, and hiked the Pacific Crest Trail from Mexico to Canada. * Left PhD program.
Sidney Primas, MS
Sidney was the technical lead for the team who commercialized the first wearable bioimpedance sensor at Jawbone. He was responsible for the heart rate algorithms from clinical validation to mass production (500k+ units). The work yielded 5 signal processing patents. At MIT, Sidney developed computer vision algorithms that could perform automated microscopic urinalysis. * Left PhD program.
Vasiliy Nerozin, MS
Vasiliy has worked on firmware, digital signal processing (DSP), and algorithms for the past 15 years. His work has spanned DSP for wearable health sensors at Jawbone, firmware for radio systems at NXP, and algorithms for fast in-browser compute at Datagrok. Vasiliy has spent the past 3-years building a two-story house entirely by himself (with an occasional extra pair of hands from his dad).
Blog
Turning ideas into reality.
In our blog, we share project reports, tutorials, and inspiration.
Testimonials
What others are saying about us.
We provide the highest level of expertise in machine learning, data science, and edge computing. And our clients agree!
Contact
Have a hard problem in mind?
Get in touch! We love meeting people who are tackling interesting problems that can change the world.
info@edgeanalytics.io