Researcher & Developer
Daniel Dratschuk
Dual-degree student in Mathematics & Computer Science researching reinforcement learning, with expertise spanning theoretical foundations to practical AI implementations. Passionate about creating tools that accelerate human learning.
Academic Background
Bachelor’s Degree Courses:
- Analysis I
- Analysis II
- Analysis III
- Complex Analysis
- Linear Algebra I
- Linear Algebra II
- Abstract Algebra
- Stochastics
- Numerical Analysis I
- Computer-Aided Mathematics for Linear Algebra (using numpy)
- Computer-Aided Mathematics for Analysis (using sympy and matplotlib)
- Introduction to Functional Analysis
- Tropical Geometry
- Introduction to Topology
Master’s Degree Courses:
- Seminar: Introduction to Game Theory
- Advanced Seminar on Knot Theory
- Algebraic Number Theory I
- Topology I
- Topology II
- Introduction to Homotopy Theory
- Algebraic Geometry I
- Applied Statistics I (using R)
- Mathematical Statistics I
- Mathematical Statistics II
Bachelor’s Degree Courses:
- Programming
- Algorithms & Data Structures
- Introduction to Computer Networks, Databases, and Operating Systems
- Computer Architecture
- Theoretical Computer Science
- Programming Lab I
- Programming Lab II
- Machine Learning
- Deep Learning
- Data Science 2
Master’s Degree Courses:
- Advanced Deep Learning
- Operating Systems Development (using Rust)
- Isolation and Protection in Operating Systems (using Rust)
Featured Projects
Languages
100 %
🇩🇪
German
Native Speaker
95 %
🇺🇸
English
Fluent
90 %
🇯🇵
Japanese
Fluent
JLPT N1
70 %
🇷🇺
Russian
Advanced
Piano Performances
