About

Hello! I am Antonio Fonseca. Engineer, Neuroscientist and Rock Climber.

I am a 4th-year Neuroscience Ph.D. student at Yale. My work is at the intersection between Computational Neuroscience and Machine Learning. Currently, I am interested in using Deep Learning to model brain dynamics in mesoscopic calcium imaging data and what it can tells us about cognition and behavior. I am advised by David Van Dijk, Ph.D. and I work closely with Jess Cardin, Ph.D. Previously, I worked on software development for mining robots and solutions for banking companies. Most recently, I worked on applying machine learning and signal processing techniques to investigate behavior in developing animals in the laboratory of Marcelo Dietrich, Ph.D. I am also a mentor to Brazilian students through the Iniciativa Proxima program, where we seek to foster the next generation of scientists for the betterment of our communities and society.

Basic Information
Email:
antonio.fonseca@yale.edu
Phone:
+1203-691-0675
Address:
New Haven, Connecticut, U.S.A
Language:
Portuguese, English
Experience
Publications
  • Dong, M; Wang,B.; Wei, J.; Fonseca, A. H. de O.; Perry, C.; Frey, A.; Ouerghi, F. et al. "Causal identification of single-cell experimental perturbation effects with CINEMA-OT." Nature methods (2023) (accepted)
  • Fonseca, A. H. de O.; Zappala, E.; Caro, J. O., & van Dijk, D. Continuous Spatiotemporal Transformers. In Proceedings of the 40 th International Conference on Machine Learning (2023).
  • Zappala, E.; Fonseca, A. H. de O.; Caro, J. O. & van Dijk, D. Neural Integral Equations. arXiv preprint (2023)
  • Zappala, E.*, Fonseca, A. H. de O.*, Moberly, A. H.; Higley, M. J.; Abdallah, C.; Cardin, J. & van Dijk, D. Neural integro-differential equations. In Proceedings of the AAAI conference on artificial intelligence (2023).
  • Perrenoud, Q.; Fonseca, A. H. de O.; Airhart, A.; Bonanno, J.; Mao, R.; Cardin, J. A. Flexible perceptual encoding by discrete gamma events. bioRxiv preprint (2022).
  • Fonseca, A. H. de O.; Santana, G. M.; Ortiz, G. M. B.; Bampi, S.; Dietrich, M. O. Analysis of ultrasonic vocalizations from mice using computer vision and machine learning. Elife 10 (2021): e59161.
  • Fonseca, A. H. de O., & van Dijk, D. "Learning aligned embeddings for semi-supervised word translation using Maximum Mean Discrepancy." arXiv preprint arXiv:2006.11578 (2020).
  • Zimmer, M. R.; Fonseca, A. H. de O.; Dai Pra, R.; Dietrich, M. O. Functional ontogeny of hypothalamic Agrp neurons in neonatal mouse behaviors." Cell 178.1 (2019): 44-59.
  • Fonseca, A. H. de O. & Zana, Y. Automated visual insect tracking for statistical measurements. Poster Presented at the Third Brazilian Meeting on Brain and Cognition, Federal University of ABC, São Bernardo do Campo – SP, Brazil 2015. Article published in annals of event (complete).
  • Fonseca, A. H. de O.; Toledo, M. A.; Helena, A. F.; Zana, Y. Simultaneous tracking of dozens of objects. Oral presentation in the VIII Computational Vision Workshop, Goiânia – GO, Brazil. 2012. Article published in annals of the event (complete)
  • Fonseca, A. H. de O.; Zana, Y. Visual Automatic Quantification of Freezing Response in Rats: Development of a Graphical User Interface. First Brazilian Meeting on Brain and Cognition, 2010, Santo André – SP, Brazil. 2010.
Press Coverage
  • A new software for USV analysis (2021) at Nature
  • Researchers Demonstrate a New Approach to Learning Integral Equations from Data (2023) at Yale News
  • Teaching
    Lecturer
    Teaching Assistant
    • Department: Computer Science - Yale University (2022,2023)
    • Course: Current Topics in Applied Machine Learning
    • Duties: Advising students (assingments, final projects), grading and guiding discussions
    Teaching Assistant
    • Department: Computer Science / Neuroscience - Yale University (2021)
    • Course: Advanced Computational Vision
    • Duties: Advising student presentations, grading and guiding discussions
    Lecturer and Teaching Assistant
    • Department: Interdepartmental Neuroscience Program - Yale University (2021)
    • Course: Data Analysis Boot Camp
    • Duties: Advising student presentations, teaching basics of Matlab and Github.
    Lecturer
    Teaching Assistant
    • Department: Interdepartmental Neuroscience Program - Yale University (2020)
    • Course: Data Analysis Boot Camp
    • Duties: Advising student presentations, teaching basics of Matlab.
    Lecturer
    • Organizer: Spatial Ecology - Basilicata University, Matera, Italy (2019)
    • Course: Geocomputation and Machine Learning for environmental applications
    • Duties: Grading final projects, teaching Neural Networks algorithms.
    Education

    2019 - current

    Doctoral Degree
    Ph.D. Neuroscience

    Yale University – CT, USA

    Awarded by the CAPES-Yale Graduate Scholars Program for the full extension of the PhD program.

    2017 - 2019

    Master's Degree
    M.Sc. Microelectronics

    Federal University of Rio Grande do Sul – RS, Brazil

    Awarded a Master Sandwich Fellowship from CAPES for two years at Yale University to receive training in behavioral neurosciences (July 2017 – June 2019).

    2009 - 2015

    Bachelor's Degree
    Bachelor of Automation, Instrumentation and Robotic Engineering

    Federal University of ABC – SP, Brazil

    Awarded a Science Without Borders Scholarship for one year and a half at Laurentian University (ON, Canada) to attend classes and gain experience in internship.

    2009 - 2012

    Bachelor's Degree
    Bachelor of Science and Technology

    Federal University of ABC – SP, Brazil

    Contact Me
    Feel free to contact me

    Address

    New Haven, Connecticut, U.S.A

    Phone

    +1203-691-0675

    Email

    antonio.fonseca@yale.edu