CV

Contact

Email: raonilourenco@proton.me

Interests

Artificial Intelligence
Responsible Data Science
Data Management
Pipeline Debugging
Automated Machine Learning
Big Data
Industry 4.0 and 5.0

Education

09/2015 – 05/2020: Ph.D. in Computer Science, New York University, Tandon School of Engineering, New York, USA
- Thesis: Debugging Science: algorithms and systems to debug computational pipelines
- Advisor: Juliana Freire
02/2011 – 07/2013: Master’s in Information Engineering, Federal University of ABC (UFABC), Santo André, Brazil
- Dissertation: Augmented Television: inserting mixed reality into SBTVD by interactive applications
- Advisor: Celso Kurashima
05/2002 – 06/2007: Bachelor’s in Computer Science, Federal University of Amazonas (UFAM), Manaus, Brazil
- Conclusion Project: A translator from SUO-KIF to PROLOG
- Advisor: Virgínia Brilhante

Professional Experience

02/2023 – Current: Research Associate
- University of Luxembourg/Snt (Interdisciplinary Centre for Security, Reliability and Trust), Luxembourg, Luxembourg
- Data Management, Industry 4.0, Predictive Maintenance
December 2021 – January 2023: Senior Backend Developer
- Accern, New York, USA
- Developing NLP models, taxonomies, and knowledge graphs
June 2020 – December 2021: Postdoctoral Research Associate
- New York University, New York, USA
- Research on the inclusion of Fairness metrics for AutoML systems; enhanced artifacts developed for the DARPA D3M program and transitioned them into sustainable, open-source products
September 2015 – May 2020: Research Assistant
- New York University, New York, USA
- Researched approaches to synthesize, debug, and optimize machine learning and other computational pipelines
March 2020 – March 2020: Research Intern
- SAP Labs, Levallois-Perret, France
- Applied Ph.D. research on Pipeline Debugging to analytical data pipelines in a proprietary distributed environment
June 2017 – August 2017: Summer Research Intern
- Nokia Bell Labs, Murray Hill, USA
- Research on Elastic Data (Bayesian Optimization, Distributed Databases)
June 2016 – August 2016: Summer Research Intern
- Nokia Bell Labs, Murray Hill, USA
- Research on Elastic Data and Distributed Databases
February 2010 – June 2015: Researcher
- TPV R&D Center, Jundiai, Brazil
- Led technical teams, supervised outsourced partners, developed embedded systems
- Keywords: Embedded Linux, Digital Television Technologies, Test Suites, SmartTV applications, Scrum
June 2009 – February 2010: Development Specialist
- Samsung Research Institute, São Paulo, Brazil
- Developed embedded systems using Java DTV (Xlet) and Digital Television Technologies
June 2008 – May 2009: Software Engineer Intern
- Siemens Corporate Research, Princeton, USA
- Developed desktop software and performed integration tests (J2SE, Software architecture, UML)
August 2007 – May 2008: Systems Analyst
- inTera Technology, Manaus, Brazil
- Developed embedded systems (C++, C#)
November 2004 – November 2006: Programmer
- Paulo Feitoza Foundation, Manaus, Brazil
- Developed desktop software (Java, mobile technologies)

Skills

Research Areas
- Data Management and Debugging
- Machine Learning Pipeline Optimization
- Automated Machine Learning (AutoML)
- Explainable AI (XAI) and Trustworthiness
- Industry 4.0 and Predictive Maintenance
- Data Provenance and Pipeline Synthesis
Programming Languages
- Python, Java, C++, C#
Technologies & Tools
- Embedded Systems, Linux
- Distributed Databases
- NLP Models and Knowledge Graphs
- Software Architecture and Testing
Languages
- Portuguese (C2 - Native)
- English (C2 - Fluent)
- French (B2 - Upper Intermediate)
- Italian (B2 - Upper Intermediate)

Publications

Towards Trustworthy Human-Centered Manufacturing: A Decision Support Tool for {Model x Explainer} Selection

Benguessoum, K., Lourenço, R., Kubler, S., & Le Traon, Y. (2026). "Towards Trustworthy Human-Centered Manufacturing: A Decision Support Tool for {Model x Explainer} Selection." AAAI International Workshop on Addressing Challenges and Opportunities in Human-Centric Manufacturing.

