Mohammad Ali Javidian

Purdue University, West Lafayette, IN, 47907ยท

I am a postdoctoral scholar at the School of Electrical and Computer Engineering of Purdue University.

Here is my CV.


University of South Carolina

Computer Science - (Dissertation [Slides])
August 2015 - December 2019

Sharif University of Technology

Master of Science
Computer Science
September 2013

Shiraz University

Master of Science
September 2007

Shahid Bahonar University of Kerman

Bachelor of Science
July 2003

Research Projects

  • Quantum entropic causal inference: This project is being led by Professors Zubin Jacob and Vaneet Aggarwal. I have been working on this project since September 2020 to develop novel algorithmic and theoretically principled methods for quantum entropic causal inference to understand causality relations between quantum particles using an entropic approach.

  • Causal structure learning and their applications in machine learning systems: This project is being led by Professors Pooyan Jamshidi and Marco Valtorta. I have been working on this project since Spring 2019 to propose novel algorithms for learning the structure of causal models in order to answer the following questions: How to use the causal structure of machine learning systems for identifying and estimating causal effects of configuration options on performance? How to apply transfer learning for performance analysis of machine learning systems by means of causal models? How to use causal inference tools for performance debugging and explainability in machine learning systems?

  • Hypergraph-Based Causal Modeling: This project was led by Professors Linyuan Lu and Marco Valtorta. I worked on this project with Zhiyu Wang to develop a novel probabilistic graphical model, which we call "Hypergraph Bayesian Network," to encode conditional independences.

  • Co-Arg: Causal Argumentation System with Crowd Elicitation. Agency: Intelligence Advanced Research Project Agency (IARPA); PI: Gheorghe Tecuci. I worked on this project under the supervision of Professor Marco Valtorta to exploit the Bayesian approach in order to improve evidence-based hypothesis analysis.


Recent Professional Service