Pushkar Ghanekar

West Lafayette, IN · pghan-remove-eka@purdue.edu

Data aesthete at heart, I am a Ph.D. candidate in the Davidson School of Chemical Engineering at Purdue University, advised by Prof. Jeffrey Greeley.

Understanding molecular-level behavior of the catalyst is at the heart of my Ph.D. research.

Working in close collaboration with experimentalists, at Purdue and beyond, I develop atomic-scale computational models through a combination of chemistry, physics, data science, and machine-learning that capture the essential structure-function properties of the real-world catalyst. These models are used to identify physical/chemical transformations of the catalysts; the impact these transformations have on their catalytic activity, and propose design principles governing the performance of the catalyst. The primary focus of my work is on improving fuel-cell technologies to develop sustainable alternatives to fossil fuel resources for meeting future energy demands.

In addition, I am part of CISTAR - an engineering research center, developing a free web-based tool to estimate, analyze, and compile the hazards associated with setting up a lab-scale chemical reaction. This tools aims to democratize setting up lab-scale experiments and provide a platform to identify likely chemical/operational hazards when doing so. This work is supported by NSF as part of CISTAR consortium and jointly supervised by Purdue Process Safety and Assurance Center (P2SAC)

Besides research, I am passionate about cooking, experimenting with different tastes and textures (link to some latest experiments); love to go down internet rabbit holes, and enjoy long bike rides.


  • Kinetic Modeling
  • Catlayst Model Development
  • Material Informatics
  • Quantitative Structure Property Relationships
  • High-throughput screening
  • Theory/Experiment Collaborations
Languages, Operating Systems
  • Python
  • html/css
  • C
  • git
  • linux
  • bash
  • beautifulsoup
  • selenium
  • High Performance Computing
  • PyTorch
  • Dask
  • RAPIDS.ai
  • VASP
  • Aspen Plus
  • Adobe Creative Suite
  • Blender
Data Management & Containers
Relevant Coursework

Bayesian optimization using Gaussian Processes

Minimal example explaining how bayesian optimization works

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End-to-end Machine Learning Project

Regression model to predict median house values in Californian districts

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High throughput perovskite screening

High throughput screening of Materials Project dataset for estimating perovskite bulk stability. For selected candidates, analyze their surface morphology using ab-initio thermodynamic analysis.

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Indian spices network analysis

Analyze 6000+ recipes to find relations between spices most frequently used in Indian cuisine.

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PyTorch CNN example

Example of how to implement a convolutional neural network in PyTorch

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Support Vector Machines example

Notebook looking at workings of SVM (support vector machine).

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Web scraping IMDB Bollywood data

Scrapped IMDB database to analyze trends in Bollywood movie ratings and release volume over the years

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Web scraping S&P 500 data

Generate a list of S&P 500 companies and plot their market valuation over the months.

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List of peer-reviewed articles based on the projects I have been part of.

Journal article - Catalysis at Metal/Oxide Interfaces: Water Gas Shift at Pt/MgO Boundaries

Developing multi-component catalyst model to simulate the metal/oxide interface as an active site for water-gas shift reaction.

April 2020

Journal article - Electronic and Structural modification of Pt-V alloy and its consequences for Propane Dehydrogenation Catalysis

Electronic characterization of the Pt-V alloy phase for propane dehydrogenation using theory and experiments to understand the factors influencing the reaction selectivity and catalyst stability.

January 2020


Chemometric & AI Intern

Dow Chemical Company (Lake Jackson, TX)

Research and Development intern in Chemometric & AI (M&E) and Cheminformatics (Core R&D) department.

  • Applying deep learning method for data-driven prediction and high throughput screening of large molecule datasets with direct application to Dow business R&D.
  • Troubleshoot complex manufacturing problems through predictive analytics by developing anomaly detection methodology

June 2020 - August 2020

Process Engineering Intern

Black & Veatch (Mumbai, India)

Worked as Process Engineering intern for the Oil & Gas sector. Worked on following projects:

  • Designing and optimisation of proprietary LNG liquefaction processes
  • Unit Operation design and life-cycle analysis.

May 2015 - July 2015

Technical Head @ Vortex 2014

Institute of Chemical Technology (Mumbai, India)

Responsible for developing and managing the festival online registration and landing portal. Lead designing of promotion and publicity material. Lead organizer of IDP (Industry Defined Problem), one of the primary events of the festival with approximate audience of 1000.

May 2014 - July 2015

Formulation R&D Intern

Abhinandan Rasayan Pvt. Ltd. (Mumbai, India)

Worked in the manufacturing and formulation department. Handled following projects:

  • Mechanical design of chemical equipment.
  • Process development for production of APIs (collaborated with the R&D dept.)

May 2014 - July 2014

Research & Development Intern

Hetero Drugs Ltd. (Hyderabad, India)

Worked as an intern in the manufacturing (R&D) and distribution (supply-chain) facility. Main project was on scaling up manufacturing protocols for an API

June 2013 - August 2013

Graphic Design Lead @ Freshers 2012

Institute of Chemical Technology (Mumbai, India)

In charge of designing merchandise and promotional media for the festival

Dec 2012 - Jun 2013


Purdue University

Ph.D. Chemical Engineering
Bill Murray CISTAR Fellow

Thesis topic: Structural and Kinetic Modeling of Heterogeneous Catalysts Using First-Principles and Machine Learning

2016 - Present

Insitute Of Chemical Technology (ICT)

B.E. Chemical Engineering

2012 - 2016

Dr. S. Radhakrishnan International School

High School

2000 - 2010
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