Siva Chiriki
Malla Reddy Engineering College, University of Hyderabad, Indian Institute of Technology Indore, Andhra University, Aarhus University
About
Dr. Siva Chiriki awarded Ph. D. (2018) in Theoretical Data Science Chemistry from School of Chemistry, IIT Indore, India for Developing Data-Driven Machine Learning Models to Studying Structure and Properties of Nano-clusters.
He Then Moved to Department of Physics & Astronomy, Aarhus University, Aarhus, Denmark for Postdoctoral Study on Developing Machine Learning Assisted Global Optimisation Algorithms. Dr. Siva worked on Surface Catalysis Reactions and Mutation Algorithms for global search. (2018-2020)
Later, Dr. Siva Chiriki Worked as Research Associate (RA) in School of Chemistry, Central University of Hyderabad, India. Developed Time Series Models like LSTM Networks and Bayesian Optimisation frame works with GPR models for a target property applications like On-site drug design, Hydrogen storage materials and Organic Solar Cell Molecules and Reaction Mechanisms.
Currently, Working a Assistant Professor in Data Science Chemistry Since March, 2022.
My Research Interests are:
1) Developing Machine Learning Models for Drug Design
2) Developing Machine Learning Algorithms for Reaction Path Generators
3) Developing Machine Learning Assisted Global Optimisation Algorithm for Surface Catalysis Reaction.
Employment
-
Malla Reddy Engineering College Assistant Professor in Machine Learning Chemistry2022 - Present
-
University of Hyderabad Research Associate2020 - 2021
-
Aarhus University Postdoc2018 - 2020
Education
-
Indian Institute of Technology Indore PhD2013 - 2018
-
Andhra University M.Sc.2008 - 2010
Projects & Funding
Projects & funding information is unavailable.
Publications (8)
- Advanced machine learning based global optimizations for Pt nanoclusters Save
- Constructing convex energy landscapes for atomistic structure optimization Save
- Correlation of structure with UV-visible spectra by varying SH composition in Au-SH nanoclusters Save
- C-T phase diagram and Landau free energies of (AgAu)<inf>55</inf> nanoalloy via neural-network molecular dynamic simulations Save
- Neural network potentials for dynamics and thermodynamics of gold nanoparticles Save
- Spherical harmonics based descriptor for neural network potentials: Structure and dynamics of Au<inf>147</inf> nanocluster Save
- Modeling of DFT quality neural network potential for sodium clusters: Application to melting of sodium clusters (Na<inf>20</inf> to Na<inf>40</inf>) Save
- Structural evolution of nucleobase clusters using force field models and density functional theory Save