Hi! My name is Luda.
I'm a software engineer + builder currently based in New York City. I'm interested in using software to tackle interdisplinary problems in a variety of real-world contexts.
I'm currently working at Instagram, where I work on products for creators + small businesses. Previously, I worked at Sidewalk Labs, building software to re-imagine urban planning through computational approaches. I also did stints at Airbnb and Stanford, where I got to build cool things with some great people.
Love to chat to anyone about interesting ideas over coffee or tea, so drop me a line (Linkedin)!
Here is a smattering of interesting past projects I've worked on before!
I was a tech lead at Sidewalk Labs, the urban technology offshoot of Google. Delve is a generative design tool used by architects, urban planners, and real estate developer to discover, compare, and optimize prospective master plans. The product was used in over 30+ cities across 4 continents to generate, evaluate, and compare potential city district plans. I learned a lot about real estate development, TypeScript, and building eB2B businesses.
I helped spun up the first version of the Airbnb Things to Do vertical, which aimed to provide Airbnb guests with relevant travel points of interests, sourced straight from local hosts + insiders. Iterated quickly and learned a ton about growth, SEO, user-generated content. Click on the pic to see an example of a live page (as of 2023) on the website!
In collaboration with the British Library, we explored how we can apply Convolutional Neural Networks to aid art history research. Using transfer learning, we provided over new 20 million annotation tags to a dataset of over 1 million book illustrations from the 1500s to the 20th century, which allowed art historians and researcher to better search and categorize these illustrations. We presented this project in London for the 2016 British Library Labs Competition in front of ~300 researchers and got great feedback!
We used open-source GIS data to build a road network model of San Francisco and applied graph network analysis to evaluate the traffic impact of potential pedestrian/bike conversions. What's the point? It's a quantitative case study on the impact of “re-humanizing” city centers by converting motor ways into pedestrian and bike-only roads.
A rendition of a classic board game I built in my spare time between classes, designed for simplicity. Supports single-play or multi-player over network modes.