Alex Bäuerle

Researcher

My research is at the intersection of AI and HCI. In this context, I am always searching for the best method to connect humans with AI systems. I try to help developers with techniques that foster communication, use visualizations to provide insights during development, and work on explanations that help humans understand the decisions their AI systems make.

Education

Ph. D. in Computer Science at Ulm University

Jan 2018 - Dec 2022

Supervised by Timo Ropinski, funded by the Carl-Zeiss-Scholarship

M. Sc. in Media Informatics at Ulm University

Oct 2015 - Jun 2017

Grade: 1.1, supervised by Timo Ropinski

B. Sc. in Media Informatics at Ulm University

Oct 2012 - Sep 2015

Grade: 1.2, supervised by Marc Schickler and Manfred Reichert

Positions

Founding Member of Technical Staff

May 2024 - Present

AI + Biology

Postdoctoral Researcher, Carnegie Mellon University

Oct 2023 - May 2024

Research and development of tools in the areas of AI evaluation and prompt engineering.

Research Scientist, Sigma Computing

Oct 2022 - Jun 2023

Bringing data and analysts closer together with the help of visualization and AI.

Research Intern, Apple Machine Intelligence

Mar 2021 - Sep 2021

Designed and developed a framework for component-based ML interfaces which can be composed in different environments such as computational notebooks and web dashboards.

Research Intern, Google TensorBoard

Jun 2020 - Sep 2020

Designed and implemented a visualization approach for a novel bias detection algorithm. This visualization is designed to support large label spaces and multilabel classification problems.

Research Intern, Google PAIR

May 2019 - Aug 2019

Invented and experimented with a technique similar to Feature Visualization, but for language models.

Publications

Humboldt: Metadata-Driven Extensible Data Discovery

VLDB 2024 Workshop: Tabular Data Analysis (TaDA), 2024

Alex Bäuerle , Çağatay Demiralp , andMichael Stonebraker

mint: Integrating scientific visualizations into virtual reality

Journal of Visualization, 2024

Sergej Geringer , Florian Geiselhart , Alex Bäuerle , Dominik Dec , Olivia Odenthal , Guido Reina , Timo Ropinski , andDaniel Weiskopf

An In-depth Look at Gemini’s Language Abilities

ArXiv, 2023

Syeda Nahida Akter , Zichun Yu , Aashiq Muhamed , Tianyue Ou , Alex Bäuerle , Ángel Alexander Cabrera , Krish Dholakia , Chenyan Xiong , andGraham Neubig

VegaProf: Profiling Vega Visualizations

UIST, 2023

Junran Yang , Alex Bäuerle , Dominik Moritz , andÇağatay Demiralp

Semantic Hierarchical Exploration of Large Image Datasets

EuroVis Short Papers, 2023

Alex Bäuerle , Christian van Onzenoodt , Daniel Jönsson , andTimo Ropinski

Neural Activation Patterns (NAPs): Visual Explainability of Learned Concepts

arXiv, 2022

Alex Bäuerle , Daniel Jönsson , andTimo Ropinski

Symphony: Composing Interactive Interfaces for Machine Learning

CHI, 2022

Alex Bäuerle , Ángel Alexander Cabrera , Fred Hohman , Megan Maher , David Koski , Xavier Suau , Titus Barik , andDominik Moritz

Where did my Lines go? Visualizing Missing Data in Parallel Coordinates

EuroVis, 2022

Alex Bäuerle , Christian van Onzenoodt , Simon der Kinderen , Jimmy Johansson Westberg , Daniel Jönsson , andTimo Ropinski

exploRNN: Understanding Recurrent Neural Networks through Visual Exploration

The Visual Computer, 2022

Alex Bäuerle , Patrick Albus , Raphael Störk , Tina Seufert , andTimo Ropinski

Visual Identification of Problematic Bias in Large Label Spaces

ArXiv, 2022

Alex Bäuerle , Aybuke Gul Turker , Ken Burke , Osman Aka , Timo Ropinski , Christina Greer , andMani Varadarajan

Net2Vis - A Visual Grammar for Automatically Generating Publication-Tailored CNN Architecture Visualizations

TVCG, 2021

Alex Bäuerle , Christian van Onzenoodt , andTimo Ropinski

Measuring Model Biases in the Absence of Ground Truth

AIES, 2021

Osman Aka , Ken Burke , Alex Bäuerle , Christina Greer , andMargaret Mitchell

What does BERT dream of?

