UC Berkeley · EPFL
Statistical Learning, Reliable AI & Real-World Systems
Incoming M.A. student in Statistics & Data Science at UC Berkeley, following a B.Sc. in Mechanical Engineering at EPFL.
My interests lie at the intersection of statistical learning, uncertainty, and sensing systems, with a focus on methods that remain reliable on imperfect real-world data.
Open to opportunities and collaborations in data science, applied machine learning, and research from Fall 2026.
Lausanne, Switzerland → Berkeley, California · August 2026
My work spans statistical learning, uncertainty, intelligent systems, and technical decision tools, with a focus on methods that remain useful and reliable on imperfect real-world data.
Probabilistic modeling, robust inference, calibration, validation, and uncertainty quantification.
Model reliability, data quality, distribution shift, reproducible evaluation, and performance under imperfect real-world conditions.
Signal processing, sensor fusion, localization, simulation-to-hardware validation, and feedback control.
Featured project
Experimental development and validation of a UWB-based robotic tracking system combining real-world sensor characterization, empirical noise modeling, localization, filtering, feedback control, ROS 2 simulation, and transfer to physical hardware.
Pipeline
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Experimental development and validation of a UWB-based robotic tracking system combining real-world sensor characterization, empirical noise modeling, localization, filtering, feedback control, ROS 2 simulation, and transfer to physical hardware.
Project 1 of 4: Follow Me
Two separate tracks: academic education, and professional, research, and leadership experience.
M.A. Statistics & Data Science
B.Sc. Mechanical Engineering
EPFL grading scale: 6.0 is the highest possible grade; 4.0 is the passing grade.
Incoming AI Engineer Intern
IndustryIncomingUpcoming internship in applied AI engineering.
Bachelor's Thesis Research Project
Research ProjectDeveloped and experimentally validated a UWB-based localization and control system for robotic tracking, combining physical sensing, empirical noise modeling, ROS 2 simulation, and hardware integration.
Teaching Assistant — Calculus III & Programming for Engineers
TeachingLed problem-solving sessions and supported undergraduate students in advanced calculus, scientific computing, Python, C, and MATLAB.
Co-founder & Founding Engineer
EntrepreneurshipDeveloped probabilistic NLP pipelines for organizational narrative analysis, with a focus on uncertainty and responsible interpretation.
Vice-President
LeadershipHelped lead the organization through a year in which Junior Enterprise EPFL was named Best Junior Enterprise in Switzerland 2026 by Junior Enterprises Switzerland, while developing partnerships, student engagement, and technical projects.
Organizational recognition: Best Junior Enterprise in Switzerland 2026 — Junior Enterprises Switzerland
Tools and methods I work with across statistics, software, and real-world systems.
Contact
Open to technical conversations and opportunities involving data science, applied machine learning, quantitative modeling, reliable AI, and real-world systems.
