Sagar Adhikari, PhD

Astrophysicist & Data Scientistadhikaree.sagar@gmail.com

Professional Summary

I find the mysteries of the universe to be incredibly fascinating as both an astrophysicist and a data scientist. Working with massive, high-dimensional data from telescopes around the world has honed my expertise in statistical modeling, machine learning, and advanced data visualization. From writing predictive algorithms to developing complex mathematical models, I constantly seek to apply data science techniques to push the boundaries of knowledge and solve broad, real-world problems.

Core Competencies

  • Python (Pandas, Scikit-learn)
  • Machine Learning & NLP
  • Deep Learning (TensorFlow, XGBoost)
  • Statistical & Time Series Analysis
  • RAG & LLM Integrations
  • Data Visualization

Key Projects

My Research Assistant (RAG Pipeline)

Python, NLP, Streamlit

An end-to-end Retrieval-Augmented Generation (RAG) web app built to interactively answer questions related to my peer-reviewed publications. Retrieves relevant responses from dense academic papers on Supermassive Black Holes and AGNs.

Stock Market Forecasting

Pandas, Scikit-learn

Utilized multiple statistical and machine learning models to forecast S&P 500 market trends. Compared and evaluated the effectiveness of different models to forecast impending market shifts.

ML Classifications of Fermi-LAT Blazars

XGBoost, Random Forest

Analyzed raw data from the Fermi-LAT telescope for classification of blazar types. Trained Decision Tree, XGBoost, and Random Forest classifiers, achieving over 90% accuracy with GBDT.

Hangman ML Solver

NLP, N-Gram Models

Implemented an N-Gram model to learn word patterns from a dictionary to solve the Hangman Word Game with ~66% accuracy against the training dictionary.

Selected Publications

  • Constraining the PG 1553+113 binary hypothesis: interpreting a new, 22-year period. Analyzed a century-long optical light curve, finding hints of a ~22 yr oscillation and exploring its relationship to supermassive black hole binaries.
  • Singular spectrum analysis of Fermi-LAT blazar light curves: A systematic search for periodicity and trends in the time domain. Processed data for 494 sources, extracting oscillatory components from trends and noise.
  • Distortions in periodicity analysis of blazars: the impact of flares. Investigated how stochastic flaring events mask or distort true periodic behavior in active galactic nuclei.

Conferences & Achievements

  • 2025: $80,000 NASA Fermi-GI research award grant
  • 2025: Meeting of Astronomers of South Carolina, Florence, SC, USA
  • 2024: 11th International Fermi Symposium, Maryland, USA
  • 2023: International Conference on Time Series and Forecasting (ITISE-2023), Gran Canaria, Spain
  • 2023: AAS/High Energy Astrophysics Division, Hawaii, USA
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