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Lead PI: Dr. Gabriel Perez
Lead PI: Dr. Gabriel Perez
Assistant Professor
Assistant Professor
Oklahoma State University
Oklahoma State University
School of Civil and Environmental Engineering
School of Civil and Environmental Engineering
Bio: Dr. Perez's research spans hydroclimate extremes, process-based modeling of hydrologic processes, extreme event statistics, hydro-geomorphological analysis, and flood risk management. His expertise includes high-performance computing, hydroclimate impact assessment, flood frequency analysis, remote sensing, machine learning, groundwater modeling, and hyporheic exchange modeling. Before joining OSU, Dr. Perez worked as a postdoctoral researcher at Oak Ridge National Laboratory & Climate Change Science Institute. Prior to that, he was a postdoctoral researcher at Vanderbilt University. He received his Ph.D. in Hydraulics and Water Resources from the University of Iowa, an M.S. in Water Resources Engineering, and a B.S. in Civil Engineering from the National University of Colombia at Medellin.
Bio: Dr. Perez's research spans hydroclimate extremes, process-based modeling of hydrologic processes, extreme event statistics, hydro-geomorphological analysis, and flood risk management. His expertise includes high-performance computing, hydroclimate impact assessment, flood frequency analysis, remote sensing, machine learning, groundwater modeling, and hyporheic exchange modeling. Before joining OSU, Dr. Perez worked as a postdoctoral researcher at Oak Ridge National Laboratory & Climate Change Science Institute. Prior to that, he was a postdoctoral researcher at Vanderbilt University. He received his Ph.D. in Hydraulics and Water Resources from the University of Iowa, an M.S. in Water Resources Engineering, and a B.S. in Civil Engineering from the National University of Colombia at Medellin.
Current Graduate Students
Current Graduate Students
Diego Osorio
Diego Osorio
PhD Student
PhD Student
Education:
MSc. Water Resources, University of Colombia, Medellin, Colombia, 2020.
BS. Environmental Engineering. University of Colombia, Medellin, Colombia, 2016.
Email: diego.osorio@okstate.edu
Diego is studying the motion—direction, speed, and trajectory—of extreme storm events and how these characteristics influence flood generation at the U.S. scale. He develops computational tools and data-driven methods to better understand the frequency and intensity of such events. His work combines storm tracking algorithms, extreme value theory, statistical hydrology, and machine learning, with a strong focus on analyzing large-scale, high-resolution rainfall datasets. Outside of research, Diego enjoys playing soccer, cycling, and hiking in the mountains.
Diego is studying the motion—direction, speed, and trajectory—of extreme storm events and how these characteristics influence flood generation at the U.S. scale. He develops computational tools and data-driven methods to better understand the frequency and intensity of such events. His work combines storm tracking algorithms, extreme value theory, statistical hydrology, and machine learning, with a strong focus on analyzing large-scale, high-resolution rainfall datasets. Outside of research, Diego enjoys playing soccer, cycling, and hiking in the mountains.
Kevin Blanco-Silva
Kevin Blanco-Silva
PhD Student
PhD Student
Education:
MSc. Water Resources and Environmental Engineering. Industrial University of Santander, Bucaramanga, Colombia, 2023.
BS. Civil Engineering. Francisco University of Paula Santander, Cucuta, Colombia, 2016.
Kevin is researching how urban hydrologic systems respond to land use change, population growth, and shifting climate patterns. His work focuses on water infrastructure—especially sewer networks—and how they perform under extreme conditions. Kevin uses computational tools, machine learning, and process-based modeling to develop Digital Twins that support the analysis and design of resilient urban systems. Outside the lab, he’s an animal lover who has rescued five cats, and enjoys walking, exploring nature, discovering new places, and cooking.
Kevin is researching how urban hydrologic systems respond to land use change, population growth, and shifting climate patterns. His work focuses on water infrastructure—especially sewer networks—and how they perform under extreme conditions. Kevin uses computational tools, machine learning, and process-based modeling to develop Digital Twins that support the analysis and design of resilient urban systems. Outside the lab, he’s an animal lover who has rescued five cats, and enjoys walking, exploring nature, discovering new places, and cooking.
Laura Torres-Torres
Laura Torres-Torres
PhD Student
PhD Student
Education:
MSc. Water Resources, University of Colombia, Bogota, Colombia, 2025.
BS. Civil Engineering. University of Colombia, Bogota, Colombia, 2021.
Laura is advancing large-scale flood modeling techniques, using state-of-the-art numerical methods to quantify extreme rainfall and produce flood maps. Her work combines radar and satellite rainfall data, stochastic storm transposition, extreme value theory, climate projections from Earth System Models, and process-based hydrologic modeling. In her free time, Laura enjoys reading, making puzzles, baking, and exploring new places.
Laura is advancing large-scale flood modeling techniques, using state-of-the-art numerical methods to quantify extreme rainfall and produce flood maps. Her work combines radar and satellite rainfall data, stochastic storm transposition, extreme value theory, climate projections from Earth System Models, and process-based hydrologic modeling. In her free time, Laura enjoys reading, making puzzles, baking, and exploring new places.
Arundhaty Mandal Oishi
Arundhaty Mandal Oishi
MSc Student
MSc Student
Education:
BS. Environmental and Geotechnical Engineering. Bangladesh University of Engineering and Technology, Bangladesh, 2021.
Email: arumand@okstate.edu
Arundhaty is researching how regional rainfall extremes are evolving in response to climate and environmental changes. She focuses on analyzing shifts in rainfall intensity, duration, and frequency through Intensity-Duration-Frequency (IDF) curves, using high-resolution meteorological datasets. Her work involves machine learning, extreme value analysis, and stochastic storm transposition to improve our understanding of regional flood risks. In spare time, Arundhaty enjoys observing the natural landscape during bus and car rides, and loves exploring new places.
Arundhaty is researching how regional rainfall extremes are evolving in response to climate and environmental changes. She focuses on analyzing shifts in rainfall intensity, duration, and frequency through Intensity-Duration-Frequency (IDF) curves, using high-resolution meteorological datasets. Her work involves machine learning, extreme value analysis, and stochastic storm transposition to improve our understanding of regional flood risks. In spare time, Arundhaty enjoys observing the natural landscape during bus and car rides, and loves exploring new places.
Interested in pursuing a Ph.D. in Water Resources and eager to contribute to sustainable and resilient community solutions? Check the admission requirements for our PhD program here, and please send your CV and a motivation letter to Prof. Gabriel Perez at gabriel.perez_mesa@okstate.edu.
Interested in pursuing a Ph.D. in Water Resources and eager to contribute to sustainable and resilient community solutions? Check the admission requirements for our PhD program here, and please send your CV and a motivation letter to Prof. Gabriel Perez at gabriel.perez_mesa@okstate.edu.
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