Sukanta Basu

ETEC 321 · +1 518-437-8633

Atmospheric Sciences Research Center

University at Albany, SUNY

Albany, NY, USA

I am a Professor of Empire Innovation at the University at Albany (SUNY), jointly appointed in the Atmospheric Sciences Research Center and the Department of Environmental and Sustainable Engineering.

My group studies atmospheric turbulence across scales and the many places it matters: the structure of the atmospheric boundary layer, optical turbulence ($C_n^2$) and its effect on imaging and laser propagation, large-eddy and mesoscale simulation of the lower atmosphere, numerical weather prediction, and wind energy. Increasingly, this work is done with machine learning — parameterizations, downscaling, nowcasting, and data-driven surrogates for the Earth system.

80+

Journal articles

25+

Funded projects

40+

Students & postdocs

15+

ML competitions

I lead the development of JAX-ALFA (Atmospheric LES For All) — a JAX-based large-eddy simulation framework for atmospheric boundary-layer flows that runs on CPUs and GPUs, with spectral horizontal derivatives, an FFT pressure solver, and dynamic subgrid-scale closures.

Before Albany I was a tenured Associate Professor at Delft University of Technology (2016–2023), and before that on the faculty at North Carolina State University and Texas Tech University. I received my Ph.D. in Civil Engineering from the University of Minnesota and hold an NSF CAREER award. I also compete in applied-ML and forecasting challenges — Shell.ai, NASA Airathon, IEEE, HEROx, and others.

See my publications, research group, the courses I teach, and software & data. My full CV is available as a PDF, and there is a short official bio on my ASRC faculty page.

news

Mar 15, 2026	Our Applied Optics paper on leveraging deep-learning foundation models for optical turbulence ($C_n^2$) estimation under data scarcity was selected as an Editor’s Pick.
Mar 06, 2026	Gave an invited seminar, “AI/ML-driven modeling of atmospheric turbulence for weather, energy, and defense applications,” at Johns Hopkins University.
Nov 19, 2025	Invited seminar at the University of Alabama in Huntsville on AI/ML-driven modeling of atmospheric turbulence.
Sep 01, 2025	With D. Roy Sarkar, L. Manuel, and S. Goswami (JHU / UT-Austin), our team ranked 5th of 40 in the NASA & DNV UQ Challenge on optimization under uncertainty.
Jun 01, 2025	Max Pierzyna won the Best Student Poster Award at the AMS Symposium on Boundary Layers and Turbulence.
May 01, 2025	Bowen Li successfully defended her Ph.D. dissertation, Dunkelflaute events — characterization, prediction and future projection (TU Delft).

selected publications

Optics

Leveraging deep learning-based foundation models for optical turbulence ($C_n^2$) estimation under data scarcity

S Basu

Applied Optics, 2026

Editor’s Pick, Applied Optics Bib Code

true

@article{basu2026AO,
  title = {Leveraging deep learning-based foundation models for optical turbulence (\(C_n^2\)) estimation under data scarcity},
  author = {Basu, S},
  journal = {Applied Optics},
  year = {2026},
  volume = {65},
  pages = {2497--2504},
}

Wind

Impact of atmospheric turbulence on performance and loads of wind turbines: Knowledge gaps and research challenges

B Kosović, S Basu, J Berg, and 7 more authors

Wind Energy Science, 2026

Bib

@article{kosovic2026WES,
  title = {Impact of atmospheric turbulence on performance and loads of wind turbines: Knowledge gaps and research challenges},
  author = {Kosovi\'{c}, B and Basu, S and Berg, J and Berg, L K and Haupt, S E and Lars\'{e}n, X G and Peinke, J and Stevens, R J A M and Veers, P and Watson, S},
  journal = {Wind Energy Science},
  year = {2026},
  volume = {11},
  pages = {509--555},
}

Optics

OTCliM: generating a near-surface climatology of optical turbulence strength ($C_n^2$) using gradient boosting

M Pierzyna, S Basu, and R Saathof

Artificial Intelligence for the Earth Systems, 2025

Bib

@article{pierzyna2025AIES,
  title = {{OTCliM}: generating a near-surface climatology of optical turbulence strength (\(C_n^2\)) using gradient boosting},
  author = {Pierzyna, M and Basu, S and Saathof, R},
  journal = {Artificial Intelligence for the Earth Systems},
  year = {2025},
  volume = {4},
  pages = {e240076},
}

Wind

Grand Challenges: wind energy research needs for a global energy transition

P Veers, K Dykes, S Basu, and 11 more authors

Wind Energy Science, 2022

Bib

@article{veers2023WES,
  title = {Grand Challenges: wind energy research needs for a global energy transition},
  author = {Veers, P and Dykes, K and Basu, S and Bianchini, A and Clifton, A and Green, P and Holttinen, H and Kitzing, L and Kosovic, B and Lundquist, J K and Meyers, J and O'Malley, M and Shaw, W J and Straw, B},
  journal = {Wind Energy Science},
  year = {2022},
  volume = {7},
  pages = {2491--2496},
}