Dr. Phani Motamarri

COmputational Materials Physics (COMP) Lab

Assistant Professor

Indian Institute of Science (IISc), Bangalore, India 560012

Academic/Research Experience:

  • Assistant Professor (Current): Department of Computational and Data Sciences (CDS), Indian Institute of Science Bangalore, India.
  • Assistant Research Scientist (Research Faculty) (2015 - 2019): Department of Mechanical Engineering, University of Michigan Ann Arbor, USA.
  • Affiliate Faculty (2015 - 2019): Michigan Institute of Computational Discovery and Engineering (MICDE), University of Michigan Ann Arbor, USA.
  • Postdoctoral Research Fellow (2014 - 2015): Department of Mechanical Engineering, University of Michigan Ann Arbor, USA.
  • Researcher (2007 - 2009): India Science Lab, General Motors Research and Development Center, Bangalore, India


  • Doctor of Philosophy (PhD) in Mechanical Engineering (2014) at University of Michigan Ann Arbor, USA
  • Master of Engineering (ME) in Mechanical Engineering (2007) at Indian Institute of Science (IISc), Bangalore India
  • Bachelor of Engineering (BE) in Mechanical Engineering (2005) at National Institute of Technology Karnataka (NITK), Surathkal, India.

Curriculum Vitae :


Research Focus:

My research interests are centered around advancing the current predictive capabilities of computation based design of materials using first principles based quantum mechanical methods, with applications geared towards mechanics of materials (design of strong light-weight materials), clean-energy, and next generation bio-molecular electronic devices. In particular, the focus will be on developing mathematical techniques and real-space scalable computational algorithms that can leverage the latest heterogeneous parallel computing architectures and future exa-scale machines for ab-initio material modeling. These methods push the current limits in our ability to study complex material systems and provide deeper insights into various aspects of material properties at the nano-scale which can then be used to inform higher-scale models for accurate prediction of macroscopic material properties. My research is highly interdisciplinary and combines ideas from condensed matter theory, materials science, solid mechanics, adaptive finite-element methods, applied mathematics and heavy dose of high performance computing.

Computational Framework of the Research Group:

Research in CMPL will be based on DFT-FE (MPI+GPU), a massively parallel finite-element based open-source code for material modeling using density functional theory (DFT). DFT-FE code is a culmination of my PhD and my post-PhD research (till 2019) and the code development was in collaboration with Dr. Sambit Das and Prof. Vikram Gavini at University of Michigan, Ann Arbor. Furthermore, this research got nominated as a 2019 ACM Gordon Bell Prize Finalist, the highest prize in Scientific Computing.

Future/Current Research Topics:

  • Development of novel scalable finite-element based methods for ab-initio material modeling geared towards advancing the capabilities of DFT-FE.
  • Machine learning strategies for accelerating geometry optimization and ab-initio molecular dynamics.
  • Data centric approaches focused towards exa-scale computing for the solution of large-scale nonlinear eigenvalue problems arising in ab-initio modeling of materials.
  • Applications of DFT-FE for challenging material modeling problems: (i) Ab-initio modeling of energetics of defects in metallic systems, metallic glasses (ii) Ab-initio modeling of 2D materials (iii) Understanding charge transport in bio-molecular devices.

Our Collaborators:

  • (a) University of Michigan, Ann Arbor, US; (b) Toyota Research Institute, US; (c) Universidad Autónoma de Madrid, Spain; (d) IIT Bombay; (e) IIT Kharagpur; (f) IIT Bhubaneswar

Research Positions in COMP lab:

My lab is looking for bright and motivated students to pursue PhD/M.Tech(Research) in our group. Students with excellent academic background in any branch of engineering or physics or computational chemistry or applied mathematics are welcome to apply. Strong research interests in computational methods is a must and furthermore, should be passionate about learning computational material modeling, parallel computing on heterogeneous architectures, finite-element methods. Good proficiency in C++ programming is required for working in our group. Postdoctoral fellows who can bring in their own initial funding will also be considered if there is a strong match of research interests. Project assistant-ships and other internship positions (atleast an year commitment) will be considered case to case basis.