Since 2021, I’ve been freelancing, contracting, and consulting with industry partners at the intersection of accessibility and data science. My favorite and most recent collaborations have included 2 years at Apple, 11 months with Adobe, a summer with Highsoft, 2 years with Quansight and Bokeh, and 2 years with Fizz Studio.

My mission has been to help businesses, non-profits, government orgs, and even policymakers make data more accessible for everyone, specifically focusing on accessibility for people with disabilities.

In my past work, I’ve helped organizations in a freelance R&D role: evaluating the accessibility of existing products, tools, and workflows, developing short and long term strategies, building out new systems alongside engineers, training and educating existing employees, and facilitating co-design and user research with people with disabilities.

My industry collaborations have also helped advance the state of the art for the whole field, improving tools, techniques, and contributing our findings broadly.

Collab with me and my Lab!

Starting in Fall of 2026, I will join the faculty at Cal Poly SLO as an assistant professor of data science. Part of my position involves a few important privileges that enable me to continue my industry collaborations, through my lab:

Call for new collaborations:

For my first 3 years, I would love to collaborate with partners in the following areas:

  1. Open source data science accessibility: improving data tools, products, libraries, and techniques.
  2. Government, educational, or non-profit orgs with datasets intended for public access or who are looking to establish accessibility policy/guidelines for data, analytics, or visualizations.
  3. Video game, 3D graphics, museum, or physical/embodied artistic curations/archives where people with disabilities can interact with rich information in the context of play, entertainment, aesthetics, or fun-centered learning.

Are you interested in AI or how AI can influence your accessibility work? I am specifically interested in building infrastructural guidelines and systems, which lay beneath AI’s level of abstractions. This means that I am not nearly as interested in using or applying existing out-of-the-box models to do accessibility work as I am interested in producing new models, data, specifications, systems, architectures, and building blocks that enable programmatic, autonomous, and even “manual” human work.

As a metaphor, I’m more interested in building engines and roadways, not just driving cars. As an example, Chartability and Data Navigator (my two existing flagship projects) have informed fully-human, mixed, and fully-autonomous accessibility design and development projects. I’m interested in continuing this style of work.

Unsure if this is you, exactly? I highly recommend that you reach out to me anyway felavsky@calpoly.edu. I'd love to hear what you're up to.

Call for funding

I will be prioritizing collaborations that fit the mission of my lab and also are able to offer funding, either for my lab (as a grant or gift), directly for my time, or both. Unsure whether you have funding available? Don’t be shy! Reach out anyway. In past freelancing, I’ve helped teams find funding from within their own companies and also helped put together grant applications that can enable our work. Getting the conversation started is the key. And I would love to write some grants or find money to make our shared goals happen.

My time for collaboration is roughly as follows (these can be combined for larger projects, of course):

  1. [2 free slots per year]:
    1. 4 months of my time at 1 day/week (~125 hours). This is enough time for either: a med-scale accessibility eval, co-design + prototype development, or a full user study.
    2. 1-2 students supporting my work (when available/appropriate).
    3. (Optional): a write-up of our work, submitted as a short paper, workshop paper, or subpart of a larger ongoing paper.
  2. [1 free slot per summer]:
    1. 10 weeks of my time (~400 hours), which is enough time for 1 full R&D project, well-scoped.
    2. 1-2 students supporting my work (when available/appropriate).
    3. (Optional): a write-up of our work, submitted as a full paper to a major venue.

Why freelance?

I hope to build out a professional model of a professor who is also a R&D freelancer. Some do this, with varying degrees of success - but why would I, personally, want to do this?

Well, my ethos fits Cal Poly’s “learn by doing:” while pursuing my PhD in human-computer interaction, I practiced “action research.” My mission was simply to work with real teams of real people wrestling with real problems. Rather than “learn by doing” (with “learning” being local to myself), I focused on “knowing by doing:” using practical settings as a site for producing novel technologies, empirical understanding about human behavior, and advancing the state of the art in our existing techniques and systems.

From a pure research perspective, this approach is seen as a risky endeavor: “do everyday teams of designers and engineers offer enough novelty or opportunities to produce foundational knowledge?” Many researchers would rather design and control an environment that can clearly answer a posed hypothesis. But my work instead simply followed practical problems in applied settings; the research value came later.

Chartability, Data Navigator, Skeleton, and Softerware (4 of the 5 projects that comprised my thesis) all came about directly due to my work as a practitioner myself or being embedded with pracitioners. And while I wouldn’t recommend that everyone attempt an action research stance, if you have enough faith in the process, the contributions that researchers value eventually emerge from the work.

And the final reason that I’m interested in the professor-as-freelance-consultant path is that it offers me immense flexibility in collaborations and variety of funding sources, both of which are valuable to me as a primarily-solo researcher at a PUI, as well as in the US during a time of broad federal cuts to research. (What is a “PUI” institution? I unpack this, as well as why I chose Cal Poly, in a prior blog post.)

