Occasionally, I consult on interesting projects. You’ll find brief outlines of my areas of expertise below. To explore a potential collaboration, please get in touch via email.
To speed things, feel free to forward a brief project overview identifying current challenges and what’s required to accelerate progress or unblock an issue. I’ll be happy to take a look and set up an initial discussion.
For additional details of my professional experience and research training, please see my CV.
Software engineering
AI / LLMs / ML ops
My personal and professional interests in AI are strongly focused on responsible applications of machine learning, and I prioritize work related to technical AI safety and reliability.
I have expertise in model development and fine tuning, dataset preparation/evaluation, and ML ops. With experience running my own businesses and iterating on product design to get startups to product-market fit, I have practical insights on where deploying AI may make sense. Equally usefully, I can help identify where AI is unlikely to be the right approach.
Interested in a compact overview of the foundations of artificial neural networks? My post on the design of neural networks has you covered.
Data science & signal processing
More traditional data science skills are also in my roster of tools, and academic training in advanced probability & statistics during my PhD program strengthen those skills. My PhD research also leaned heavily on signal processing of medical imaging datasets to facilitate image reconstruction, and I have both academic and practical experience in the field.
Data engineering & observability
Data transport, storage, and analysis are all in my wheelhouse, and I’ve been the lead on a data migration of a live and mission-critical database. I’ve worked with off the shelf tools and have done custom builds of data pipelines to meet efficiency, privacy, and cost objectives for transactional, client usage, and observability data.
Software applications
My recent software engineering experience has been focused on backend compute and (cloud based) infrastructure. I also have some networking and front end experience.
I particularly enjoy working at the edge of my abilities, and am adept as transferring my skills to challenges in new fields. You’ll find a list of my core software skills and technologies, plus example personal projects, on my CV.
Hardware & electronics
Optical and acoustic imaging systems
As a medical imaging systems researcher, I gained hard-won intuition and practical experience with lasers and optical elements, as well as custom electronics for laser tuning and output stabilization, feedback-controlled detector positioning, and signal capture. Ditto for medical ultrasound test systems for piezoelectric transducers and positioning systems (synthetic arrays), and acoustic signal generation and capture. I designed and built several such systems from scratch.
Domain-specific expertise
High resolution medical ultrasound imaging: optical (laser-based) generation/detection
I worked at the bleeding edge of medical ultrasound imaging research for 7+ years. Specifically, optoacoustic array detection of ultrasound at frequencies and device scale suitable for high resolution medical imaging. These techniques fall under the umbrella of laser based ultrasound, where the piezoelectric elements typically used for ultrasound transduction are replaced by components responsive to both acoustic and optical signals. I also led research developing microfluidics vascular models for ultrasound imaging of angiogenesis, which can be a tumor growth indicator.
A brief overview of my PhD research is included on the Publications page.
Drug discovery for longevity interventions
From early 2019 to mid-2021, I built and managed a longevity bioscience research portfolio at the University of Oxford. A high level overview “Hedging bets on healthier aging” touches on longevity research, drug discovery, and academic project/portfolio management. Beyond what’s covered in that post, I gained significant knowledge and expertise specific to clinical trial design for longevity interventions.
Medical imaging + AI in radiology
I keep up with advances in AI in medical imaging/radiology, and have extensive expertise to draw on for signal generation and image capture (hardware) as well as image processing/generation (software).
In 2017, I wrote Picture Perfect: AI + Medical Imaging for a general audience. Despite the date, a decent proportion of the piece remains relevant.
Jeff Fessler (one of my professors in grad school) works on the cutting edge of ML in medical imaging and his numerous papers on arXiv and talks are excellent resources. An Introduction to Score Based Generative Models is a great place to start exploring Jeff’s work for a deeper dive on using AI in medical imaging.
Bridging industry & academia
I spent a number of years working in roles that involved crafting project proposals and agreements between academic research groups and industry. Tremendous value can be found in such collaborations, but they can be tricky to set up for success. I’ve resolved dozens of stalemates to unblock the path - I speak the language on either side, and understand both institutional and commercial/corporate constraints.
Entrepreneurship and business operations
During graduate school, I was on a startup team at the very earliest stages of commercializing a research prototype low-dose radiation, small-footprint CAT scanner. Our team participated in Joshua Coval’s “Idea to IPO in 14 weeks” course at the University of Michigan business school, building a business plan and pitching VCs. Ultimately, the startup team received an SBIR grant for close to $2M in two phases and evolved into a thriving venture. Xoran
I’ve also acquired and founded non-technical brick & mortar businesses, generally leading those teams alongside my primary career in technology and science. Over the course of a decade as CEO, I gained significant operations and strategy experience — including successfully leading a growing retail and wholesale operation through the challenges of the 2008 financial crisis.