Hello!


I am Juliette Parchet

I'm into

Portrait of Juliette Parchet

Who Am I?

About Me

I am Juliette, an EPFL Data Science graduate who enjoys turning complex data into clear, usable products. I work across machine learning, computer vision, and data-driven applications, from research to deployment, and I love making complex ideas easy to understand, a skill I refined while teaching computer science to highschoolers.
Outside work, I recharge with classical piano (Chopin’s Nocturne in C♯ minor on repeat!), plenty of tea, and coffee when needed, and I stay active through competitive sailing and badminton.
I want to keep learning, take on new challenges, and apply my skills to meaningful real-world problems across diverse industries.

My Skills

Programming

Python
Java
C++
C#
C
SQL

Artificial Intelligence

Machine Learning
Deep Learning
Computer Vision
NLP
LLMs
PyTorch
TensorFlow
Scikit-learn
OpenCV

Data Analysis

NumPy
Pandas
Matplotlib
Seaborn
Jupyter Notebook
Statistics

Tools

Git
Azure
Docker
Github
VS Code
Linux
Agile
Communication & Teamwork

Education

Master in Data Science

EPFL (Swiss Federal Institute of Technology) — Lausanne (Sept. 2022 – Mar. 2025)

Rigorous Master of Science covering machine learning, algorithms, and data engineering; graduated with GPA 5.17/6

Teacher Training Program (Secondary Level II)

HEP (Haute Ecole Pédagogique) — Lausanne (Aug. 2023 – July 2024)

Joint EPFL–HEP training in computer science education: didactics, pedagogy, and a school-based teaching internship

Bachelor in Communication Systems

EPFL (Swiss Federal Institute of Technology) — Lausanne (Sept. 2018 – July 2022)

Solid foundations in math, computer science, and information theory, with projects in networks and signal processing; graduated with GPA 4.91/6

Projects

Deep Image Translation via Diffusion Models

Generated synthetic image pairs with a diffusion model and trained a lightweight neural network to adapt scenes to look abandoned for 100 years.

Lemanic Life Science Hackathon: Tumorscope

Won 2nd place at the Hackathon with Tumorscope, an interdisciplinary project using computer vision to analyze cell interactions.

Virtual Reality Game Development

Team-built a Unity VR game with real-time gesture recognition, navigation, and combat, optimized for comfort and immersion.

Actionability of Explainable AI (XAI)

Investigated how XAI methods can improve interpretability and actionability of black-box neural networks in education.

Image Analysis and Pattern Recognition

Built a computer vision pipeline for puzzle-piece analysis using feature extraction, clustering, shape recognition, and outlier detection.

LLM Fine-Tuning for Math QA

Fine-tuned LLM transformer models for mathematical reasoning, using curated datasets and targeted evaluation protocols.

User Preference Modeling

Modeled user behavior and preferences from large beer-rating raw data to guide user experience improvements and engagement tactics.

Embedded Autonomous Robotic Arm

Implemented guidance, detection, and grasping on a low-cost autonomous robotic arm with embedded code and calibration.

SimpledCLIP: Text-driven 3D Poses

Experimented with SMPL, differentiable rendering, and CLIP for text-driven 3D poses; the model remained unstable but highlighted key research challenges.

Rigel: Object-Oriented Night Sky Simulator

Built a modular Java app simulating the night sky with physics, applying object oriented principles and design patterns.

Act for Change Award: Microalgae in Cities

Won the EPFL Act for Change award for a poster project exploring microalgae-based CO₂ capture in urban environments as a sustainable climate solution.

FLIP Perceptual Metric: Mitsuba Integration

Integrated FLIP into Mitsuba with color and feature pipelines to produce perceptual error maps, and matched NumPy baseline and profiled performance.

Interaction Design: Anti-Procrastination App

Applied goal-directed design for a prototype App: user interviews, personas, scenarios, interactive prototype, and usability evaluations.

Automatic Coffee Machine

Designed a Finite State Machine for a coffee vending machine in VHDL, and tested timing and functionality via simulation.

Database Design and Optimization

Built a relational database from scratch with ER modeling, SQL queries, indexing, and query optimization.

Collaborative Indie Game Jam in Unity

Team-developed Unity/C# games in 24–48h jams, fast prototyping under high time constraints with creative, collaborative design.

Experience

Computer Vision Intern

Schindler Group — Lausanne (Sept. 2024 – Feb. 2025)

Developed computer vision solutions to reconstruct 3D building surfaces and simulate heat flow for renovation planning
Built and optimized ML pipelines for 3D reconstruction using NeRF, SDF, and Plenoxel
Collected, processed, and prepared datasets for training, testing, and inference
Refined models to improve accuracy and robustness for industrial applications
Developed workflows with Docker and Microsoft Azure for reproducible ML deployment
Applied ML best practices in pipeline design, data management, and workflow planning

Computer Science Teacher

High School — Nyon (Aug. 2023 – July 2024)

Taught coding and computational thinking, adapting complex computer science concepts
Designed Python projects, guiding students in debugging, code structure, and algorithms
Mentored high schoolers, building robust problem-solving and algorithmic skills
Created lesson plans and assessments, ensuring involvement and progress tracking
Adapted teaching approaches to diverse skill levels, learning needs, and learning styles

PyGirl Tutor

Boston Consulting Group (BCG) — Online (Apr. 2022 – Apr. 2023)

Led online Python sessions for groups of up to 5 beginner students, mentoring programming and problem-solving skills
Fostered engagement and collaborative problem-solving among participants
Crafted tailored lesson materials and collaboratively optimized curriculum for online classes

Contact Me

Phone No.:
+41 78 448 65 75

Email:
juliette.parchet@gmail.com

Social Links: