08/27/2026 updated
60 % partially available
AI & Data Science Undergraduate | Machine Learning | Python | Research
bharatpur, India
Only remote
B.Tech in Artificial Intelligence & Data Science (currently pursuing)About me
AI & Data Science student with research experience at TIFR and IIT Roorkee. Skilled in Python, machine learning, data analysis, visualization, and scientific computing. I enjoy solving real-world problems and delivering clean, reliable, well-documented work.
Data AnalysisPython (Programming Language)Machine LearningNumPyAzure Machine LearningSciPySupervised LearningData ScienceDeep LearningJupyterpandasMatplotlibScikit LearnMachine Learning OperationsAzure Data Analytics
Machine Learning & Deep Learning
Expertise in supervised learning, classification, regression, feature engineering, and model evaluation. Hands-on experience with XGBoost, CNNs, and CNN + Transformer architectures for real-world astronomical datasets.
Python & Scientific Computing
Proficiency in Python programming with scientific libraries including NumPy, Pandas, Matplotlib, SciPy, and Scikit-learn. Application of these tools for astronomical time-series analysis and TESS light curve processing.
Astrophysical Data Analysis
Practical experience working with real astronomical time-series data from NASA's Transiting Exoplanet Survey Satellite (TESS). Development of ML/DL-based classification pipelines for detecting self-lensing events in highly imbalanced datasets.
C++ Programming
Knowledge of C++ programming applied in scientific computing contexts, including working with GEANT4, a C++-based particle interaction and detector simulation toolkit.
GEANT4 Simulation
Learning and applying GEANT4 for detector geometry, particle interactions, optical photons, and PMT response using simulation-based approaches in experimental nuclear astrophysics.
Data Structures & Algorithms
Foundational knowledge of data structures and algorithms as part of academic coursework, supporting efficient problem-solving and software development.
Object-Oriented Programming
Understanding of object-oriented programming concepts applied across Python and C++ development tasks.
Tools: Git, GitHub, Jupyter Notebook, VS Code
Familiarity with version control and development tools including Git, GitHub, Jupyter Notebook, and VS Code for collaborative and individual research projects.
Expertise in supervised learning, classification, regression, feature engineering, and model evaluation. Hands-on experience with XGBoost, CNNs, and CNN + Transformer architectures for real-world astronomical datasets.
Python & Scientific Computing
Proficiency in Python programming with scientific libraries including NumPy, Pandas, Matplotlib, SciPy, and Scikit-learn. Application of these tools for astronomical time-series analysis and TESS light curve processing.
Astrophysical Data Analysis
Practical experience working with real astronomical time-series data from NASA's Transiting Exoplanet Survey Satellite (TESS). Development of ML/DL-based classification pipelines for detecting self-lensing events in highly imbalanced datasets.
C++ Programming
Knowledge of C++ programming applied in scientific computing contexts, including working with GEANT4, a C++-based particle interaction and detector simulation toolkit.
GEANT4 Simulation
Learning and applying GEANT4 for detector geometry, particle interactions, optical photons, and PMT response using simulation-based approaches in experimental nuclear astrophysics.
Data Structures & Algorithms
Foundational knowledge of data structures and algorithms as part of academic coursework, supporting efficient problem-solving and software development.
Object-Oriented Programming
Understanding of object-oriented programming concepts applied across Python and C++ development tasks.
Tools: Git, GitHub, Jupyter Notebook, VS Code
Familiarity with version control and development tools including Git, GitHub, Jupyter Notebook, and VS Code for collaborative and individual research projects.
Experience
Professional experience0 - 5 years
Freelancer since2026
Languages
EnglishFluent
Project history
Working under Prof. Anil Gourishetty on experimental nuclear astrophysics. Learning and applying GEANT4 for particle interaction and detector simulation. Studying Photo Multiplier Tubes (PMTs) and Cherenkov radiation. Exploring detector geometry, particle interactions, optical photons, and PMT response using simulation-based approaches.
Developed a workflow for processing and analysing astronomical light curves obtained from TESS observations. Worked with time-series data and visualisation techniques to identify meaningful patterns. Used Python-based scientific computing libraries for analysis.
Analysed astronomical light-curve datasets using Python. Performed preprocessing, visualization, and exploratory analysis of time-series observations. Strengthened practical understanding of scientific datasets and computational astronomy.