Bio | Portfolio | In the Media | Personal Interests
This a highlight reel of the products I’ve designed and built. I made this catalog for as much you as for my own record-keeping. These projects span web, mobile, and hardware.
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Table of Contents:
Currently building a text-based adventure game powered by GPT-4
Designed & coded a GPT & DALL-E AI Superhero Generator web app. ****
Coded a command-line LLM-Powered AI-Code-Documenter.
An all-knowing AI chatbot that builds hack-a-thon and start-up teams based on compatible interests and skills.
Designed & coded software that enables organizers to throw 1000+ participant virtual events over a phone hotline.
Designed & coded a Google Docs alternative that uses votes to determine which edits go live. ****
Built prototypes of an electronic wearable designed to measure daily hugging behavior.
Designed & coded the prototype of a location-and-relationship-aware contacts app.
Designed & coded the winning app submission to the 2014 PCORI App Challenge, which enables researchers and patients to co-design participatory research studies.
Designed a digital health platform which enables people with Crohn’s & Colitis to get support and contribute their data towards collective medical knowledge.
Designed & coded prototypes of a mobile app that enables users to chat with those around them.
Coded front-end web implementations of design mock-ups.
Designed & coded a social network and co-housing ops software for Delta Upsilon fraternity. Won DU International’s best website award*.* ****
Projects for which I don’t have portfolio pages:
TI-PROGS
Designed, coded, & distributed TI-83+ apps (utilities & games) online.
1000MEMORIES
Coded web features enabling the upload, management, and display of photos and video. ****
WORLD CLASS SHOWS
Designed & coded a marketing website and credit card payment flow.
OPENPPRN
Designed & directed an open-source project, allowing anyone to launch an online patient-powered-research-network. ****
DAPLIE
Coded a blockchain contract to manage a federated network of network-attached-storage devices. ****
AIRSPEED
Designed & coded a prototype microcontroller to measure & publish wifi speeds of AirBnBs. ****
I am currently building a text-based adventure game powered by GPT-4. I’m building it in React & Node. While it’s not yet ready for release, here’s the Development Preview Link. To start, you’ll need to log in with the authorization provider of your choice. Note I earlier named the app TextRPG.
I built Hero.Rodeo, a web app that uses OpenAI’s GPT and DALL-E to generates superhero “trading cards” from simple user prompts. It generates amazing heroes from prompt text consisting of animals, fantasy characters, creatures, and objects! Try it Out!
I built it using Python, Flask, TailwindCSS, Amazon S3, and OpenAI’s GPT and DALL-E API. I designed the UX on the fly as I developed. One thing I noticed early on in user testing is how much near-instantaneous joy people got from the app. They provided an animal, eg. “squirrel”, and then seconds later “Master Nutcracker the Squirrel” appeared. When I user-tested in social settings, users would often turn to their friends to show them what they just made. This learning helped me see the value of enabling the heroes that others had created to be shared and discovered by others.
I gave each hero a unique shareable link and added navigation that allows users to flip through a gallery of “hero trading cards” in the catalog.
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I worked with Tyler Neylon on coding a GPT script that automatically augments files of code with AI-generated code documentation.
It currently runs as a command-line tool which runs through your code, inserting GTP-generated python docstrings into your files and functions.
https://github.com/tylerneylon/add_docstrings
As an input argument, provide a file containing undocumented code.
Mark is the all-knowing super-connector who knows everybody present at your hack-a-thon, their skills, interests, project ideas, and need for teammates. He can suggest highly compatible team compositions, naming the project, each member and their area of contribution. You can ask him innumerable questions to get matched with the right people to work on your project idea.
Mark uses Retreival-Augmented-Generation (RAG) via a vector database and GPT4 to store the DevPost profiles of all the participants at your hack-a-thon, and query them like the all-knowing super-connector he is. I built this as a team of one, a solo hack-a-thon entrant, for the RAG Hackathon on 2/5/24 in Santa Clara, CA sponsored by LLamaIndex.
Out of the 50+ projects demo’d, this project got the only full-audience-spontanenous-ovation, earning it the unofficial audience-choice award.
My inspiration to build this came from the fact that the hack-a-thon itself was not well-set-up to allow people who arrived not yet having a team to find and join teams to build projects for the hack-a-thon. So, somewhat cheekily, I decided to make my project be the solution to the problem I had, which was not having an efficient mechanism to be match-made with other developers who wanted to work on a particular problem, and had the skills to develop it with me. Therefore, I built that exact thing, somewhat aptly, as a team of one.
