There's a lesson here, and I'm not going to be the one to figure it out.


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My name is Apo and I’m a mighty pirate

Educated in several acronyms across the globe (UNISR, SFI, MIT), I was co-founder and CTO of Tooso, a NLP / IR startup in San Francisco acquired by TSX:CVO.

I led Coveo’s A.I. and MLOps roadmap from scale-up to IPO, and built out Coveo Labs, an applied R&D practice rooted in collaboration (e.g. Stanford, Outerbounds, Netflix, Farfetch, Microsoft, NVIDIA), open source and open science.

I’m a proud NLP advisor for Plural, and Adj. Professor of ML at NYU, which is mostly notable because it is the only job I ever had that my parents (sort of) understand.

I recently started investing in tech startups, both directly and as LP in AI funds: I’m always happy to chat with founders about DataOps, MLOps and AI.

I’m now building Bauplan.

Where is my mind?

I occasionally share code, ideas and teaching materials; if you have no intention of selling me anything, you can also try me on Linkedin.

I talk a lot, and I’m sometimes invited to do so by friends in industry (e.g. Home Depot, Lowe’s, Farfetch, eBay, NVIDIA, Pinterest) and research (e.g. keynotes at KDD, SIRIP, RecSys): some of my talks and papers are highlighted at the end of this page.

Research-y stuff

My recent research sits at the intersection of language, learning and retrieval, with a recent drift towards data processing.

I am co-organizer of SIGIR eCom (2022, 2023), EvalRS (2022, 2023), Industry Sponsorship Chair for CIKM 2022, and I’ve been in the program committee for many conferences (COLING, ECONLP, ECNLP, EMNLP, ACL, SIRIP). My work has been presented in venues such as NAACL, WWW, RecSys and Nature journals: our paper on cognitively-inspired query embeddings won the Best Paper Award at NAACL 21.

As a true SFI alumnus, I am an old-fashioned generalist, and I gave tiny contributions to other fields mostly as a way to spend more time with old friends: data systems, logic and computation, cellular automata, computational social sciences, networks, philosophy of mind, political science.

Old stuff

In previous lives, I managed to get a Ph.D., simulate a pre-Columbian civilization, document biases in national elections and give an academic talk on videogames. Some of my improbable “achievements” received ample press coverage in national outlets.

Having built end-to-end data and ML pipelines at garage, growth and IPO scale, I happily shared all my mistakes in a series of articles that introduced the concept of Reasonable Scale.

Some time before Brad Pitt’s movie, I led one of the first attempts of running sophisticated analytics for a professional basketball team, and spearheaded the first data science effort on Milan’s bike-sharing service (no bikers or bureaucrats were harmed during the project).

About this page

The content of are released under the BY-NC-ND license; my chibi has been designed by the incredibly talented wisesnail.

Last update: August 2023.


Quick links to some selected projects, talks, papers, datasets.

Open source projects



Datasets and data challenges

Aside from research and tutorials, our datasets have been successfully used by dozens of master students to defend their thesis at Tillburg University and Politecnico in Milan.