Marcos M. Raimundo
Professor of Machine Learning and Optimization
Institute of Campinas - University of Campinas
Biography
Marcos M. Raimundo is an Assistant Professor at University of Campinas (UNICAMP), in the Institute of Computing (IC). He is also a faculty member of the REasoning for COmplex Data laboratory (Recod.ai). His research interests includes Machine Learning, Multi-objective Optimization, Ethical AI, Mathematical Programming.
Interests
- Machine Learning
- Multi-objective Optimization
- AI Ethics
- Mathematical Programming
Education
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PhD in Computer Engineering, 2018
School of Electrical and Computer Engineering - University of Campinas
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MS in Computer Engineering, 2014
School of Electrical and Computer Engineering - University of Campinas
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BSc in Computer Engineering, 2011
University of Campinas
Recent Publications
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(2021).
Mining Pareto-Optimal Counterfactual Antecedents With A Branch-And-Bound Model-Agnostic Algorithm.
Preprint.
(2021).
CriPAV: Street-Level Crime Patterns Analysis and Visualization.
IEEE Transactions on Visualization & Computer Graphics.
(2021).
Exploring multiobjective training in multiclass classification.
Neurocomputing.
(2020).
An extension of the non-inferior set estimation algorithm for many objectives.
European Journal of Operational Research.
Experience
Adjunt Professor
Institute of Computing - University of Campinas
Responsibilities include:
- Teaching of Computing and Machine Learning for Computer Science and Engineering.
- Research and Graduate Students advising.
- Extension Programs.
- Administrative Roles.
Adjunt Professor
Federal University of Rio de Janeiro
Responsibilities include:
- Teaching of Statistics and Operations Research for Production and Gas Engineering.
- Research and Graduate Students advising.
- Extension Programs.
- Administrative Roles.
Postdoctoral Researcher
School of Applied Mathematics - FGV
I developed a project analysing criminality in São Paulo and Rio de Janeiro using Machine Learning, Visualization and Optimization tools. I created a interpretability tool for machine learning that creates counterfactual scenarios (when you change the variables to change the prediction of a learning machine) that reduces criminalities on regions of São Paulo and Rio de Janeiro, this tool was created using combinatorial optimization and machine learning. To deal with multiple counterfactual antecedents for multiple regions we created a visualization tool that helped finding counterfactual scenarios for multiple, similar, regions and also to understand which counterfactual scenarios are more promising in reality.
Data Scientist
Tech - Inovação Tecnológica para a Agropecuária
Responsibilities include:
- Data Analysis.
- Optimization Modeling.
- Staff training in Machine Learning.
- Software Engineering.
Research assistant
University of Campinas
This position was one of my roles in the Masters and Ph.D. courses. I researched many fields, including operations research applied to inventory and vehicle routing management, multiobjective optimization, machine learning applied to detection of epileptic seizures and ant genera identification, as well as an application of multiobjective optimization in multi-class and multi-label classification, transfer learning, multi-task learning, and multi-view learning.
Contact
- mraimundo at ic dot unicamp dot br
- Av. Albert Einsten, 1521, Campinas, SP 94305
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Monday 10:00 to 12:00
Wednesday 10:00 to 12:00