Crohnology was a digital health platform designed to support individuals living with Crohn's disease (which I have) and Ulcerative Colitis, each chronic inflammatory bowel diseases. At our peak, we grew to 30K patients (1% of the US population with the condition), purely through word-of-mouth and member-invites.
I designed, coded, and then raised funding and built a team to create Crohnology. I served as our product/engineering lead switch-hitting between coding, leading the team, and guiding product strategy.
Crohnology is a fusion of a social network and PHR (personal health record). It served as an online community and resource hub that empowered patients by providing a space for sharing experiences, insights, and information related to these conditions. Crohnology enabled users to track and manage their symptoms, medications, and overall health through interactive tools and personalized tracking features. The data contributed by members on Crohnology played a vital role in powering research and medical discoveries related to Crohn's disease. By voluntarily sharing their experiences, symptoms, treatments, and outcomes, members provided valuable real-world data that was analyzed and utilized by researchers to better understand the diseases. Researchers can leverage this information to identify trends, patterns, and factors that may influence disease progression or treatment response.
The initial idea for Crohnology came from my own personal experience with Crohn’s, coupled with meeting and swapping treatment stories with other patients. I organized a support group in San Francisco for other patients with the disease. It was clear to me that we, as patients, had a lot we could learn from each other, if we only had a health platform with rich enough tools to accurately and succinctly record our experiences. I set out to build those tools.
I seeded my prototype with the fifty-or-so support members of my support group. Using this early test group, I held in-person user testing and feedback sessions. I iterated on these learnings. I launched my prototype on Hacker News; it was #2 on the front page for a day.
An inspirational new user journey through Crohnology: a newly diagnosed patient can find others with Crohn’s or Colitis in his/her city, learn about the treatments are working for patients, and record his/her progress as he/she tries new treatments, ultimately to get better and help others.
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As the product grew, paying attention to product strategy was crucial. Some key insights came during this time: sticky usage was fueled strongly by our highly arbitrary 1-100 user self-assessed health meter. It drove engagement because it could tell somebody’s health story in a snapshot, and we could inform friends of that user that their friend’s health has improved or fell, driving more engagement.
But what drove long term value was the deeper information we gathered from patients, such as the user’s health history, current medications and symptom status, and answers to questions asked by other users. For most our users, it is too much information to give in a single user session. So we needed ways to break down that information gathering across multiple sessions, across small points of engagement that might have simply come because the user was emailed they received a message from a user on the site.
At the same time, we had pharmaceutical companies and research organizations reaching out to us to either recruit for clinical trials, or to have our patients fill out their market or clinical research surveys. We seized these opportunities in the simplest way at first (advertising these opportunity to our users over email). However, I soon saw the opportunity to make these offerings native into the app itself: something that provided value directly in the product.
Inspired by the revenue source we found in helping organizations get their surveys answered, I designed a “question card” interface. Almost like Tinder in its simplicity, users would be presented a question. After selecting or writing an answer, they were presented with another. A score let them know how much info they contributed. The questions came from a variety of sources around the site. “How’s your health today” could be followed by “Have you ever taken X medication?”. If that answer was a “yes”, we might follow up with asking for how long they took the medication and how it worked for them. We next might interject a question from a research survey. We build a model behind this for each user which predicted the most value-add questions we could ask at any given point.
The result of this, is that we now had a powerfully working engine for feeding in any data request from users, including arbitrary surveys, which worked in a bite-sized fashion in short user sessions on web or mobile. It doubled the average number of data points we had collected for each active user. It also drove up our active user percentage. It simplified business development because we knew we could get the data asked by any research deal, and in fact, many times already had many of their questions answered. It also simplified new feature development, because we had a tool to bootstrap data into any new feature we built. We didn’t have to figure out “Okay now how are we going to get users to provide that data?”.
As Crohnology grew, I was fortunate to forge a partnership with the CCFA and the University of North Carolina. Together, we received a grant to put the power of Crohnology towards full-fledged clinical research with a national community of medical researchers. We built out tools for patients to directly collaborate on designing research and contributing to it. We built out a researcher application for researchers to interface with opt-in contributed data.