About me
I'm a Ph.D. student at the University of Toronto and Vector Institute for Artificial Intelligence.

My research interests are lossless data compression, information theory, and AI. Data sources usually have some type of structure, such as graphs and sets. This means we can compress them better by taking this structure into account during compression. Unfortunately, existing methods that do this are either sub-optimal (don’t achieve the Shannon bound) or computationally intractable. I’m interested in building computationally efficient compression algorithms that can be used with deep generative models on structured data, as well as their connections to bayesian methods.

Originally, I am from Florianópolis (Brazil) but I’ve lived in New Jersey, Orlando, Toronto (now), São Paulo, as well as other smaller cities in the south of Brazil.

Previously, I interned at Facebook AI Research (FAIR) with Karen Ullrich in the summer of 2021.

I spend more time than I should on Twitter.

Check out my CV (last updated: June/2022).

I’ve joined Google AI as a Student Researcher with Lucas Theis and Johannes Ballé.
I’m accepting invitations to speak at conferences, workshops, and academic events in general.

Selected Publications and Preprints #

For a complete list, please see my Google Scholar profile.

  • Data-driven Optimization for Zero-delay Lossy Source Coding with Side-Information
    Elad Domanovitz, Daniel Severo, Ashish Khisti, Wei Yu
    International Conference on Acoustics, Speech, & Signal Processing (ICASSP), 2022

  • Compressing Multisets with Large Alphabets
    Daniel Severo*, James Townsend*, Ashish Khisti, Alireza Makhzani, Karen Ullrich
    Data Compression Conference (DCC), 2022
    [arXiv] [code] [tweet 1] [tweet 2] [slides]

    This paper was also presented as
    Your Dataset is a Multiset and You Should Compress it Like One
    Best Paper Award at NeurIPS Workshop on DGMs, 2021

  • RCAQ: Regularized Classification-Aware Quantization
    Daniel Severo, Elad Domanovitz, Ashish Khisti
    Biennial Symposium on Communications (BSC), 2021
    [arXiv] [code]

  • Improving Lossless Compression Rates via Monte Carlo Bits-Back Coding
    Yangjun Ruan*, Karen Ullrich*, Daniel Severo*, James Townsend, Ashish Khisti, Arnaud Doucet, Alireza Makhzani, Chris J. Maddison
    Long talk at International Conference on Machine Learning (ICML), 2021
    [arXiv] [code] [tweet] [video]

  • Predicting Multiple ICD-10 Codes from Brazilian-Portuguese Clinical Notes
    Arthur D Reys, Danilo Silva, Daniel Severo, Saulo Pedro, Marcia M Sá, Guilherme AC Salgado
    Brazilian Conference on Intelligent Systems (BRACIS), 2020
    [arXiv] [code]

    * Equal contribution

Awards #

Vector Scholarship in Artificial Intelligence Recipient, 2020-21

The Vector Scholarship in Artificial Intelligence supports the recruitment of top students to AI-related master’s programs in Ontario. Valued at $17,500 for one year of full-time study at an Ontario university, these merit-based entrance awards recognize exceptional candidates pursuing a master’s program recognized by the Vector Institute or who are following an individualized study path that is demonstrably AI-focused.


NSERC Applied Research Rapid Response to COVID-19 Grant, 2020

Our project titled “Canadian Hospital Simulator For Management of COVID19 Cases and Contact Tracing” was awarded $75,000.00.


Virtual Design Challenge Winner, 2019

Won 1st place at the VDC hosted by The University of British Columbia with my paper Proof of Novelty. Received a cash prize of $ 3,000.00.


Student Merit Award & Medal, 2015
Graduated with the highest GPA ever obtained (at the time) for my major. Elected ”Best Student” by the faculty of Electrical & Electronics Engineering at the Federal University of Santa Catarina
Science Without Borders Scholarship, 2013
Awarded a full scholarship that covered tuition, transportation, necessary materials and living costs to study 2 academic semesters at the University of Toronto.

Talks and Media #

You may reach me at