Khosronejad has received more than $6.7M in research funds/grants to date (9/7/2024) and over $5M of which is currently active supporting his research team members and research activities.

California Department of Transportation, Grant # 56A0532              (PI: Ali Khosronejad)    Total award: $55,000 (Khosronejad’s share: 100%),                          10/2017 – 09/2018 Title: High-fidelity three-dimensional numerical simulation of bridge foundation scour at a desert wash bridge under a flash flood event. The main goal of the project is to gain insight into the physics of bridge foundation scour in the dry-bed desert streams during flash floods. Role: PI (co-PI: none)

National Science Foundation (NSF), Grant # EAR-0120914             (PI: Ali Khosronejad)    Total award: $240,000 (Khosronejad’s share:100%)                            9/2018 – 08/2022 Title: Collaborative Research: Linking turbulent flow dynamics to meandering river migration The main goal of the project is to gain insight into the linkage between turbulence and formation of meandering rivers. Role: PI (co-PI: none)

National Institute of Health (NIH), Grant # 2R44ES025070-02       (PI: Ali Khosronejad) Subaward, Total award: $150,000 (Khosronejad’s share: 100%)          7/2019 – 08/2021 Title: Use of DNATrax and high-fidelity computational methods to model transport of contaminants in urban environments. The main goal of the project is to develop Eulerian and Lagrangian models of contaminant and saliva particle transport. Role: PI (co-PI: none)

National Science Foundation of Austria,                                               (PI: Christine Sindelar) Total award: €375,546                                                                        01/2019 – 01/2022    Funds allocated to Khosronejad: a Ph.D. student from Austria will travel to Stony Brook University and stay on campus for an academic year to take grad classes, and conduct research under his supervision. Title: PiCASSO: Particle Collisions for Arbitrary Smooth Shaped Objects, Experimental and numerical investigation: Model development and validation. The main goal of the project is to develop Lagrangian model of sediment grain transport. Role: co-PI (PI: Christine Sindelar, University of Natural Resources and Life Sciences, Vienna, Austria)

New York State Energy Research & Development Authority (NYSERDA) through National Offshore Wind Research & Development Consortium, Department of Energy (DOE)              (PI: Ali Khosronejad)                                                                   01/2020 – 01/2023      Total award: $1,085,121 (Khosronejad’s share: 100%)                                                       Title: High-fidelity simulations and data-driven models with turbine controls for the design of bottom-fixed offshore wind farm layouts. The main goal of the project is to develop advanced computational models and reduced-order models to optimize the design of offshore wind farms. Role: PI (co-PI: Lian Shen and Peter Seiler)

US Department of Energy (DOE)                                                  (PI: Ali Khosronejad)        Total award: $2,000,000 (Khosronejad’s share: 72.5%)                 08/2021 – 07/2025       (PI: Ali Khosronejad,  Title: An Atlantic Marine Energy Center (AMEC) for Advancing the Marine Renewable Energy Industry and Powering the Blue Economy. The main goal of the project is to develop computational and machine-learning algorithms to optimize the design of hydrokinetic turbines in tidal farms. Role: PI (co-PI: Fang Luo)

National Institute of Health (NIH), Grant # 2R44ES025070-02               (PI: Ali Khosronejad) Subaward, Total award: $50,000 (Khosronejad’s share: 100%)             8/2021 – 08/2022 Title: Phase 2 STTR: High fidelity computational methods to model transport of contaminants in urban environments. This project is a continuation of my previous NIH sub-award provided to conduct COVID-19 related research. The main goal of the project is to develop Eulerian and Lagrangian models of saliva transport during human respiratory events such as breathing, coughing, and sneezing. Role: PI (co-PI: none)

Safetrace Inc. Grant #: 1173396              (PI: Ali Khosronejad)                                                   Total award: $15,000           (Khosronejad’s share: 100%)            1/2022 – 12/2022     Title: Optimization of a spray system design using high-fidelity numerical modeling              The main goal of the project is to optimize the design of DNA sprayer systems.                 Role: PI (co-PI: none)

Stony Brook University  Grant #: 1176849              (PI: Ali Khosronejad)                                       Total award: $60,000           (Khosronejad’s share: 50%)             8/2022 – 8/2023      Title: Data-driven physics-based reduced-order models for effective design of offshore wind farms. Role: PI (co-PI: Dimitris Samaras)

National Science Foundation (NSF), Grant # 2233986                             (PI: Ali Khosronejad) Total award: $550,000 (Khosronejad’s share:100%)                                   7/2023 – 08/2027 Title: Development of artificial Intelligent systems for extreme flood prediction in large-scale waterways. Role: PI (co-PI: none)

Austrain National Science Found                                    (PI: Christine Sindelar)                 Total award: €397,000                                                                         09/2023 – 08/2026 Title: PiCASSO – II: Particle Collisions for Arbitrary Smooth Shaped Objects, Experimental and numerical investigation: Model development and validation.The main goal of the project is to develop Lagrangian model of sediment grain transport. Role: co-PI (PI: Christine Sindelar, Univ. of Natural Resour. & Life Sciences, Vienna, Austria).

US Department of Energy (DOE)                                             (PI (SBU): Ali Khosronejad) Total award: $2,100,000 (Khosronejad’s share: 42%)                        08/2024 – 07/2029      Title: Bi-Partisan Infrastructure Law DOE (BIL) Funding for activities at the AMEC National Marine Energy Center. The project’s main goal is to develop and test new marine hydrokinetic turbine (MHK) blades using composite material and fine-tune computational and machine-learning algorithms for tidal arrays in natural settings.Role: PI (co-PI: Fang Luo, Georgios Moutsanidis, Paolo Celli, Rigoberto Burqueño)