Maitreyee Sharma Priyadarshini

Johns Hopkins University — United States

Mathematics · Physical Sciences

10h-index409citations44works3.62yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Gas Dynamics and Kinetic Theory(27), Computational Fluid Dynamics and Aerodynamics(10), Fluid Dynamics and Turbulent Flows(6), Phase Equilibria and Thermodynamics(6), Machine Learning in Materials Science(6)

Publications44 total

Author Correction: A call to elevate the role of processing in AI-driven materials design
Nature Reviews Materials·2025Open Access
Machine Learning-Driven Closed-Loop Discovery of Hard Multiple Principal Element Alloys
2025Open Access
Bayesian Optimization Hackathon for Chemistry and Materials
2025· 1 citedOpen Access
Swaged Aluminum Powder Compacts: Linking Processing Variables to Quasistatic and Dynamic Properties with Machine Learning
SSRN Electronic Journal·2025Open Access
Swaged Aluminum Powder Compacts: Linking Processing Variables to Quasistatic and Dynamic Properties with Machine Learning
SSRN Electronic Journal·2025Open Access
CFD ANALYSIS OF THRUST VECTORING NOZZLE
JOURNAL OF ADVANCE AND FUTURE RESEARCH·2025Open Access
ReLMM: Reinforcement Learning Optimizes Feature Selection in Modeling Materials
Journal of Chemical Information and Modeling·2024· 3 citedOpen Access
Machine learning-guided accelerated discovery of structure-property correlations in lean magnesium alloys for biomedical applications
Journal of Magnesium and Alloys·2024· 25 citedOpen Access
NestedAE: interpretable nested autoencoders for multi-scale materials characterization
Materials Horizons·2023· 3 citedOpen Access
PAL 2.0: a physics-driven bayesian optimization framework for material discovery
Materials Horizons·2023· 14 citedOpen Access
Efficient quasi-classical trajectory calculations by means of neural operator architectures
Physical Chemistry Chemical Physics·2023· 10 cited
Efficient Quasi-Classical Trajectory Calculations by means of Neural Operator Architectures
2022· 4 citedOpen Access
Comprehensive Study of HCN: Potential Energy Surfaces, State-to-State Kinetics, and Master Equation Analysis
The Journal of Physical Chemistry A·2022· 10 cited
Rovibrational-Specific QCT and Master Equation Study on N<sub>2</sub>(X<sup>1</sup>Σ<sub>g</sub><sup>+</sup>) + O(<sup>3</sup>P) and NO(X<sup>2</sup>Π) + N(<sup>4</sup>S) Systems in High-Energy Collisions
The Journal of Physical Chemistry A·2022· 35 cited
Importance of Exchange Processes in Earth and Mars Atmospheric Kinetics: Application to HCN System
AIAA SCITECH 2022 Forum·2022· 1 cited
Rovibrational-Specific Master Equation Analysis of High-Temperature Air Mixture
AIAA SCITECH 2022 Forum·2022· 2 cited
Rovibrational-Specific QCT and Master Equation Study on $\text{N}_2(\text{X}^1Σ_g^+)$+$\text{O}({}^3\text{P})$ and $\text{NO}(\text{X}^2Π)$+$\text{N}({}^4\text{S})$ Systems in High-Energy Collisions
arXiv (Cornell University)·2021Open Access
Rovibrational-Specific QCT and Master Equation Study on $\text{N}_2(\text{X}^1\Sigma_g^+)$+$\text{O}({}^3\text{P})$ and $\text{NO}(\text{X}^2\Pi)$+$\text{N}({}^4\text{S})$ Systems in High-Energy Collisions.
arXiv (Cornell University)·2021Open Access
Carbon Clusters: Thermochemistry and Electronic Structure at High Temperatures
The Journal of Physical Chemistry A·2021· 5 cited
Application of DeepOnet to model inelastic scattering probabilities in air mixtures
AIAA AVIATION 2021 FORUM·2021· 13 cited
page 1 of 3Next →

Frequent Co-authors

Marco Panesi(23), Simone Venturi(16), Alessandro Munafò(11), Joanna M. Austin(7), Richard L. Jaffe(7), Sung Min Jo(6), Paulette Clancy(6), Timothy P. Weihs(4), Yen Liu(2), Sreenivas Raguraman(2), Adam J. Griebel(2), Matthew McGilvray(2), Peter A. Jacobs(2), Richard G. Morgan(2), Nick Glumac(2), Luca Massa(2), Marcp Panesi(2), David W. Schwenke(2), Ivan Zanardi(2), Nikhil Thota(2)