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Sai Krishna Sirumalla
Sai Krishna Sirumalla
ML Research at entos.ai
Verified email at entos.ai
Title
Cited by
Cited by
Year
OrbNet Denali: A machine learning potential for biological and organic chemistry with semi-empirical cost and DFT accuracy
AS Christensen, SK Sirumalla, Z Qiao, MB O’Connor, DGA Smith, F Ding, ...
The Journal of Chemical Physics 155 (20), 2021
632021
# COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol
A Dommer, L Casalino, F Kearns, M Rosenfeld, N Wauer, SH Ahn, ...
The international journal of high performance computing applications 37 (1 …, 2023
522023
Temperature and oxygen partial pressure dependencies of the coal-bound nitrogen to NOx conversion in O2/CO2 environments
A Panahi, SK Sirumalla, RH West, YA Levendis
Combustion and Flame 206, 98-111, 2019
362019
Extensive high-accuracy thermochemistry and group additivity values for halocarbon combustion modeling
DS Farina Jr, SK Sirumalla, EJ Mazeau, RH West
Industrial & Engineering Chemistry Research 60 (43), 15492-15501, 2021
152021
Nitrogen oxide evolution in oxy-coal combustion
SK Sirumalla, A Panahi, A Purohit, A Baugher, YA Levendis, RH West
US Eastern States Section of the Combustion Institute, 2018
92018
Assessing impacts of discrepancies in model parameters on autoignition model performance: A case study using butanol
SK Sirumalla, MA Mayer, KE Niemeyer, RH West
Combustion and Flame 190, 284-292, 2018
62018
Graph neural networks and high throughput quantum chemistry workflows for detailed kinetic modeling
SK Sirumalla
Northeastern University, 2021
32021
Automating the generation of detailed kinetic models for halocarbon combustion with the reaction mechanism generator
DS Farina Jr, SK Sirumalla, RH West
Proceedings of the Combustion Institute 39 (1), 223-232, 2023
22023
Systems and Methods for Determining Molecular Properties with Atomic-Orbital-Based Features
Z Qiao, A Anandkumar, TF Miller, MG Welborn, FR Manby, F Ding, ...
US Patent App. 17/332,951, 2022
2022
Graph Neural Networks to Predict Thermochemistry of Halogenated Hydrocarbons for Use in Combustion Modeling: New Data, Methods, and a Cautionary Tale.
SK Sirumalla, D Farina, RH West
2021 AIChE Annual Meeting, 2021
2021
Automating the Construction of Predictive Kinetic Models for the Combustion of Halogenated Hydrocarbons, with Rmg
D Farina, SK Sirumalla, RH West
2021 AIChE Annual Meeting, 2021
2021
Extensive High-Accuracy Thermochemistry and Group Additivity Values for Automated Generation of Halocarbon Combustion Models
D Farina Jr, SK Sirumalla, RH West
12th US National Combustion Meeting, 2021
2021
# COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy of Delta SARS-CoV-2 in a Respiratory Aerosol (preprint)
A Dommer, L Casalino, F Kearns, M Rosenfeld, N Wauer, SH Ahn, ...
2021
An Automated Job Management Framework for High Fidelity Quantum Chemistry Calculations
SK Sirumalla, D Farina, N Harms, RH West
2019 AIChE Annual Meeting, 2019
2019
Autonomous Systems for Experimental and Data-Driven Modeling of Combustion Kinetics
SK Sirumalla, N Harms, M Barbet, C LaGrotta, M Burke, K Niemeyer, ...
2019 AIChE Annual Meeting, 2019
2019
Message Passing Attention Networks for Reaction Rate Estimation
SK Sirumalla, RH West
2019 AIChE Annual Meeting, 2019
2019
Predicting the Combustion Properties of Hydrofluorocarbon (HFC) Refrigerants Using the Automated Reaction Mechanism Generator (RMG)
D Farina, SK Sirumalla, N Harms, RH West
2019 AIChE Annual Meeting, 2019
2019
Transition State Geometry Prediction Using Neural Embeddings of Transition State Graphs
SK Sirumalla, N Harms, RH West
2018 AIChE Annual Meeting, 2018
2018
Assessing Discrepancies in Kinetic Parameters and Improving Combustion Models through Metaheuristic Optimization
N Harms, SK Sirumalla, RH West
2018 AIChE Annual Meeting, 2018
2018
Unsupervised machine learning for data-driven representations of reactions
SK Sirumalla, R West
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 256, 2018
2018
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Articles 1–20