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Harshit sethi

@harshitsethi

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Research-focused machine learning engineer applying deep learning to physics and materials science.

Finland

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What I'm looking for

I seek research-oriented roles applying deep learning to physics or materials science, with opportunities for dataset creation, model development, and collaboration in academic or industry labs.

I am a research-focused machine learning engineer who develops deep learning models—especially convolutional and graph neural networks—to solve problems in physics, materials science and fusion diagnostics. My work includes automating tip-enhanced Raman spectroscopy, building custom datasets and fine-tuning detection and tracking models such as YOLO to improve PSNR and SSIM on experimental video data.

I hold an Erasmus Mundus master’s degree in Photonics for Security, Reliability and Safety and advanced AI coursework at Aalto University, and I have contributed to research at EPFL, Montanuniversität Leoben and the University of Cassino. I bring hands-on experience in data preprocessing, self-supervised learning, generative models, reinforcement learning simulations, and scientific computing with Python, PyTorch, CUDA and MPI.

Experience

Work history, roles, and key accomplishments

Current

Research Assistant

Current

Aalto University

Nov 2024 - Present (10 months)

Developing convolutional and graph neural network models to automate tip-enhanced Raman spectroscopy for quantum materials, advancing geometric deep learning approaches for materials science research.

Deep Learning Convolutional Neural Networks PyTorch Python Geometric Deep Learning data preprocessing

ÉL

Visiting Master Student

École Polytechnique Fédérale de Lausanne

Mar 2024 - Aug 2024 (5 months)

Conducted master’s thesis applying deep learning to track runaway electrons in JET tokamak data, built custom dataset, used self-supervised learning and autoencoders, and fine-tuned YOLO for detection and tracking.

Deep Learning YOLO Self Supervised Learning Python data preprocessing PSNR Computer Vision

Research Intern

University of Cassino and Southern Lazio

Sep 2023 - Sep 2023 (0 months)

Performed analysis of electric field measurements to identify computer operations as part of a NATO-funded project, applying advanced data analysis to process and interpret signals.

Python NumPy Pandas Matplotlib Data Processing Research Feature Extraction

Summer Research Intern

Montanuniversität Leoben

Jun 2023 - Aug 2023 (2 months)

Investigated reinforcement learning strategies to develop low-level control policies for a Unitree Go1 quadruped in simulation using ROS and Gazebo, focusing on control policy design and evaluation.

Reinforcement Learning ROS Gazebo Simulation Python Robotics Unitree Go1

Education

Degrees, certifications, and relevant coursework

Aalto University

Postgraduate coursework, Artificial Intelligence

2024 -

Advanced courses in AI including Deep Generative Models, Gaussian Processes, Probabilistic Machine Learning, and Programming Parallel Computers (2024 - Present).

Erasmus Mundus Joint Master’s Degree (QUANTEEM & PSRS consortium)

Master of Science, Photonics

2022 - 2024

Grade: Mention Très bien

Erasmus Mundus Joint Master’s in Photonics for Security, Reliability and Safety with modules in signal processing, image processing, Fourier optics, computer vision, machine learning and micro/nanotechnology; final grade: Mention Très bien.

St. Stephen's College, University of Delhi

Bachelor of Science (Hons), Physics

2019 - 2022

Grade: 8.973/10

Bachelor of Science (Hons) in Physics covering differential equations, numerical analysis, linear and tensor algebra, quantum mechanics and nanomaterials; final GPA 8.973/10.