π Iβm currently studying π»Electrical Engineering and Information Technology @ π’ETH Zurich.
π My academic focus lies on all subtopics of π§ Machine Learning and ποΈComputer Vision.
π― I am also focused on developing my π¨βπ»Software Engineering skills.
π You can reach me at π§cyrknech [at] student [dot] ethz [dot] ch
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A list of languages, frameworks, tools etc. that I have used before or am currently using. Sorted by proficiency. The order within each proficiency category is random.
π Proficiency | π Languages | π¦ Packages | π οΈ Tools | π§ Frameworks | π» IDEs | π₯οΈ OS |
---|---|---|---|---|---|---|
π₯ Proficient | ||||||
πͺ Familiar | ||||||
π€ Used Before |
During my studies at ETH Zurich, I have worked on a variety of projects.
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Projects I have worked on in my free time. All available projects repositories that are public are linked below. The projects are listed in chronological order.
A web application that allows users to classify the sentiment of a given text. The application is built with Flask and deployed on Google Cloud using Google Kubernetes Engine.
- Building a web application with Flask
- Containerizing a web application with Docker
- Using Kubernetes
- Deploying a web application on Google Cloud
- Using GitHub Actions to build a CI/CD pipeline
Projects I have worked on for my studies at ETH Zurich. To respect the privacy of my fellow students and agreements with the respective labs, not all projects are public. All available project repositories that are public are linked below. The projects are listed in chronological order.
π§ Work In Progress π§
Generative Machine Learning for Radar-Based Vital Sign Monitoring: Explored the use of machine learning models to improve the performance of radar-based vital sign monitoring. Therefore, the performance of different machine learning models, including TCN(Temporal Convolutional Networks) and LSTM(Long Short-Term Memory), was compared to the performance of a traditional signal processing approach.
- Testing and comparing different machine learning architectures
- Ablations on data input structure, preprocessing, and output structure
- Working with raw Low-Power-FMCW radar data
Course | Project | Description |
---|---|---|
Robot Learning | Learning to Walk with World-Model-Based Reinforcement Learning | Used the Dreamer Reinforcement Learning algorithm to train a quadruped robot (Unitree Go1) to walk different terrains in the Isaac Gym environment. |
Software Engineering | No Limit Texas Hold'em Poker |
Developed a multiplayer poker game using C++ and wxWidgets. |
Deep Learning | Self-Augmentation Network for Sarcasm Generation with Synthetic Data |
Made use of GPT-2 to generate synthetic data and fine-tuned Bert for sarcasm detection. |
Smart Patch Flagship Project: Developed a smart patch wearable device to monitor the health of the wearer. My work was focused on the software side of the project. Therefore, i developed a basestation software package to communicate with smart patches and showcase their data in a web application. Further I developed a cross-platform mobile application to conveniently map smart patches to patients in the database.
- Working with an IoT platform
- Developing a cross-platform app with Flutter
- Developing a communication interface between the app and the IoT platform and the smart patch using MQTT and BLE in Python
Optogenetic stimulation of neuronal networks in vitro: Developed and assembled a system to stimulate neuronal networks in vitro with light.
- Building an optical setup
- Working in a wet lab
- Python programming