Counterfactual Explainable AI (XAI) Method for Deep Learning-Based Multivariate Time Series Classification

Cetina, A. P., Benguessoum, K., Lourenço, R., & Kubler, S. (2026). "Counterfactual Explainable AI (XAI) Method for Deep Learning-Based Multivariate Time Series Classification." The 40th Annual AAAI Conference on Artificial Intelligence (Main track).

Through the Lens of Explainability: Enhancing Trust in Remaining Useful Life Prognosis Models

Benguessoum, K., Lourenço, R., Bourel, V., & Kubler, S. (2024). "Through the Lens of Explainability: Enhancing Trust in Remaining Useful Life Prognosis Models." International Conference on Flexible Automation and Intelligent Manufacturing, Springer, Cham.

Decision support model for time series data augmentation method selection

Joubaud, D., Kubler, S., Lourenço, R., Cordy, M., & Le Traon, Y. (2024). "Decision support model for time series data augmentation method selection." IEEE Access.

AlphaD3M: An Open-Source AutoML Library for Multiple ML Tasks

Lopez, R., Lourenço, R., Rampin, R., Castelo, S., Santos, A. S. R., Ono, J. H. P., Silva, C., & Freire, J. (2023). "AlphaD3M: An Open-Source AutoML Library for Multiple ML Tasks." AutoML Conference (ABCD Track).

BugDoc: Iterative Debug and Explanation of Pipeline Executions

Lourenço, R., Freire, J., Simon, E., Weber, G., & Shasha, D. (2022). "BugDoc: Iterative Debug and Explanation of Pipeline Executions." VLDB Journal.

DataPrism: Exposing Disconnect between Data and Systems

Galhotra, S., Fariha, A., Lourenço, R., Freire, J., Meliou, A., & Srivastava, D. (2022). "DataPrism: Exposing Disconnect between Data and Systems." ACM SIGMOD.

BugDoc: A System for Debugging Computational Pipelines

Lourenço, R., Freire, J., & Shasha, D. (2020). "BugDoc: A System for Debugging Computational Pipelines." ACM SIGMOD (demo).

BugDoc: Algorithms to Debug Computational Processes

Lourenço, R., Freire, J., & Shasha, D. (2020). "BugDoc: Algorithms to Debug Computational Processes." ACM SIGMOD.

Debugging Machine Learning Pipelines

Lourenço, R., Freire, J., & Shasha, D. (2019). "Debugging Machine Learning Pipelines." ACM SIGMOD Workshop on Data Management for End-to-End Machine Learning.

Automatic Machine Learning by Pipeline Synthesis using Model-Based Reinforcement Learning and a Grammar

Drori, I., Krishnamurthy, Y., Lourenço, R. de P., Rampin, R., Cho, K., Silva, C., & Freire, J. (2019). "Automatic Machine Learning by Pipeline Synthesis using Model-Based Reinforcement Learning and a Grammar." ICML Workshop on Automated Machine Learning.

AlphaD3M: Machine Learning Pipeline Synthesis

Drori, I., Krishnamurthy, Y., Rampin, R., Lourenço, R. de P., Ono, J. P., Cho, K., Silva, C., & Freire, J. (2018). "AlphaD3M: Machine Learning Pipeline Synthesis." ICML Workshop on Automated Machine Learning.

Open-Source Systems

BugDoc
- Code: https://github.com/VIDA-NYU/BugDoc
- Video: https://youtu.be/RJrcZByP_Os
AlphaD3M
- Code: https://gitlab.com/ViDA-NYU/d3m/alphad3m

Service and leadership

2026 – Current: Program Committee Member – Research Track
- IEEE International Conference on Big Data (BigData)
2026 – Current: Program Committee Member – Research Track
- AAAI/ACM Conference on AI, Ethics, and Society (AIES)
2021 – Current: Program Committee Member – Research Track
- International Conference on Management of Data (SIGMOD)
2024: Reviewer – Special Edition
- Very Large Data Bases (VLDB) Journal
2021 – 2022: Program Committee Member – Short Paper Track
- Conference on Information and Knowledge Management (CIKM)
2021 – 2022: Program Committee Member – Research Track
- Very Large Data Bases (VLDB) Conference
2021 – 2022: Program Committee Member
- International Conference on Extending Database Technology (EDBT)

Awards and Honors

eLife Innovation Leaders Mentorship – 2020
Provost Global Research Initiative Fellowship – NYU Paris, Spring 2020
Provost Global Research Initiative Fellowship – NYU Paris, Fall 2018
Science Without Borders Scholarship – Full Ph.D. (CNPq - Brazil)

Raoni Lourenco

CV