Teaching

Below you can find information regarding current and upcoming courses focused on the intersections of data visualization, interactive computing, and biomedical analytics, followed by historical teaching records and thesis supervision.

Current & Upcoming Courses

Information Visualization (CS-GY 6313)

Being able to analyze and present data visually has become one of the most important skills for students who want to work in data science and related fields. This graduate course teaches you how to design effective interactive visualizations of complex data for data understanding, discovery, and presentation. The course is an intense blend of theoretical knowledge and practical work aimed at developing a well-rounded set of skills to ideate, design, implement, and evaluate sophisticated data visualizations.

The theoretical track provides a mental model to think about the visualization design space in a principled manner, covering visual encoding theory, human perception mechanisms, and color choices. The practical track teaches frontend web skills needed to build effective interactive visualizations on the web, incorporating practical labs on exploratory data analysis, sketching, design critique, and a series of technical individual assignments using JavaScript, SVG layouts, and the D3.js library framework.

Advanced curriculum topics span geographic visualizations, time-varying data tracking, network graphs, multivariable data displays, and dynamic dashboard views (brushing, linking, zooming). Course requirements involve comprehensive tracking via individual homework assignments, continuous concept quizzes, a pen-and-paper midterm exam, individual mini-projects (Geo+Time and Networks tracks), and a final collaborative group development project where student teams build, evaluate, and present functional interactive visualization systems.

Biomedical Visual Analytics (BMIN-GA 9223 & CS-GY 9223 P)

Analyzing and presenting high-dimensional biological data visually has become an increasingly important skill for students entering bioinformatics and computational biology. This course bridges robust computational processing pipelines with visualization design and development, teaching students how to engineer interactive visualization systems tailored for complex biomedical domains including digital pathology, single-cell genomics sequencing, health records, and clinical informatics.

The curriculum structure blends initial foundational lectures covering biomedical visual analytics architectures and steerable, interpretable AI interface tooling. This class is cross-registered across Computer Science and Bioinformatics programs. Students organize into interdisciplinary research teams, select specific scientific focus areas (such as Electronic Health Records, Radiology, Multi-Omics layouts, Wearable Biosensor Informatics, or Structural Protein Folding models), and study relevant advanced literature to summarize and present to the class.

Following the seminar component, groups engage in an intense hands-on research project utilizing authentic datasets to engineer a custom visual analytics solution. Development is strictly monitored across milestones—spanning project proposals, specification documents, interactive prototypes (leveraging Python and optionally JavaScript/Jupyter configurations), and a final tool delivery. The course concludes with an evaluation presentation and a written research report styled as a short scientific paper suitable for biomedical journal or conference tracks.

Historical Teaching Records

• [Spring Term 26] Lecturer: Information Visualization
• [Fall Term 25] Lecturer: Information Visualization
• [Spring Term 25] Lecturer: Information Visualization
• [Fall Term 24] Lecturer: Information Visualization
• [Winter Term 20/21] Teaching Fellow: CS171 - Visualization
• [Summer Term 20] Teaching Fellow: CS271 - Topics in Data Visualization
• [Winter Term 19/20] Teaching Fellow: CS171 - Visualization
• [Winter Term 18/19] Teaching Fellow: CS171 - Visualization
• [Winter Term 17/18] Lesson: Geographic Visualization as part of the Information Visualization Course
• [Summer Term 17] Seminar: Information Visualization of High-Dimensional Data
• [Winter Term 16/17] Lesson: Geographic Visualization as part of the Information Visualization Course
• [Summer Term 16] Seminar: Interactive Visualization
• [Winter Term 15/16] Seminar: Virtual Reality
• [Winter Term 15/16] StuPro "Crowd"
• [Summer Term 15] StuPro "Crowd"
• [Winter Term 14/15] Exercise Group: Information Visualization and Visual Analytics
• [Summer Term 14] Seminar: Techniques and Toolkits for Data Visualization
• [Winter Term 13/14] Seminar Visual Analytics von sozialen Medien
• [Summer Term 13] Elaboration for: Datastructures and Algorithms Course
• [Winter Term 12/13] Exercise Group: Artificial Intelligence Foundations

Group Leadership & Team Management

I am currently leading a biomedical visualization research lab at NYU Tandon. Since 2014, I have managed and supervised 14 student trainees/researchers working on visualization research and software development tasks for the EU H2020 research project CIMPLEX and the Human Tumor Atlas Network (HTAN) as part of the NCI-funded Cancer Moonshot Initiative. This responsibilities included project management, task assignments, weekly progress updates, and personnel management. From 2021-2023, I served as a subgroup leader at the Visual Computing Group (VCG), Harvard University, managing visual analytics and data tracking partnerships with the Laboratory of Systems Pharmacology at Harvard Medical School.

Thesis Supervision & Advising

• [Master Thesis] Scalable Web-Based Multi-Volume Rendering, 2022/2023
• [Master Thesis] Cell-Cell Interaction in 3D High-resolution Multiplexed Imaging Data, 2022/2023
• [Master Thesis] Visual Spatial Neighborhood Analysis to Study Cell-Cell Interactions in Human Tissue, 2020/2021
• [Master Thesis] Visual Prediction of Quantitative Information using Social Media Data, 2017
• [Master Thesis] Visual Analytics of City Dynamics using Soical Media Data, 2016/2017
• [Bachelor Thesis] VIsual Interactive Map Matching of Large Movement Datasets, 2016/2017
• [Bachelor Project] Visual Analysis of Driver Behavior Based on Large Taxi Fleet Data, 2016
• [Bachelor Thesis] Extension of a Query Visualization for Event Sequences, 2016
• [Master Thesis] Semi-automated Detection of Opinion Patterns in News Articles, 2015/2016
• [Bachelor Thesis] Exploration of Complex Datasets in Multi-Display Environments, 2015/2016
• [Bachelor Project] Cross-Media Orchestration Workbench for Decision-making, 2015/2016
• [Bachelor Project] Interaktive Exploration of Immersive Illuminated 3D Scatterplots, 2015
• [Bachelor Thesis] Visual Analysis of Information Diffusion for Civil Protection, 2014/2015
• [Bachelor Thesis] Interactive Trajektory Clustering based on a Partition-and-Group Clustering Framework, 2014/15
• [Diploma Thesis] Visualisierung von Besucherbewegungen in Innenräumen, 2014
• [Bachelor Thesis] Visual Analytics of Dynamic Computer Network Data, 2013
• [Bachelor Thesis] Processing Dynamic Computer Network Data for Visual Analysis, 2013
• [Bachelor Application Study] Evaluation of Available Visual Analytics Toolkits using Benchmark Datasets, 2013