I'm the Head of Visualization Research at Ozette Technologies – a biotech startup trying to digitize the Human immune system. I lead the research and development of scalable and intelligent data visualization and exploration tools for analyzing high-dimensional single-cell data to drive decision making and understanding.
I received my PhD in computer science from Harvard University, where I worked with Hanspeter Pfister and Nils Gehlenborg on scalable visualization tools for pattern-driven exploration of epigenomic data. Prior to my PhD, I was a visiting postgrad research fellow in the Department of Biomedical Informatics at Harvard Medical School, where I conducted research with Nils Gehlenborg and Peter J Park. I obtained a Bachelor and Master degree in bioinformatics from the Freie Universität Berlin in Germany.
My research has been recognized with several prestigious awards, including the EuroVis Best PhD Award, an IEEE VGTC Visualization Dissertation Award Honorable Mention, a Siebel Scholarship, the Best Paper Award from EuroVis 2020, and a Best Paper Honorable Mention from IEEE InfoVis 2020.
Harvard University, Cambridge, MA, United States.
Freie Universität Berlin and Charité – Universitätsmedizin Berlin, Berlin, Germany.
Freie Universität Berlin and Charité – Universitätsmedizin Berlin, Berlin, Germany.
Head of Visualization Research (07.2022 – Present)
Research Scientist (06.2021 – 07.2022)
Research Assistant
Research Intern
Visiting Postgrad Research Fellow in Biomedical Informatics
Research Assistant
Trainee
Visiting Research Assistant
Intern
Visiting Research Assistant
Intern
My dissertation "Scalable Visualization Tools for Pattern-Driven Data Exploration" received a Visualization Dissertation Award Honorable Mention from the IEEE Visualization and Graphics Technical Community .
My dissertation "Scalable Visualization Tools for Pattern-Driven Data Exploration" received the Best PhD Award from the EuroVis Conference .
Our poster abstract "Grammar-Based Interactive Visualization of Genomics Data" received the Best Abstract Award at the BioVis Symposium at ISMB 2021.
My dissertation "Scalable Visualization Tools for Pattern-Driven Data Exploration" received an Outstanding PhD Dissertation Honorable Mention from Computer Science at Harvard. Third best CS dissertation in the 2020-21 academic year.
Our paper "A Generic Framework and Library for Exploration of Small Multiples through Interactive Piling" received a Best Paper Honorable Mention at the IEEE Visualization Conference (InfoVis). Among the best 5 papers out of 250 submissions.
1-year scholarship of $35,000 for the final year of graduate studies from Siebel Scholars. The program recognizes the most talented students at the world’s leading graduate schools of business, computer science, bioengineering, and energy science.
Our paper "Peax: Interactive Visual Pattern Search in Sequential Data Using Unsupervised Deep Representation Learning" received the Best Paper Award at the EuroVis conference. Best paper out of 168 submissions.
Our poster on "Feature-Centric Visual Exploration of Genome Interaction Maps" received the Best Poster Award at the BioVis symposium at ISMB 2018 in Chicago.
My thesis "Ontology-guided exploration of biomedical data repositories" received the Best Master Thesis award in the informatics for life sciences (ILW) category from the German Informatics Society (GI) and German Association for Medical Informatics, Biometry and Epidemiology (GMDS).
6-year PhD fellowship from Harvard University.
6-month scholarship from Freie Universität Berlin and the German Academic Exchange Program (DAAD).
10-month scholarship comprised of a 6-month industrial internship and four months of full-time language courses in Japan to experience Japanese business and corporate culture.
I develop interactive, intelligent, and insightful data visualization systems for analyzing and exploring large-scale data on the web. I use visualization as the primary means of interacting with data and human-centered AI/ML methods to guide decision making at scale. My goal is to build new techniques that enable scientists to discover, explore, and compare data patterns efficiently to gain actionable insights at scale.
At Ozette Technologies my team and I develop novel intelligent data visualization and exploration tools for analyzing high-dimensional single-cell data to drive understanding and decision making at scale. Our research focuses primarily on:
A general theme of research that I'm exploring in recent years is how to effectively visualize high-dimensional data at scale.
