I am a PhD candidate in Industrial Engineering and Operations Research at UC Berkeley working with Professor Anil Aswani. I obtained my Bachelor’s degree in Industrial Engineering at Pontificia Universidade Catolica do Rio de Janeiro, Brazil. My research is focused on the interplay between control, learning and optimization, with emphasis on autonomous systems, such as self-driving vehicles, satellites, and robots. In particular, I study optimization algorithms and statistical learning techniques that are able to provide safe and efficient real-time operation of such systems.
I have work experience in both prototyping (Python, Matlab) and developing production-level code (C, C++) of embedded algorithms for real-time applications, including nonlinear, hybrid, and stochastic systems, as well as a patent on an efficient algorithm for Model Predictive Control based on second-order methods. In Spring 2020, I designed and served as the lead instructor for IEOR 265 - Learning and Optimization, a graduate level course at UC Berkeley which covers theory and algorithms for approximate dynamic programming, deep reinforcement learning, and learning-based model predictive control (LBMPC).
I have collaborated with Professor Ram Vasudevan at Univertisy of Michigan and with researchers Rien Quirynen and Stefano Di Cairano at Mitsubishi Electric Research Laboratories MERL.
My CVPhD in Industrial Engineering and Operations Research, 2020
University of California Berkeley
MS in Industrial Engineering and Operations Research, 2015
University of California Berkeley
BSc in Industrial Engineering and Operations Research, 2010-2014
Pontificia Universidade Catolica do Rio de Janeiro
(Instructor)
(Teaching Assistant)
Math Programming I (IEOR 262A, Fall 2018): https://atamturk.ieor.berkeley.edu/ieor262a/
Engineering Statistics, Quality Control, and Forecasting (IEOR 165, Spring 2018): http://ieor.berkeley.edu/~ieor165/
Service Operations Design and Analysis (IEOR 151, Fall 2017): http://ieor.berkeley.edu/~ieor151/
Learning and Optimization (IEOR 265, Spring 2017): http://ieor.berkeley.edu/~aaswani/teaching/SP17/265/
Marshall-Oliver-Rosenberger Fellowship Award - granted by the Industrial Engineering and Op- erations Research Department at University of California Berkeley. (link)
Outstanding GSI Awards - granted by the Industrial Engineering and Operations Research Depart- ment at University of California Berkeley. (link)
Outstanding Graduate Student Instructor 2019 - granted by the Graduate Division of University of California Berkeley. (link)
ENGIE Brazil Innovation Prize - granted by ENGIE Group for the development of the HERA software.
PUC’s Academic Performance Premium - granted by Pontical Catholic University of Rio de Janeiro to students with the highest GPA.
Medal Graca Couto - granted by the Military School of Rio de Janeiro to the student with the highest academic performance of the school.
Medal Thomaz Coelho - granted by the Military School of Rio de Janeiro to the student with the highest GPU during all years during highschool.
Surrogate Optimal Control for Strategic Multi Agent Systems Professor S. Shankar Sastry semiautonomous group at UC Berkeley.
A Structure Exploiting Branch-and-bound Algorithm For Mixed-integer Model Predictive Control INFORMS Annual Meeting, Seattle, WA, 2019.
Statistically-Consistent Identication of Switched Linear Systems INFORMS Annual Meeting, Seattle, WA, 2019.
Surrogate Optimal Control for Strategic Multi-Agent Systems 58th IEEE Conference on Decision and Control, Nice, France, December 11-13, 2019.
Statistical Watermarking for Networked Control Systems Annual American Control Conference, Milwaukee, USA, June 27-29, 2018.
Newton Jacobian Updates for Nonlinear Model Predictive Control Annual European Control Conference, Lymassol, Cyprus, June 12-15 2018.
Family-Personalized Dietary Planning with Temporal Dynamics Annual American Control Conference, Milwaukee, USA, June 27-29, 2018.
Dynamic Watermarking for General LTI Systems 56th IEEE Conference on Decision and Control, Melbourne, Australia, December 12-15, 2017.
Deterministic Approximation Algorithm For Population-Scale Personal Dietary Management INFORMS Computing Society Conference, Austin, TX, 2017.
Deterministic Approximation Algorithms For Population-scale Personal Dietary Management INFORMS Annual Meeting, Nashville, TN, 2016.