Profile
Research Assistant Professor at Northwestern University’s Kellogg School of Management and the Center for Science of Science & Innovation. Researcher, data scientist, and developer with expertise in dynamic complex networks, machine learning, science of science, computational social science, and interactive visualization. Creator of Helios Web and author of 60+ publications, with 2,600+ citations and an h-index of 23 on Google Scholar. Ph.D. in Computational Physics with a strong interdisciplinary focus bridging physics, computer science, biology, and the social sciences.
Appointments
- Research Assistant Professor, Center for Science of Science & Innovation, Kellogg School of Management, Northwestern University, 2025–present
- Associate Research Scientist, Observatory on Social Media, Indiana University, 2023–2025
- Assistant Research Scientist, Indiana University Network Science Institute, 2019–2023
- Postdoctoral Fellow, São Carlos Institute of Physics, University of São Paulo, 2015–2019
- Visiting Research Scholar, Indiana University Bloomington, 2017–2018
Education
- Ph.D. in Physics, Computational Physics, São Carlos Institute of Physics, University of São Paulo, 2015
- M.Sc. in Physics, Computational Physics, São Carlos Institute of Physics, University of São Paulo, 2009
- B.Sc. in Physics, Computational Physics, São Carlos Institute of Physics, University of São Paulo, 2006
University of São Paulo is ranked #1 in Latin America in the Times Higher Education Latin America University Rankings 2026.
Dissertation received a university-level Honorable Mention, ranking among the top three theses in the exact sciences.
Selected projects
- Scientific and engineering discovery: Combining science-of-science evidence, structured extraction pipelines, network analysis, embedding-based search, and domain knowledge to identify promising scientific and engineering opportunities.
- Technology capability maps: Developing embedding models that represent design choices and technical attributes across papers and patents, predict technological capabilities, and identify interpretable directions aligned with measurable progress in materials and device platforms.
- Graph and language models of scientific impact: Comparing random-walk embeddings, transformer representations, and graph-retrieval methods to model scientific impact, research similarity, and scholarly trajectories.
- Mapping how science is funded: Linking funding acknowledgments to organizations and publications to study how different forms of support shape research directions.
- Helios Web: Browser-native visualization and exploration of large networks and embedding spaces. GitHub
Browse the full project portfolio.
Grant writing and funded projects
- APTO: Global Observatory and Virtual Laboratory for Science and Technology, National Science Foundation, Senior Personnel, 2024–2026. Contributed goals, methodology, data integration, and analytical strategy during proposal development for the $7.5M funded program.
- Integrative Study of Local Microbiome Function in Chronic Rhinosinusitis, National Institutes of Health, Senior Personnel, 2024–2027. Contributed network-methods conceptualization and writing during development of the funded proposal.
- UPSCALE: Universal Population Segmentation and Characterization Algorithms for Online Environments, DARPA, Researcher, 2023–2024. Participated in the funded program and developed computational and network methods for large-scale online environments.
- A National Network for Critical Technology Assessment: A First-Year Pilot, National Science Foundation, Senior Personnel, 2022–2023. Participated in the funded pilot and contributed technology-assessment and science-of-science methods.
- Science Genome: A Scholarly Graph Embedding Framework, U.S. Department of Defense Minerva Research Initiative, Researcher, 2020–2024. Participated in the funded program and developed network and embedding representations of science.
Research areas
Network science; science of science; complex systems; artificial intelligence and machine learning; computational social science; scientific and engineering discovery; graph and text embeddings; interactive visualization; community detection; information science; biological, climate, political, and urban networks.
Selected teaching and mentorship
- Instructor, INFO-I 590: Data Visualization, Luddy School of Informatics, Computing, and Engineering, Indiana University, Spring 2025; in person. A project-based course connecting visual perception and design to exploratory analysis, multidimensional data, maps, text and embeddings, networks, interaction, and web deployment using Python and JavaScript. Course site · Materials
- Instructor, INFO-I 513: Usable Artificial Intelligence, Luddy School of Informatics, Computing, and Engineering, Indiana University, Spring 2025; online. An applied introduction to data preparation, regression, classification, clustering, evaluation, feature selection, explainability, natural-language processing, embeddings, and responsible use of large language models in practical Python workflows. Course site · Materials
- Guest lecturer on complex-network visualization at the University of São Paulo.
- Graduate and undergraduate research supervision in network visualization, embedding analysis, large-language-model interfaces, and scientific software.
- Google Summer of Code mentor for Helios/FURY projects under the Python Software Foundation, 2021–2023.
Selected service
- Academic editor for PLOS ONE and PeerJ.
- Reviewer for journals and conferences spanning network science, information science, complex systems, computational social science, and physics.
- Organizer of tutorials and workshops for IC2S2, ISSI/CADRE, and the Indiana University Network Science Institute.
- Contributor to open research infrastructure including Helios Web, OSoMe tools, brainlife.io network apps, Scholarometer, and FURY.
Technical skills
Python, JavaScript, C/C++, Objective-C, WebGPU, WebGL, OpenGL, WebAssembly, parallel processing, large-scale data pipelines, network analysis, community detection, scientific visualization, natural-language processing, machine learning, graph and text embeddings, PyTorch, TensorFlow, transformer models, and LLM APIs.
Languages
Portuguese (native); English (fluent).
Profiles
Website · GitHub · Google Scholar · ORCID · OpenAlex