World Cup Player Impact
An end-to-end study of 2,927 player-tournament observations that combines role-relative measurement, reliability adjustment, nested validation, temporal testing, clustering, and explainable machine learning.
Read the projectTravel document / Résumé
Akshay Byagathvalli
Data Science, Artificial Intelligence, and Research
Profile
I investigate complex questions through data, build intelligent systems, and communicate results through rigorous analysis and visualization.
Selected research
Pressure, Production, and Noise
A reproducible study of whether normal-condition offensive traits explain or predict the preservation of scoring efficiency during NBA clutch situations, with explicit non-clutch baselines, repeated validation, shrinkage, simulation, and multi-season stability checks.
Read the projectConcentration, Chokepoints, and Supply-at-Risk
A reproducible study of geographic concentration, country-mineral networks, structural vulnerability, and simulated supply disruption across a synthetic panel of 24 critical minerals and 35 producer countries.
Read the projectResearch approach
Questions → evidence → useful tools
Frame testable questions, document data provenance, compare methods honestly, and communicate findings through accessible visual explanations.
Portfolio field guideTechnical toolkit
Methods used in published work
Pythonpandasscikit-learnOptunaSHAPPlotlystatsmodelsnba_apiMonte CarloNetworkX