The 4D Nucleome project was a large-scale NIH-funded effort to understand the principles underlying nuclear organization in space and time, the role nuclear organization plays in gene expression and cellular function, and how changes in nuclear organization affect normal development as well as various diseases. During my PhD, I developed visualization methods and tools for exploring and analyzing the datasets generated throughout the program.
Connectomics is the production and study of connectomes: comprehensive maps of connections within the mouse brain or eye. This project focuses on the segmentation, visualization and analysis of brain scans in electron and optical microscopy in the multi-terabyte range.
The Refinery Platform was a web-based system for data management, data visualization, and analysis of biomedical data sets powered by an ISA-Tab-compatible data repository. Analyses were implemented as Galaxy workflows and executed through the Galaxy API.
The Human Pluripotent Stem Cell Registry (hPSCreg) was created to offer the research community, legislators, regulators and the general public at large an in-depth overview on the current status of human pluripotent stem cell research in Europe.
The CellFinder project set out to map validated gene and protein expression, phenotype and images related to cell types. The data allowed characterization and comparison of cell types and could be browsed by using the body browser and by searching for cells or genes. All cells were related to more complex systems such as tissues, organs and organisms and arranged according to their position in development. CellFinder incorporated complex data exploration tools using visualization and analysis tools.
Invited Lecture Pfizer
Invited Talk CSCI3360: Human-AI Interaction at Boston College
Invited Talk Visual Analytics Laboratory at Tufts University
Invited Keynote Symposium on Biological Data Visualization (BioVis) at the International Conference on Intelligent Systems for Molecular Biology (ISMB)
Talk University of Massachusetts Boston: CS617 – Visualizing Boston
Seminar National Institute of Informatics, Japan
Talk SciPy Conference
Workshop National Science Foundation, US
Talk Symposium on Biological Data Visualization (BioVis) at the International Conference on Intelligent Systems for Molecular Biology (ISMB)
Invited talk Worcester Polytechnic Institute – Bioinformatics and Computational Biology Seminar
Invited talk Indiana University Bloomington
Paper presentation CHI Conference on Human Factors in Computing Systems
Invited talk University of British Columbia - Department of Computer Science
Invited talk The University of Edinburgh - School of Informatics
Invited talk Brown University - Data Science Institute
Invited talk University of Washington - Paul G. Allen School of Computer Science & Engineering
Invited talk University of Utah - School of Computing - Data Science Seminar
Paper presentation IEEE Visualization Conference (InfoVis)
Invited talk The University of Edinburgh, Visual+Interactive Data Group
Invited talk National Institute of Health (NIH), ENCODE, Analysis Working Group
Talk Symposium on Biological Data Visualization (BioVis) at the International Conference on Intelligent Systems for Molecular Biology (ISMB)
Paper presentation EuroVis conference
Guest lecture Boston College, CSCI 2254 Web Application Development
Guest lecture University of Massachusetts Boston, CS 410
Paper presentation IEEE Visualization Conference (InfoVis) Vancouver, Canada
Talk IEEE Visualization Conference (InfoVis), Doctoral Colloquium Vancouver, Canada
Talk SciPy Conference Austin, TX
Invited talk Harvard SEAS Nexus Cambridge, MA
Invited talk Bio-IT World Boston, MA
Invited talk University of Utah, Scientific Computing and Imaging Institute, Visualization Seminar Salt Lake City, UT
Talk Symposium on Biological Data Visualization (BioVis) at the International Conference on Intelligent Systems for Molecular Biology (ISMB) Chicago, IL
Tutorial Harvard Medical School, Hi-C Data Analysis Bootcamp Boston, MA
Paper presentation IEEE Visualization Conference (InfoVis) Phoenix, AZ
Invited talk Harvard - Novartis Machine Learning and Computational Meeting Cambridge, MA
Tutorial 4D Nucleome Annual Meeting Bethesda, MD
I'm interested in web-based software tools for visually exploring high-dimensional data and have (co-)created several popular open-source software projects. I primarily work in JavaScript/TypeScript and Python. These days I think a lot about frameworks for intelligent, composable, and scalable visualization software tools.
An Interactive Scatter Plot Widget. Explore datasets with millions of data points with ease in Jupyter Notebook, Lab, and Google Colab.
A simple, small, and content-agnostic modal for Svelte.