Clemens Schwarzmann ⛰️

About me

I am a double degree M.Sc. student in Computer Science and Machine Learning at the Technical University of Munich and KTH Royal Institute of Technology. My primary interests lie in machine learning and medical informatics, and enjoy tackling challenges in these fields. I am always eager to learn about new developments and to contribute to exciting projects. Below, you can find some of the projects I have worked on.

Interests

Machine Learning Computer Vision Computational Medicine Gaussian Splatting Self-Supervised Learning Medical Imaging

Experience

  1. Research Project – Predictive Modeling of Music Listening Behavior

    Ludwig-Maximilians-Universität München
    Developed predictive models for music preference and listening behavior using multimodal smartphone sensing data.
    Behavioral Data Analysis Mobile Sensing Statistical Inference R
  2. Research Practical – Machine Learning in Medical Imaging

    Technical University of Munich
    Created analytical framework for Gaussian Splatting and Neural Radiance Fields techniques in field of medical imaging diagnostics.
    Medical Imaging Gaussian Splatting Neural Radiance Fields Docker
  3. Research Practical – Machine Learning in Crowd Modeling

    Technical University of Munich
    Modeled crowd dynamics using classical and machine learning-based dynamical system approaches.
    Simulation and Modeling Dynamical Systems Time-Series Analysis
  4. Bachelor Thesis – Energy Modeling for Embedded Systems

    Technical University of Munich
    Designed an energy model for embedded systems and evaluated optimization strategies to reduce power consumption.
    Energy Modeling Embedded Systems Optimization Techniques
  5. Teaching Assistant – Algorithms & Data Structures and Computer Architecture

    Technical University of Munich
    Teaching of algorithm design, data structures, C Programming, and computer architecture.
    Algorithm Design Data Structures Computer Architecture Technical Communication
  6. Seminar Thesis – Automated Match Statistics

    Simpert-Kraemer-Gymnasium
    Designed and implemented a Python-based computer vision system using OpenCV to automate match statistics and gameplay analysis for table tennis with a 3D camera setup.
    OpenCV Object Tracking 3D Pose Estimation
  7. Robotics Project – Autonomous Rescue and Soccer Robots

    Simpert-Kraemer-Gymnasium
    Designed and implemented rescue and soccer robots with CAD, circuit design, and vision-based control.
    Embedded Systems Robotics Engineering Circuit Design OpenCV ROS

Education

  1. Double Degree – M.Sc. Computer Science & M.Sc. Machine Learning

    Technical University of Munich & KTH Royal Institute of Technology
    Currently pursuing a joint double degree in Computer Science and Machine Learning at TU Munich and KTH Stockholm.
  2. Double Degree – B.Sc. Computer Science & B.Ed. Mathematics/Informatics

    Technical University of Munich
    Completed dual degree in Computer Science and Science Education Mathematics/Informatics at TU Munich.
Skills & Hobbies
Technical Skills
Python
C++
PyTorch
OpenCV
Languages
English
German
Learning Swedish
Hobbies
Guitar & Bass
Hiking
Running
Soccer
Recent Projects
Self-supervised Vision Transformer are Scalable Generative Models for Domain Generalization featured image

Self-supervised Vision Transformer are Scalable Generative Models for Domain Generalization

Based on: Doerrich, S., Salvo, F. D., & Ledig, C. (2024). Self-supervised Vision Transformer are Scalable Generative Models for Domain Generalization (No. arXiv:2407.02900). arXiv. …

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Gaussian Splatting Conditioning and an Analytical Framework featured image

Gaussian Splatting Conditioning and an Analytical Framework

Introduction: Tooling for an explicit 3D representation Reconstructing realistic 3D scenes from a few photographs is one of the most exciting frontiers in computer vision, yet …

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Prediction of Alternative RNA Conformations with Dependency Map and VQVAE featured image

Prediction of Alternative RNA Conformations with Dependency Map and VQVAE

Introduction: Why alternative RNA structures matter Imagine an RNA transcript that can fold into two different secondary structures depending on its environment – each fold changes …

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Modeling Pedestrian Dynamics – When Physics Meets Data featured image

Modeling Pedestrian Dynamics – When Physics Meets Data

Understanding Pedestrian Motion: From Empirical Curves to Learned Behaviors Modeling how people move through space is an old problem with new relevance. Urban planners, architects, …

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High-resolution Piano Transcription with Pedals featured image

High-resolution Piano Transcription with Pedals

Based on: Kong, Q., Li, B., Song, X., Wan, Y., & Wang, Y. (2021). High-resolution Piano Transcription with Pedals by Regressing Onset and Offset Times. IEEE/ACM Transactions on …

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Resource-oriented Energy Analysis for IoT Sensors featured image

Resource-oriented Energy Analysis for IoT Sensors

Introduction: Energy as a first-class design constraint Energy efficiency is a critical consideration in battery-powered IoT devices, where prolonged autonomous operation is often …

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