Renan Souza, Ph.D.

Applied Scientist & Sr. Software Engineer | Data & AI Platforms for Edge-Cloud-HPC

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Summary

Tech lead, sr. software engineer, and research scientist of intelligent data and AI platforms to accelerate scientific discovery. With 15+ years at IBM, ORNL, SLAC, and UFRJ, I foster a user-centric system design by keeping experts in the development loop, rapidly translating abstract requirements from domains like Energy, Chemistry, Biology, and Climate into production-grade systems that are easier to operate, maintain, and scale. My research focuses on highly scalable, low-latency, observable, provenance- and metadata-first architectures that facilitate comprehensive data analysis across heterogeneous infrastructure, bridging edge instruments, cloud clusters, and leadership-class supercomputers, as well as data integration for SQL/NoSQL databases, knowledge graphs, messaging, streaming, and parallel file systems. My current focus includes AI/ML, LLM-driven, and agentic workflows. I authored 50+ papers, won best thesis and paper awards, held 10+ USPTO patents, and reviewed for major venues like IEEE TPDS, IEEE Big Data, IEEE eScience, FGCS, VLDB, and Supercomputing.

Areas of Expertise

  • AI/ML, LLM-driven, and Agentic workflows
  • Edge-Cloud-HPC Computing
  • Provenance-driven data analysis, lineage, and observability
  • Scalable data engineering (SQL, NoSQL, KGs, Streaming, Parallel File Systems)

Education

Federal University of Rio de Janeiro, Brazil

    Ph.D. in Computer Science | Sep 2015 — Dec 2019

        Thesis: Supporting User Steering in Large-scale Workflows with Provenance Data

    M.Sc. in Computer Science | Jan 2013 — Jul 2015

        Thesis: Controlling the Parallel Execution of Workflows Relying on a Distributed Database

    B.Sc. in Computer Science | Jan 2009 — Dec 2012

        Thesis: Linked Open Data Publication Strategies: An Application in Network Performance Data

    International experience:

        Visiting Ph.D. Student - Inria/Univ. Montpellier, France | Jan 2019 — Mar 2019

        Computer Science exchange student - Missouri State University, U.S. | Jun 2011 — Jun 2012

Experience

Oak Ridge National Laboratory Oct 2022 — Present

Staff Scientist & Sr. Software Engineer, HPC Workflows, Data & AI | Knoxville, USA

  • Led R&D on workflow provenance and observability for AI-driven science, focusing on transparency, reliability, and reproducibility in end-to-end workflows.

  • Developed provenance models and system mechanisms to connect user intent, agent decisions, workflow executions, and downstream results in unified traces.

  • Validated methods through real deployments spanning Edge-Cloud-HPC environments and interactive workflows that require low-latency, auditable responses.

  • Published and presented results in workflow and eScience venues, and drove community engagement through tutorials and reference architectures.

IBM Research Apr 2015 — Oct 2022

Staff Scientist & Sr. Software Engineer, Cloud, Data & AI | Rio de Janeiro, Brazil

  • Conducted applied R&D in data management and AI systems, producing peer-reviewed outputs and patented innovations.

  • Explored scalable data services and governance-aware approaches that support AI lifecycle requirements in enterprise contexts.

  • Collaborated internationally across research and engineering teams to validate ideas in real deployments and user scenarios.

SLAC National Accelerator Laboratory, Stanford University May 2013 — Dec 2014

Research Software Engineering Intern | Menlo Park, USA

  • Applied semantic web and scalable data management methods to publish structured measurement data for broad community use.

Federal University of Rio de Janeiro Jan 2010 — Sep 2014

Software Engineer (Intern → Engineer) | Rio de Janeiro, Brazil

  • Built applied semantic web and linked data solutions, grounding research ideas in real systems and user needs.

  • Early applied work on integrating heterogeneous data sources for analytics and reporting.

Petrobras May 2007 — May 2008

IT Intern | Rio de Janeiro, Brazil

  • Early industry experience in software delivery and operations.

Selected on-going Projects

American Science Cloud (AmSC)

AmSC integrates DOE computing and experimental facilities, high-performance networks, and data resources into a secure, federated environment for AI-ready datasets and model services. I design and implement multi-agent workflow frameworks within ORNL use cases and align them with platform APIs for cross-facility interoperability.

