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.
- 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.
- Organizer: Spatial Ecology - Basilicata University, Matera, Italy (2022,2023)
- Course: Geocomputation and Machine Learning for environmental applications
- Duties: Grading final projects, teaching Unsupervisd learning algorithms.
- Department: Computer Science - Yale University (2022,2023)
- Course: Current Topics in Applied Machine Learning
- Duties: Advising students (assingments, final projects), grading and guiding discussions
- Department: Computer Science / Neuroscience - Yale University (2021)
- Course: Advanced Computational Vision
- Duties: Advising student presentations, grading and guiding discussions
- Department: Interdepartmental Neuroscience Program - Yale University (2021)
- Course: Data Analysis Boot Camp
- Duties: Advising student presentations, teaching basics of Matlab and Github.
- Organizer: Spatial Ecology - Stockholm University, Stockholm, Sweden (2021)
- Course: Geocomputation and Machine Learning for environmental applications
- Duties: Grading final projects, teaching Unsupervisd learning algorithms.
- Department: Interdepartmental Neuroscience Program - Yale University (2020)
- Course: Data Analysis Boot Camp
- Duties: Advising student presentations, teaching basics of Matlab.
- Organizer: Spatial Ecology - Basilicata University, Matera, Italy (2019)
- Course: Geocomputation and Machine Learning for environmental applications
- Duties: Grading final projects, teaching Neural Networks algorithms.
2019 - current
Yale University – CT, USA
Awarded by the CAPES-Yale Graduate Scholars Program for the full extension of the PhD program.
2017 - 2019
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
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
Federal University of ABC – SP, Brazil
Address
New Haven, Connecticut, U.S.A
Phone
+1203-691-0675
antonio.fonseca@yale.edu