CV - Archith Sharma / Personal Website

Education

B.S. in Statistics & Machine Learning, Carnegie Mellon University, 2028 (expected), GPA: 3.5

Relevant coursework: Intro to Machine Learning, Statistical Computing, Statistics Graphics & Visualization, Concepts of Mathematics, Principles of Imperative Computation (C Programming)
Honors: CMU Summer Undergraduate Research Fellow (SURF, $4,500 award); Putnam Score of 2; Syracuse Basketball Analytics Competition winner; publication in the Wharton Sports Analytics Journal (Spring 2025); publication in the Dietrich College WOVEN Interdisciplinary Journal (forthcoming)
Certifications: Society of Actuaries Exam P (Mathematical Probability); DataCamp R Programming

Work experience

Research Assistant, CMU Heinz College of Information Systems and Public Policy, October 2025 - Present

Ongoing research with Dr. Woody Zhu on deep-learning methods in earthquake detection
Developing an extension of CUSUM (Cumulative Sum Statistic for distribution change) to multiple data sources — see the CUSUM Portal project page
Supported by the CMU Summer Undergraduate Research Fellowship (SURF)

Research Assistant, University of North Texas (UNT), August 2023 - May 2025

Conducted research with Dr. Junhyeon Kwon on bird population models for conservation action
Developed a synthetic simulation framework and ARMA & ARDL time-series tools using R and R Markdown — published as Modeling American Kestrel Decline Using Spatiotemporal Subsampling to Improve eBird Data Reliability

Projects

The list below is pulled automatically from the Projects page.

Allegheny Land Trust: St. John’s Citizen Science Analysis

A data-for-good project with CMU Students Using Data for Good, measuring whether citizen-science activity around the Allegheny Land Trust’s St. John’s project has grown faster than state and county baselines. Download the write-up (PDF)

Syracuse Basketball Analytics Competition

Built a composite metric using weighted min-max normalization across Expected Points, Advantage Ratios, and Points Per Chance Ratios to identify which players a new team should prioritize protecting or targeting from proprietary data metrics.

NFL Big Data Bowl 2026: Ball Hawks

Measuring a defender’s commitment to the ball when it is in the air and its impact on play outcomes. Submitted to the NFL Big Data Bowl on Kaggle.

TAMS Mock Election 2024

A student-run mock election at the Texas Academy of Mathematics and Science: 115 voters, Texas-style ballot ordering, and a look at what ranked-choice voting can and can’t fix. Download the results write-up (PDF)

Geospatial Mobile Application for Emergency Response and Management

A location-based AR app for navigation and emergency response on the UNT campus, built on Google Photorealistic 3D Tiles and Cesium for Unity. Research in UNT’s Data Visualization and eXtended Reality (DVXR) Lab.

Skills

Technical: R, Python, HTML, LaTeX, Java, C, C++, C#, MATLAB Software: Tidyverse, PyTorch, Pandas, Object-Oriented Programming (OOP), Unity, Shiny Analysis: Mathematical Modeling, Contextual Thinking, Data Wrangling Soft Skills: Public Speaking, Organization, Building Relationships, Mathematical Thinking

Publications

The list below is pulled automatically from the Publications page.

Stats & Stumps: Using Machine Learning to Predict T20I Matches with Player and Venue Data

Sharma, A. (2025). "Stats & Stumps: Using Machine Learning to Predict T20I Matches with Player and Venue Data." Wharton Sports Analytics Journal.

Modeling American Kestrel Decline Using Spatiotemporal Subsampling to Improve eBird Data Reliability

Sharma, A., Bednarz, J. C., & Kwon, J. (2025). "Modeling American Kestrel Decline Using Spatiotemporal Subsampling to Improve eBird Data Reliability." bioRxiv. doi:10.1101/2024.10.31.621376.

Archith Sharma

CV