VISxAI, 2020

Alex Bäuerle , andJames Wexler

Classifier-Guided Visual Correction of Noisy Labels for Image Classification Tasks

EuroVis, 2020

Alex Bäuerle , Heiko Neumann , andTimo Ropinski

Automatic identification of crossovers in cryo‐EM images of murine amyloid protein A fibrils with machine learning

Journal of Microscopy, 2020

Mattthias Weber , Alex Bäuerle , Matthias Schmidt , Matthias Neumann , Marcus Fähndrich , Timo Ropinski , andVolker Schmidt

Convolutional neural network (CNN) applied to respiratory motion detection in fluoroscopic frames

International Journal of Computer Assisted Radiology and Surgery, 2019

Christoph Baldauf , Alex Bäuerle , Timo Ropinski , Volker Rasche , andIna Vernikouskaya

Talks

Unlocking Model Performance Insights with Zeno

Fri Jan 26 2024

Multimodal Weekly

Where did my Lines go? Visualizing Missing Data in Parallel Coordinates

Wed Jun 15 2022

EuroVis 2022, Rome, Italy

Symphony: Composing Interactive Interfaces for Machine Learning

Wed May 04 2022

ACM CHI 2022, New Orleans, LA, USA

Net2Vis - A Visual Grammar for Automatically Generating Publication-Tailored CNN Architecture Visualizations

Thu Oct 28 2021

IEEE VIS 2021, New Orleans, LA, USA (remote)

Visualization for AI in Critical Domains

Mon Oct 26 2020

Bio+Med+Vis Spring School, Brno, Czech Republic (remote)

What Does BERT Dream Of?

Mon Oct 26 2020

VISxAI 2020, Salt Lake City, UT, USA (remote)

Classifier-Guided Visual Correction of Noisy Labels for Image Classification Tasks

Wed May 27 2020

EuroVis 2020, Norrköpping, Sweden (remote)

Automatic Fibril-Crossover Detection in EM-Images using Deep Convolutional Networks

Thu Apr 12 2018

MedVis Workshop 2018, Ulm, Germany

Teaching

Lecture: Deep Learning for Graphics and Visualization

2019 - 2022

Created and regularly held one chapter on visualization for AI at Ulm University. Talk about different explainability techniques and visualization concepts that help investigate and communicate about AI systems.

Projects: Visualization and Explainability for AI

2017 - 2022

Supervise undergrad and grad students in regular projects. We go through the process of ideation, implementation, and writing about these projects.

Seminars: Visualization and Explainability for AI

2017 - 2022

Held regular seminars for both undergrad and grad students.

Mentoring

Junran Yang

Jun 2022 - Dec 2022

Research Intern, Sigma Computing

VegaProf: Profiling Vega Visualizations

Lena Wiedmann

Dec 2021 - Aug 2022

Bachelor Thesis, Ulm University

Creating an Interactive UI for Human/AI Collaboration in Poster Design Processes

Simon der Kinderen

Feb 2021 - Nov 2021

Master Thesis, Ulm University

Visualizing Missing Data in Parallel Coordinates

Shasa Fringston

Feb 2021 - Oct 2021

Bachelor Thesis, Ulm University

Generating Synthesizer Presets from Audio with a Neural Network

Marios Sirtmatsis

Feb 2021 - Aug 2021

Bachelor Thesis, Ulm University

Visualizing Deep Reinforcement Learning

Raphael Störk

May 2019 - Feb 2020

Bachelor Thesis, Ulm University

leaRNN: Eine Interaktive Visualisieurng rekurrenter neuronaler Netze

Christoph Baldauf

Jun 2018 - Jan 2019

Master Thesis, Ulm University

Convolutional Neural Networks (CNN) Applied to Respiratory Motion Detection in Fluoroscopic Frames

Funding

Ph. D. Scholarship: Visualization Techniques to Support Training and Analysis of Neural Networks

Jan 2018 - Dec 2021

Carl-Zeiss Scholarship for PhD Students

Undergraduate Scholarship

Oct 2012 - Sep 2015

German Stipend for Excellent Students

Reviewing and Service

VGTC - Industrial Relations Chair (2023 - Present)

VISxAI - Program Committee (2022 - Present)

TVCG (2020 - 2023)

VIS (2021, 2023)

CHI (2021, 2023)

UIST (2022)

CG&A (2022)

EuroVIS (2022)

IMWUT (2022)

VCBM (2022)

MICCAI (2022, 2023)