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Open Source Contributor Data Science ML
Data scientist at FMF and CERN who built predictive semiconductor models and automated complex data pipelines.
SwitzerlandOpen Source Contributor Data Science ML at GitHub
Contributing to production-grade ML systems in quantitative finance and renewable energy forecasting. Applying PhD-level physics expertise to develop robust, interpretable machine learning pipelines for time-series prediction and algorithmic trading. Collaborating with international teams on open source projects with emphasis on code quality, reproducibility, and MLOps.
PythonMLOpsscikit learnPyTorchGitHubXGBoostPytestFinance Analytics
Adapted quickly to the Swiss work environment, demonstrating strong communication, patience, and cross-cultural integration skills.
Communication SkillsCultural IntegrationPatience
Developed automated Python/Pandas pipelines to clean, transform, and analyze complex spectroscopic and electrical datasets, reducing data processing time by 40%. Implemented numerical simulations and statistical analysis to model optical properties of perovskite semiconductors, increasing characterization accuracy by 30%.
PythonPandasScipyNumerical SimulationStatistical AnalysisHPCCObject Oriented Programming
Translated complex mathematical and physical concepts into accessible lessons for high school students, improving average student test scores by 50%.
TeachingMathematicsPhysicsCommunication Skills
Designed statistical models to analyze time-differential perturbed angular correlation (TDPAC) data, identifying hidden patterns in magnetic nanoparticle behavior and enhancing data correlation capabilities by 35%. Led interdisciplinary data collaboration, bridging theoretical physics and experimental data, resulting in a 20% faster iteration cycle for material synthesis experiments.
Statistical ModelingData AnalysisTDPACInterdisciplinary CollaborationCorrelation
European Organization for Nuclear Research (CERN)
Applied machine learning techniques and multivariate statistical analysis to correlate isotopic implantation data with semiconductor cryogenic properties, improving predictive model accuracy by 30%. Processed complex experimental data from the ISOLDE ion separator, creating SQL and Python-based data workflows for cross-border research teams.
Machine Learningscikit learnMultivariate Statistical MethodsSQLPythonData WorkflowsData Processing
Taught Integral/Differential Calculus, Electromagnetism, and Materials Science to engineering students. Developed data-driven grading and performance tracking systems for over 100 students.
TeachingCalculusElectromagneticsMaterials ScienceData Driven GradingPerformance Monitoring
Intensive, peer-to-peer project-based learning focusing on C programming, memory management, debugging, Linux environments, networking, and algorithmic complexity.
Ph.D. in Sciences – Applied Nuclear Technology. Thesis: Investigation of impurities and surface properties on TlBr crystals for radiation detectors.
M.Sc. in Sciences – Applied Nuclear Technology. Thesis: Optimization of methodology for the preparation of TlBr crystals.
B.Sc. in Physics.
Profile sourced from Himalayas.