👨‍💻 What I'm working on

I build products that make the world a better place.

Most recently I've been working with my friend and co-founder Albert Wang on Comend. We build tools for the rare disease community to help them become research ready.

I drink a lot of 🍵 and enjoy the culture. I'm building Teatico, an encyclopedia of tea products with my girlfriend Ramy Zhang.

I release original piano compositions on YouTube and Spotify.

📚 What I've worked on

Comend - Co-founder and CTO

Feb 2023 - Present - Toronto, Canada

• Built and launched our core platform, helping patient groups organize, share, and find partners for their research.
• Built and launched Librarey, a search platform to help rare families find resources.
• Grew the team to 4 and onboarded over 50 patient groups with over 140 research plans (and counting).
• Lead engineering efforts across all products, coordinated workloads, managed tickets, built E2E and unit testing suites, organized monorepo and project architecture, monitored deployments and containers.
• Raised over $700K in pre-seed funding to date from Character Labs, Drive Capital, and PharmStars.

Entrepreneur First (EF) - Founder in Residence

March 2022 - Feb 2023 - Toronto, Canada

• Went through the formal process of finding strong co-founder fit and identifying problems worth solving and having useful customer conversations.
• Iterated on many ideas through many rounds of product validation with several potential cofounders.
• Got very comfortable with sales tools like LinkedIn Sales Navigator, Apollo.io, Klenty, and Reply.io.

Kebotix Inc. - Machine Learning Developer Intern

Sept 2020 - May 2021 - Boston, MA

• Developed a generative Transformer model optimized with a genetic algorithm for discovering organic and inorganic molecules of interest.
• Contributing author of "Molecular discovery with conditional generative transformers coupled with genetic algorithms" (unpublished).

Relation Therapeutics - Machine Learning Research Intern

Sept 2019 - May 2020 - London, UK

• Developed novel GNN models for predicting the druggability and classifying the types of proteins.
• Built tuning and testing pipeline to optimize model parameters and run configurations.
• Contributing author of "Sparse Dynamic Distribution Decomposition: Efficient Integration of Trajectory and Snapshot Time Series Data".

ML for Chem/Bio-informatics - Personal Projects

Oct 2018 - June 2019 - Toronto, Canada

• Built a series of pipelines for preprocessing several chemical and biological data assays.
• Built various predictive, multivariate, and generative, ML models to train on processed data.
• Wrote a series of articles on the various methods of Geometric Deep Learning and Graph Learning.

Canadian Imperial Bank of Commerce (CIBC) - Summer Intern

June 2018 - Sept 2018 - Toronto, Canada

• Summer intern at CIBC Live Labs as front end developer and designer for an AR app.
• Designed basic UI/UX for app, collaborated with backend developers throughout development.
• Performed user/guerrilla testing of prototype and aggregated feedback for improvements.

📜 Publications

Sparse Dynamic Distribution Decomposition: Efficient Integration of Trajectory and Snapshot Time Series Data

Jake P. Taylor-King, Cristian Regep, Jyothish Soman, Flawnson Tong, Catalina Cangea, Charlie Roberts

DDD allows for the fitting of continuous-time Markov chains over these basis functions and as a result continuously maps between distributions. The number of parameters in DDD scales by the square of the number of basis functions; we reformulate the problem and restrict the method to compact basis functions which leads to the inference of sparse matrices only -- hence reducing the number of parameters.

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