Siddarth Achar, Ph.D.

Siddarth Achar, Ph.D.

Postdoctoral Scholar

University of Chicago

Biography

My research interests include molecular simulation, statistical and quantum mechanics, scientific machine learning, material design and development, and molecular discovery. I am a postdoctoral scholar in the labs of Dr. Andrew Ferguson and Dr. Junhong Chen at the Pritkzer School of Molecular Engineering at the Unviersity of Chicago. I received my Ph.D. in Computation Modeling and Simulation from the University of Pittsburgh under the mentorship of Dr. J. Karl Johnson.

Download my resumé.

Interests

  • Molecular Simulation
  • Statistical Mechanics
  • Machine Learning
  • Quantum Mechanics
  • Material Design and Development
  • Molecular Discovery

Education

  • Postdoctoral Scholar, 2024 - Present

    University of Chicago

  • Ph.D. in Computational Modeling and Simulation, 2020 - 2024

    University of Pittsburgh

  • M.S. in Chemical Engineering, 2019

    Carnegie Mellon University

  • B.E. in Chemical Engineering, 2018

    R.V. College of Engineering, Bangalore

Experience

 
 
 
 
 

Postdoctoral Scholar

University of Chicago - Ferguson Lab

Aug 2024 – Present Chicago, IL

Responsibilities include:

  • High-throughput virtual screening and data-driven design of sensitive and selective molecular sensors.
 
 
 
 
 

RAMP Computational Material Science Intern (2022)

Western Digital

May 2022 – Aug 2022 San Jose, CA
Discovered new electrode metal-chalcogenides for phase change memory devices.
 
 
 
 
 

RAMP Computational Material Science Intern (2021)

Western Digital

May 2021 – Aug 2021 San Jose, CA
Building active learning machine learning potentials using moment tensors (MTP) to investigate interdiffusion at metal-chalcogenide alloys interfaces.
 
 
 
 
 

Graduate Student Researcher

University of Pittsburgh - Johnson Group

Jan 2020 – Aug 2024 Pittsburgh, PA

Responsibilities include:

  • Modeling anhydrous proton conducting membranes for fuel cells using machine learning potentials.
  • Reactive active learning for machine learning potentials.
  • Deep learning for charge density prediction.
  • Metal-Organic-framework UiO-66 material designs and simuation.
  • Mentoring undergrad and graduate students.
  • Grant writing.
  • President of Chemical Engineering Graduate Student Association.
 
 
 
 
 

Summer Research Fellow

Saha Institute of Nuclear Physics

May 2017 – Jul 2017 Kolkata, India
Worked with the instrumentation of Secondary Ion Mass Spectroscopy.
 
 
 
 
 

Research Intern

Innovative Nano Materials (INM) Pvt. Ltd.

Jan 2017 – Dec 2017 Bangalore, India
Synthesis of MgF2 - TiO2 composites using sol-gel techniques for solar glass panels.

Recent & Upcoming Talks

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