Asim Dey

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I am a Visiting Research Collaborator in the Department of Electrical Engineering (EE) at Princeton University and a Postdoctoral Research Associate at The University of Texas at Dallas. I work jointly with H. Vincent Poor at Princeton University and Yulia R. Gel at The University of Texas at Dallas. In Summer 2019 I received my PhD from the department of Mathematical Sciences at The University of Texas at Dallas under the advice of Yulia R. Gel. In Fall 2017 I was a Visiting Graduate Research Fellow at Statistical and Applied Mathematical Sciences Institute (SAMSI), NC.

Employment

Fall 2019 - present: Visiting Research Collaborator, Princeton University.
Fall 2019 - present: Postdoctoral Research Associate, The University of Texas at Dallas.
Summer 2018: Intern, Pacific Northwest National Laboratory (PNNL).
Oct 2011 - July 2013: Software Engineer, IMS Health, Dhaka, Bangladesh.

Education

Ph.D., Statistics, The University of Texas at Dallas, 2019.
M.S., Mathematics, Lamar University, TX, 2015.
M.S., Applied Statistics, University of Dhaka, 2010.
B.Sc., Applied Statistics, University of Dhaka, 2009.

Research interests

  1. Statistical methods for complex networks.
  2. Topological and geometric data analysis.
  3. Extreme value modeling.
  4. Environmental statistics, and statistical methods for finance and economics.
  5. Statistical foundation of data science and machine learning.

Publications

List of my publications is available at Google Scholar.

Selected Awards and Honors

2020 Best Paper Award, American Statistical Association (ASA) Section for Statistics in Defense and National Security (SDNS).
2019 Best Paper Award, American Statistical Association (ASA) Section for Statistics in Defense and National Security (SDNS).
2018 PhD Research Small Grant, The University of Texas at Dallas, TX.
2018 Summer Institute Scholarship, Department of Biostatistics, University of Washington, WA.
2017 Graduate Research Fellowship, SAMSI, NC.

External Research Grants

2020–2021 & “RAPID: Collaborative Research: Operational COVID-19 Forecasting with Multi-Source Information”, NSF DMS 2027793, & Role: Senior Personnel; PI: Yulia R. Gel.
2020-2021 “UT Dallas NRUF Grant: Market Sensing with Cryptocurrency Chainlets: Can We Learn More on the Traditional Economy from Non-Traditional Blockchain Data Sources”, Role: Senior Personnel; PI: Irina Panovska.
2021-2024 “What New Can We Learn on the Aggregate Economy through Lenses of Topological Data Analysis and Non-Traditional Blockchain Data Sources?” Role: co-PI; PI: Irina Panovska. (submitted)

Teaching

Recent Courses at The University of Texas at Dallas

Guest Lecturer, “Multivariate Analysis by Data Depth”, STAT 7331 Multivariate Analysis.
STAT 3360 - Probability and Statistics for Manag. and Econ.
MATH 2413 - Differential Calculus
MATH 2414 - Integral Calculus

Professional Service

Reviewer for Canadian Journal of Statistics, Computational Statistics & Data Analysis, Technometrics, Physica A: Statistical Mechanics and its Applications and REVSTAT.

My CV is available here here and is my ResearchGate page.