Martin Schmitz
Bonn
Summary
Final year Ph.D. student at the National University of Singapore with expertise in deep learning and AI, specializing in reinforcement learning, contrastive learning, and geometric deep learning. Proficient in PyTorch and TensorFlow, complemented by strong analytical skills and a commitment to scientific excellence.
Overview
13
13
years of professional experience
Work History
Ph.D. Student
National University of Singapore
01.2021 - Current
- Designed and implemented deep learning pipelines for biological data, focusing on graph neural networks, graph transformers, and contrastive learning.
- Taught machine learning courses at NUS, supervised Bachelor’s/Master’s theses and research interns, and reviewed for leading ML conferences.
Research Assistant
Fraunhofer IAIS
04.2019 - 03.2021
- Research, implementation, and training of Machine Learning models in Natural Language Processing for research and industry-related projects.
Tutor
01.2013 - 01.2020
- Tutoring math to college and high school students (part-time).
Illustrator
01.2015 - 01.2018
- Freelance Illustrator.
Education
Ph.D. - Computer Science
NATIONAL UNIVERSITY OF SINGAPORE
Singapore11-2025
M.Sc. - Computer Science
UNIVERSITY OF BONN
05.2021
B.Sc. - Computational Visualistics
UNIVERSITY OF KOBLENZ
09.2017
Skills
- Machine Learning & AI: PyTorch, TensorFlow, Keras; deep learning model design, training & tuning; Transformers, Graph Neural Networks, Reinforcement Learning
- Mathematics & Statistics: Linear algebra, probability, optimization, statistical modeling
- Data Science: scikit-learn, Pandas, NumPy, SciPy, Matplotlib, etc
- Bioinformatics: genomics & computational biology
- Research: LaTeX, scientific writing
Personal Information
- Date of Birth: 05/26/95
- Nationality: German
Academic Activities
- Ph.D. Research – Geometric Deep Learning for Diploid De Novo Genome Assembly: Designed and implemented deep learning pipelines for biological data, with a focus on graph neural networks, graph transformers, and contrastive learning.
- Master’s Thesis – Solving Los Alamos Chess using Distributed Deep Reinforcement Learning and Proof Number Search: Developed AlphaZero-based reinforcement learning system with various extensions.
- Bachelor’s Thesis – A Comparison of Reinforcement Learning Algorithms for Dynamic and High-Dimensional Problems: Evaluated A3C, REINFORCE, and DQN on convolutional and linear models.
Timeline
Ph.D. Student
National University of Singapore
01.2021 - Current
Research Assistant
Fraunhofer IAIS
04.2019 - 03.2021
Illustrator
01.2015 - 01.2018
Tutor
01.2013 - 01.2020
Ph.D. - Computer Science
NATIONAL UNIVERSITY OF SINGAPORE
M.Sc. - Computer Science
UNIVERSITY OF BONN
B.Sc. - Computational Visualistics
UNIVERSITY OF KOBLENZ
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