Different collaborators

I’m not just interested in external freelance-style collabs with folks who are willing to find funding. I’d also love to collaborate with other researchers and students, as well! If that’s you, read below:

Researcher-researcher collabs

I’m really looking at expanding the model of the mostly-solo PUI researcher into a model where I can either co-advise someone else’s student (perhaps yours, dear reader!) or simply offer my unique expertise to your current research venture.

What would I want in return? Well, co-authorship at a minimum! But I’d also love to work on grants together too. My student workers are highly affordable compared to other schools and places, and I’m also interested in looking at larger-budget grants that could enable me to hire a postdoc, research staff, or even research admin down the road. Perhaps you’d also like to share in this endeavor?

And as strange as might seem, I could be a “hired hand” (so to speak) in your research! Do you need help visualizing data effectively? My prior visualization work has won awards, and even appeared in the Nobel Lecture on Physics! Do you need help working on accessibility, with co-design, or running an HCI study for the first time? I’ve played that role before, too! I’m also happy to just serve as a more-senior paper editor/writer too. I’m quite a seasoned peer reviewer (7 of my 36 reviews during my PhD won awards or recognitions for their high quality).

Student collabs

Are you really skeptical of AI? Do you have reservations about the ethics of modern models: how they extract data, usurp jobs, threaten the environment, risk reducing human learning, can cause bias, produce slop, or demand significant energy? If so, great! Read on. I likely would not restrict a student from using or exploring machine learning or models (most of my work involves data, data science, and machine learning!). However, my work requires that my collaborators are highly aware of the shortcomings of models. I view skepticism as a strong trait in a student collaborator, perhaps the most important pre-requisite to get on my shortlist of students I’d like to work with.

As an advisor, I’m simultaneously highly inclusive and very selective with my student research assistants. What do I mean by this? Well, I don’t often expect students to have specific skills yet in order to work with me. And I’m also really encouraging of students who are historically excluded from higher ed and research environments (minority or under-represented, indigenous, gender non-conforming, non-male, disabled, and from a low-income background). That being said, I am highly selective when it comes to alignment of interests (see previous paragraph on AI as an example).

You will learn when you work with me. I expect that! But in order to learn, you’ll need to be willing to shift your frame of thinking. This means that you’ll need to be curious and willing to hear new perspectives (I am also willing to shift my frame of thinking, too!). But helping a student re-frame how they think about the ethics of technology, as well as what disability is, in addition to what the role of “knowledge production” is in a research environment, means that students who are more successful with me are the ones most willing to learn a new way of thinking about the world.

How do you get started working with me? At first, I’d love to build a relationship that is low stakes: you get a feel for the work I am currently doing and whether it fits with you, and then if you’re interested in collaborating on a concrete project or deliverable, we find a way to get you credit for a term. During this early phase, you can just have an introductory email or chat with me after class. If I’m hosting meetings with other students in the lab, you’re welcome to shadow and tag along, just make sure to send me an email and ask first.

Ideally, the next step is that we collaborate on a really well-scoped project that you can complete during a single semester and you get credit for this. A senior thesis project you lead, perhaps? Or it could be a project where you’re actively helping me with something I’m working on, but it’s for a class specific to hands-on project work. At this stage, the stakes are still pretty low: you’re only expected to do whatever you can in a semester. You’ll probably primarily be motivated by a grade at this point. Do well, you’ll get an A. Easy enough.

But after a first pass working together where you get credit, we can have a conversation about whether a paid research assistantship makes sense for our current work. Students that are interested in more than just a grade are the ones who I want to work with the most. This stage is ideal for me: I want students who are willing to continue work on a longer project! But at this point I’ll only be picking students who show strong initiative and there is either follow-up work to be done or we want to pursue a publication together (in which case, we want to write a paper, run a study, or more). Don’t worry if this seems intimidating, either! Ideally I’m helping you understand what all this means and whether you’d even be interested in giving it a try.

After this, we can even find additional ways to work together even more. But at that point, we can just have a conversation about what to do and how to pull it off.

In short: The ideal path? You shadow a bit, then get interested and get some credit to work with me for a semester. Your work is successful and there’s more to do. I bring you on as a paid assistant, perhaps for a summer. Then, you might have a senior thesis project you can get even more work done on. And the bonus round? Perhaps we find something exciting enough based on our work together that you pursue a master’s degree and want me to advise you on your thesis work.

If all goes well, I’d be happy to mentor the right student for 2-3 years or more! But the best part about this whole arrangement is that you’re never stuck with me or your work for longer than a semester at a time. If you wrap up our work together, you’re free to go and explore a new direction with another researcher.