معرفی
Hernan Makse is a Distinguished Professor of Physics at the City College of New York (CCNY), affiliated with the Levich Institute and Department of Physics. He directs the Complex Networks and Data Science Lab, pioneering research in statistical physics approaches to complex systems. His work bridges brain networks, biological synchronization, social media dynamics, and granular materials.
Research Focus: Makse's lab develops emergent laws for complex systems using statistical mechanics, network theory, and machine learning. Key areas include:
- Brain network optimization via Collective Influence algorithms for neural integration and control
- Symmetry fibrations in biological systems (e.g., C. elegans connectome)
- COVID-19 contact tracing through superspreader k-core analysis
- Election/fake news forecasting via Twitter data mining
- Granular matter phase transitions and jamming physics
Publication Trends: His recent articles focus on network-based prediction systems (elections, pandemics), neural synchronization mechanisms, and AI-driven solutions for biological and social systems. Earlier foundational work established fractality and renormalization in complex networks.
Awards & Honors:
- Elected Member, Academia Brasileira de Ciencias (2023)
Academic Leadership: He mentors PhD students in physics/data science and collaborates with Memorial Sloan Kettering (brain tumors), University of Vienna (neural symmetry), and Brazilian health agencies (COVID apps). Grants include NSF-CRCNS and NIH Brain Initiative funding.
Lab Initiatives: The lab develops open-source tools for COVID-19 contact tracing and neural symmetry analysis. Current projects include MRI-based breast cancer prediction and neurotransmitter dynamics modeling.