Orchestrated Platform for Autonomous Laboratories (OPAL)

OPAL seeks to create a network of autonomous laboratories that can learn and adapt by combining AI, robotics, and automated experimentation. I lead agentic AI systems that translate expert intent into HPC-scale execution and multimodal analytics, enabling human-in-the-loop discovery workflows.

Advanced Manufacturing into Leadership-class Supercomputers via AI Agents

A cross-facility system integrating a natural language interface, a multi-agent decision framework, programmable facility APIs, and provenance-aware infrastructure for adaptive and reproducible workflows. I led the multi-agent communication layer and dynamic steering mechanisms that connect decisions to actions across facilities.

Flowcept

Flowcept captures runtime provenance with low overhead and links tasks, lineage, telemetry, and AI-agent interactions into end-to-end traces for accountability and reproducibility. I created and lead the platform, which underpins multiple DOE cross-facility initiatives and current work on agentic provenance.

Technical Knowledge

  • Programming Languages: Python, Java, C, C++, C#, Shell, NodeJS, Scala, Lua

  • Data Science/ML: PyTorch, MLFlow, Airflow, Pandas, Polars, Jupyter, Matplotlib, Plotly

  • Agentic AI: MCP, CrewAI, LangChain, Streamlit, Chainlit, RAG, LLM-based orchestration

  • Big Data & Streaming Platforms: Apache Spark, Dask, Kafka, Redis, RabbitMQ

  • Parallel & Distributed Programming: MPI, OpenMP, CUDA, PubSub

  • Cloud, HPC, DevOps: Kubernetes, OpenShift, Docker, Slurm, LSF, PBS; CI/CD GitHub Actions, Jenkins, Travis; Grafana

  • Databases & Knowledge Graphs: PostgreSQL/PostGIS, MySQL, MongoDB, Elasticsearch, HBase, Hive, Redis, LMDB, Polystores; AllegroGraph, Jena, Virtuoso, RDF, SPARQL, OWL

Grants and Awards

  • ORNL performance award for top performers (2025).

  • Best paper award at WORKS@Supercomputing for the paper The (R)evolution of Scientific Workflows in the Agentic AI Era: Towards Autonomous Science (2025).

  • LDRD-funded project leadership, managed near $2M and led 10+ researchers and developers (2023—2025).

  • IBM Patent Plateaus for high-impact software and data innovations (8+ USPTO patents) (2020, 2021).

  • SBBD Honored Mention for the Best Ph.D. Thesis Award (2021).

  • Early Academic Honors: SBBD Best M.Sc. Thesis and CAPES International Science Grant (2012—2017).

Teaching and Supervisions

Courses

  • Databases Laboratory (UFRJ), 2017. Teacher assistant to Prof. Marta Mattoso

  • Logics for Computer Science (UFRJ), 2012—2013. Teacher assistant to Prof. Mario Benevides

Supervisions

Scientific Community Service

  • IEEE Transactions on Parallel and Distributed Systems - Reviewer

  • Future Generation Computer Systems - Reviewer

  • Concurrency Computation Practice and Experience - Reviewer

  • Journal of Parallel and Distributed Computing - Reviewer

  • The Very Large Databases (VLDB) Journal - Reviewer

  • IEEE Transactions on Big Data - Reviewer

  • Journal of Cloud Computing - Reviewer

  • Computer Physics Communications - Reviewer

  • Discover Data - Reviewer

  • Frontiers in High Performance Computing - Reviwer and Editorial Board

  • International Workshop on AI Principles in Science Communication (AISC) - PC

  • International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD’25) - PC

  • Workflows in Distributed Environments (WiDE’24) - PC

  • IEEE/ACM Supercomputing (SC’24) - PC

  • IEEE International Conference on e-Science (eScience’23) - Session Chair, PC

  • Workflows in Support of Large-Scale Science (WORKS’20, 21, 23, 24, 25) - PC

  • Brazilian Workshop on Database and Artificial Intelligence Integration - PC

  • Brazilian Symposium on Databases (SBBD’20, 23, 24, 25, 26) - PC, Session Chair

  • Brazilian e-Science (BreSci’26) - PC

  • Innovation Summit on Information Systems (at SBSI’19,20) - PC

Badges and Certifications

Languages

  • English: Full professional proficiency

  • Portuguese: Native

  • Spanish: Reading fluent; speaking/listening intermediate

Publications and Events

For all publications and patents, visit renansouza.org/publications.

For all events participation, visit renansouza.org/events.