CV

For the full list of academic publications, see my CV or check out my ADS, inSPIREhep, Google Scholar profile.

Education

  • Ph.D in Physics, University of Michigan - Ann Arbor, 2012-2018
  • Ph.D in Scientific Computing, University of Michigan - Ann Arbor, 2012-2018
  • M.S. in Physics, University of Michigan - Ann Arbor, 2012 - 2014
  • B.S. in Mechanical Engineering, Sharif University of Technology, 2004 - 2009
  • B.S. in Physics, Sharif University of Technology, 2004 - 2009

Teaching experience

  • Instructor:
    • Yale University, Introduction to Scientific Computing & Data Science (with Daisuke Nagai), Fall 2020 – responsible for designing the material for the data science half of the course.
  • Guest Lecturer:
    • University of Michigan, Exploratory Data Analysis for Health (LHS 610), Fall 2017
    • University of Michigan, Big Data Summer Institute (BDSI), Summer 2017
    • University of Michigan, Comprehensive Studies Program (CSB) 100, Summer 2017
  • Grader:
    • University of Michigan, PHYSICS 525, Advance Cosmology, September 2016 - December 2016
  • Graduate Student Instructor (GSI):
    • University of Michigan, Physics 505, Advance Electricity and Magnetism, GSI
    • University of Michigan, Physics 241, Elementary Laboratory II, Laboratory Instructor
    • University of Michigan, Physics 136, Life Sciences Lab I, Laboratory Instructor
    • University of Michigan, Physics 236, Life Sciences Lab II, Laboratory Instructor

Employment History

  • Data Science Fellow with Michigan Institute for Data Science, University of Michigan, November 2019 – now)

  • McWilliams Postdoctoral Fellow, Carnegie Mellon University, September 2018 - October 2019

  • Research Assistance at University of Michigan, September 2012 - 2018

Leadership

  • Co-founder and a member of the steering committee of the Michigan - Data Informed Cities for Everyone (M-DICE), 2020 – present

M-DICE develops data-driven solutions to emerging challenges in realizing smart cities.

Our team has embarked on a partnership with the City of Detroit to provide AI-support solutions for several key mobility challenges in the city. The overall goals of our partnership are to provide a unified solution for managing and integrating disparate mobility data sources, and to use data to inform budget planning, resource allocation, and policy evaluation. We currently have three ongoing projects with four departments in Detroit. In the first project, the team that I lead is working on (i) automating the twice-annual evaluation of road conditions by using millions of images that the city collects and (ii) designing a recommendation system to guide decision-makers on which roads should be fixed during the next road-maintenance cycle. In the second project, another team is developing a mobility safety index through which we aim to understand the commuting patterns in downtown Detroit and evaluate policy proposals aimed at reducing the number of crashes. During the COVID-19 pandemic, the city initiated a new program that provides e-scooters and e-bikes to essential workers for commuting. In a recently launched project, we seek to use survey data to assess the effectiveness of this new program. The results will set recommendations to enhance safety and user experience and guide the next phase of this program.

  • Co-chair of Baryon Pasters collaboration, 2020 – present

The demand for improved cosmological simulations and computational tools has grown in the astronomy community, which is rooted in need for testing and validating survey-specific inference and data analysis pipelines. To fulfill these needs, the Baryon Pasting (BP) collaboration, an international team of >30 astronomers, statisticians, and computer scientists, is formed. BP designs novel computational tools, produces cosmological simulations, implements data analysis methods, and releases open-source software packages to unleash the full potential of data collected by large-scale astronomical surveys, and enhance the utility of astronomical data. BP has a number of on-going partnerships with the major observational surveys to produce survey-specific simulations.

  • Member of Organization Committee for the AI for Social Good Workshop at NeurIPS, 2018

  • Executive Member of Michigan Data Science Team (MDST), 2016-2018

    • Recruited and mentored over 100 active members
      • Promote data science interest and education on campus
      • Teaching practical data science skills to students at University of Michigan
      • Lead high-impact public-service projects
    • Leads a group of advanced team members on public data science challenge
    • Responsible for the production of well-validated and reproducible science, technology, and consulting products of legacy quality.

Services

  • External Reviewer for the NASA’s Future Investigators in Earth and Space Science and Technology (FINESST) program, 2019-2020

  • Volunteer for Statistics Without Boarder, 2019-2020

  • Co-chair of the poster session at the Midwest Big Data Hub All-Hands Meeting, 2018-2019

  • Member of Dark Energy Survey (DES) outreach working group, 2017-2019

  • AI Grant reviewer, 2017-2018

  • Cluster Seminar Organizer, University of Michigan, 2015-2017

  • ELI/SLC Co-mentor, University of Michigan, Winter 2015 & Winter 2016

  • Member of Local Organization Committee for DES (Dark Energy Survey) Collaboration Meeting, University of Michigan, 2015

  • Reviewer for Conferences: AAAI, Workshops: AI for Social Good (NeurIPS), Machine Learning and the Physical Sciences (NeurIPS), Journals: The Astrophysical Journal, Monthly Notices of the Royal Astronomical Society, Entropy, Astroparticle Physics Journal.

  • Member of the following collaborations:

    • Michigan - Data Informed Cities for Everyone (M-DICE, co-founder and a member of the steering committee)
    • Baryon Pasters (PB, chair of the optical and lensing working group)
    • The Cosmostatistics Initiative (COIN)
    • DEEP SKIES – Bringing Artificial Intelligence to Astrophysics
    • Dark Energy Science Collaboration (DESC)
    • Dark Energy Survey (DES)
    • Local Cluster Substructure Survey (LoCuSS)
    • XMM-XXL Consortium.