IIT Indore
Research Interests




    Broadly, we focus on following:

    1.
    Developing machine learning methods for chemical problems.
    • Here we are mainly interested in modelling potential energy surfaces of nanoclusters,nanoalloys.
    • Studying small gas adsorptions on the surface of nanoalloys using ML based potentials.
    • Developing transferable ML based interatomic potentials and atomic/molecular based descriptors to study structure, dynamics, repnose properties of chemical systems
      • J.Chem.Phys.149,194101(2018), Chem.Phys.Lett.693,152(2018), J.Chem.Phys.146,204301(2017), J.Chem.Phys.152,154302(2020), Comput.Theor.Chem.1220,113985(2023).

    2.
    Using hardware technologies(FPGA,GPUs) to parallelize our programs.
    • Here we are interested in developing a heterogenous computing platform, a hardware-software co-design, to implement parallel algorithms in an FPGA framework to reduce computation time. In case of a typical MD simulation, we developed a hetrogenous model such that the computationally expensive force calculations are implemented on FPGA while the rest of the simulation is carried on a PC. We believe such a system will drastically reduce the computational time and pave the way to parallelize the code efficiently.
      • IEEE Access 10,40338(2022)
    3.
    ML based Kinetic energy functionals for developing orbital free DFT(OFDFT).
    • Developing a Kinetic energy density functionals is a major challenge in OFDFT. We are trying to solve this problem with the help of ML methods to directly map the electron density to Kinetic energy density functionals.
      • J.Chem.Phys.159,124114(2023), Chem.Phys.Lett 801,139718(2022)
Dr. Satya S. Bulusu
Professor
Chemistry (Theoretical and Computational Chemistry)

sbulusu[at]iiti.ac.in