Luis Winckelmann

Enhancing Search Algorithms with ML & NLP

- Leveraged HD Map data to integrate stop sign locations into the autonomous driving system. - Developed a ResNet-based traffic light detector capable of detection and classification, significantly enhancing autonomous driving capabilities. - Improved the driving score of previous thesis results by 23% on the LAV benchmark.

Conducted weekly tutorials, graded exams, and provided feedback on weekly assignments for the courses: - Analysis (term 2018) - Linear Algebra (term 2018/19) - Database Systems (term 2020)

Creating an interactive forecasting app to predict sales: - Implemented sales forecasting using the Multiple Aggregation Prediction Algorithm (MAPA), focusing on seasonal variations. - Developed an interactive forecasting application using R, Flexdashboard, and Shiny. - Achieved a 7% reduction in average delivery time by optimizing storage and pre-ordering processes

Working on a automatic clustering/classification algorithms for Leucemia based on Gen-Analysis: - Conducted analysis of high-dimensional, heterogeneous leukemia data (over 100 million samples) generated via flow cytometry. - Implemented theory-based Databionic algorithms, - Applied projection-based clustering with multiple projection and clustering methods. - Created and co-authored several R packages, e.g., FCPS: Fundamental Clustering Problems Suite, ProjectionBasedClustering, and GeneralizedUmatrix.

- Enhanced data integrity by cleaning datasets and handling anomalies and missing data. - Identified and addressed production bottlenecks for various material and machine combinations. - Boosted overall production speed by 15% through forecasting-driven optimization of order distribution.

Private math tutoring for high school stundents & graduates

- Grade: 1.2 - Specialized in Advanced Machine Learning Techniques and Probabilistic Modeling. - Coursework included: Deep Learning, Advanced Neural Networks, Self-Driving Cars, Data Mining and Probabilistic Reasoning, Probabilistic Inference and Learning, Statistical Learning, Reinforcement Learning, Programming in C/C++, Neural Data Analysis, Explainable Machine Learning, Mathematics for Machine Learning, Data Literacy - Thesis: LiDAR-based Object Detection for Planning Transformers:

- Grade: 1.6 - Robust foundation in Mathematics, Statistics, and Computer Science, specializing in mathematical statistics, database systems, and extracting insights from data. - Coursework included: Machine Learning, Statistics, Stochastic, Database Systems, Object-Oriented Programming, Algorithms and Data Structures, Efficient Algorithms, Software Engineering, Linear Algebra, Knowledge Discovery - Thesis: Similarity Search in Videos using Deep Learning