What We Do
Senior research leadership without a full-time hire. Monica embeds with your team to set research direction, mentor scientists and engineers, prioritize workstreams, and serve as the scientific voice in product and strategy conversations. Particularly suited to early-stage AI, data infrastructure, and privacy-tech companies navigating the gap between research and product.
Translating scientific uncertainty into structured, executable plans. This includes scoping research questions, identifying methodological approaches, sequencing work against business or publication timelines, and defining what "done" looks like. Grounded in experience taking research from whiteboard to shipped product at Snowflake and CryptoNumerics.
Hands-on research across several interconnected domains, bringing both theoretical rigor and practical product experience to each:
Applying quantum mathematical formalism to model ambiguity, perception, and meaning in ways classical probability cannot capture — with implications for world models, grounded language learning, and creative AI systems.
Design and evaluation of differential privacy, synthetic data, k-anonymity, and secure multi-party computation systems.
Research and prototyping in synthetic tabular data generation, including evaluation frameworks for fidelity, utility, and appropriate use cases.
Design and implementation of numerical models integrating diverse data sources, with depth in hydrodynamic simulation and large-scale scientific computation.
Bridging the gap between domain experts, data teams, and engineering. Monica has extensive experience turning unclear client problem statements into precise technical requirements — and translating complex research concepts back into product-aligned specifications. Available as a standalone engagement for organizations struggling with misalignment between what scientists produce and what engineers can build.