The Siddata project developed a digital study assistant that helps students find relevant courses, learning resources, and study partners using personalized recommendations. I developed machine learning recommenders and worked extensively on its Django backend, turning a research prototype that previously took days to deploy into a containerized, tested, and easily deployable system. My masters thesis was also conducted in the scope of this project.
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For this thesis, I created a Conceptual Space from Course Descriptions for explainable Recommendation, in a highly performant pipeline on the university-grid.
Sub-Pages:
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A comprehensive course, with lectures and interactive assignments, about Scientific Programming in Python, offered for three years at the University of Osnabrück.
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As part of the practical course following the lecture The C++ Programming Language at the University of Osnabrück, we had two weeks to develop a complete game in a team of 11 students, including a level editor. The project involved working with libraries such as Box2D for physics and Boost, as well as the HDF5 data format. We decided to develop Bomberperson, a Bomberman-inspired multiplayer game with a few additional mechanics.
The Game
Bomberperson is a maze-based multiplayer game for 2-4 players, where the goal is simple: eliminate the other players and be the last one standing. Players can place bombs that explode after a short delay, sending explosions in multiple directions, destroying obstacles and potentially killing other players. Destroyed obstacles can drop power-ups, which can temporarily improve a player’s abilities or make their life more difficult.
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A speech-controlled meditation assistant and sentiment tracker
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Delving into the realm of self-driving cars for my bachelor’s thesis, I endeavored to optimize their tactical decisions, particularly speed, using cutting-edge deep neural networks and reinforcement learning in tensorflow within a transformed racing simulation. The resulting research platform, built on Unity, showcased the potential of real-time feedback and adaptability, offering valuable insights into the future integration of reinforcement learning in self-driving cars.
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In this 3D-Browser-Game developed in a computergraphics-project using
THREE.js, the player is trapped in the infamous burning AVZ and must try to escape this inferno. The player controls the in-game character and must overcome obstacles, puzzles and traps to get to the bottom and out of the AVZ. Play here!
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