I occasionally consult on interesting projects. For an overview of my professional experience and research training, please see my CV.
To explore a potential collaboration, the ideal starting point is a brief overview of your project, details on specific challenges, and what you think is needed to accelerate progress or unblock an issue. Feel free to reach out at [monicaspisar] at [gmail dot com].
Software engineering
AI / machine learning
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 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 engineering & analysis
Data transport, storage, and analysis are all in my wheelhouse. I’ve worked with off the shelf tools and have done custom builds of data pipelines to meet efficiency, privacy, and cost objectives.
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.
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
A high level overview of my time at the University of Oxford - where I built and managed a longevity bioscience research portfolio - can be found in my post Hedging bets on healthier aging. It 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 image capture (hardware) and image processing/generation (software).
In 2017, I wrote about AI in medical imaging; despite the date, a decent proportion of the post remains relevant.
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.