I lead the Graphing & Search teams at Datadog. I also teach at CUNY Graduate Center. Before: I studied design at Parsons, built healthcare products at Arcadia, and studied engineering at Brown. I live in Queens, New York.
I lead the Graphing & Search teams at Datadog, a group of 80 engineers and 5 PMs responsible for Datadog’s most-used products: dashboards, notebooks, SQL, spreadsheets, and search.
We’re building:
My initial focus at Datadog was Data Visualization and Querying. I started by creating more expressive data analysis tools. In parallel, I studied how customers move through an investigation. As my understanding in this space matured in my first year at Datadog, I developed a vision for how to automate investigation.
In year two, I conceived and shipped the first step towards my vision for automated investigation: Watchdog Explains. In near-realtime, this feature automatically detects anomalies on dashboards, and picks apart the exact dimensions, and code changes contributing to the anomaly. Watchdog Explains is reliable for triage: it runs quickly, meets users in their natural investigation flow, and shows strong recall. It is now widely used by humans and agents.
As LLMs matured, we moved beyond triage to automating root cause analysis. The challenge then became: how do we meet the user in their workflow, build trust, and gradually change their approach to investigation? We shipped automated investigation on dashboards, which shows evidence and next steps for solving issues across the stack.
Through this work, I saw how agents struggle with information retrieval and contextual grounding. I built out the Search team to address those gaps, focusing on agentic search tooling.
I teach Creative Computing at CUNY Graduate Center, where grad students learn to use code for creative expression. I love watching researchers, artists, and designers discover code as both a way of thinking and a creative medium. Their skepticism about how technology is deployed, and who it serves, pushes me to examine my own assumptions about what I build and its consequences.
After years of building interactive art with code outside of work, I wanted to push my practice further. I went to Parsons Design School to study computational design and data visualization.
My thesis at Parsons, How We Gaze, was a gallery of gazes: it distorts art to reflect how the viewer looks at it in realtime. How We Gaze was selected as a winner for the Pudding Cup, an independent data visualization award. Snippets of this project and others below.
I still continue my creative practice, most recently on back2back, a music discovery engine derived from human curators.
I started my career at Arcadia, a healthcare tech startup. I got my hands dirty, learning to design, code, model data, and pitch new product ideas.
At Arcadia, I launched two enterprise workflow products from 0 to $XM: Care Manager and Referrals (press). In building Arcadia Referrals, I translated the complex decision trees that referral administrators work with into a deterministic, simple product. For Care Manager, I worked to automate risk stratification and patient outreach, freeing nurses to focus on caring for patients. Both products went on to become core to Arcadia's suite.