Andreas Mueller's Email & Phone Number

💼 Past Experience

Michaela Walker, who teaches at York University in Toronto, Canada, says that "Andreas Mueller is a superb researcher who has frequentlyathoroughly investigated different questions related to data science. His research expertise is encompassed in a variety offields, including machine learning, graphical models, and data analysis, and he is particularlytalented when it comes to informatics. In addition to his brilliance as a researcher, Andreas has excellentpeople skills, and he is a very attentive and communicative leader. He is always willing to sharehis expertise with other investigators and continue to develop groundbreaking newmethods and tools."Walker says that, "one of the unique aspects of Mueller's work is his combination of brilliance as aninvestigator and good people skills. He is always willing to chat and open up about his work, and he is always willing to learn about newresearch developments. He also has a very good sense of what is important to his colleagues andbounces back quickly to share any suggestions or ideas. He has a genuine interest in helping others succeed and he is reallyable and supportive of his fellow researchers."

🎓 Education

Andreas Mueller's educational background and work readiness are based on his time as a doctor of philosophy (PhD), computer science at Rheinische Friedrich-Wilhelms-Universität Bonn / University of Bonn from 2009 to 2013, and as a diplomat, mathematics at Rheinische Friedrich-Wilhelms-Universität Bonn / University of Bonn from 2003 to 2009.Mueller completed a doctorate in computer science at Rheinische Friedrich-Wilhelms-Universität Bonn / University of Bonn in 2009, and a Diplom in mathematics at Rheinische Friedrich-Wilhelms-Universität Bonn / University of Bonn in 2003. Mueller's main focus in his doctoral studies was on the area ofComputing Science with a focus on mathematical methodologies. In particular, Mueller aimed to develop tools to improve the quality of data analysis and the correctness of algorithmic implementations.Mueller began his professional career at Google in 2003 as an algorithmista in the Google Thread Trustee Department. He also held several other responsible positions at Google, including leads on data engineering and data profiling, and director of the Google Neural Networks team. In his time at Google, Mueller developed the Google Neural Networks library and toolset, as well as worked on a number of high-profile projects, such as the Google Deepmind casino application.Mueller has held a number of other positions in the academic and industrial communities. He has acted as a liaison between Google and a number of research centers in top-tier countries, helping to foster strong relationships between Google employees and key research partners. He also served as a member of the executive committee of the World Union for Computational Physics, a non-profit organization that aims to improve the standing of computational physics.Mueller's work has earned Mueller several awards and distinctions. He was awarded the 2009 Nagel Award for his work on the Google Neural Networks library, the 2013 Computational Sciences Millennium Award, and the 2016 ACM SIGPLASH paper "A Unified Model of Algorithmic Variability in Data Analysis", which was featured in the ACM Press book "Peeking Inside: Mathematical and Computational Sciences Investigations into Parallel and Multiple Programming Algorithms". He has also been involved in a number of high-profile studies, such as the "Peterson-Lagrange Algebra of Mathematical Functions" study, the "Structured Neural Networks: A Comparison of manually-crafted and tensor-trained variants" study, and the "Multi-scale Neural Networks for Timeseries Analysis" study.Mueller is currently an investigator at the Google Research Institute for All Purpose Computing, where he is working on a number of important projects, including the "Transfunctional Algebra for Computational Physics" study, the "Multi-scale Neural Networks for Timeseries Analysis" study, and the "A Unified Model of Algorithmic Variability in Data Analysis" study. Mueller is also an instructor at Google Research, where he teaches computer science and mathematical methods.Mueller has a strong interest in teaching and2012 he founded the

💡 Technical & Interpersonal Skills

Andreas Mueller has experience in research, development, and teaching in the field of machine learning and data science. He has also been responsible for solving real-world problems at large scale.). He has a background in computer vision, along with experience in structural methods for semantic segmentation of images and in machine learning. He is currently a Research Intern at Microsoft in Cambridge, United Kingdom, where he worked on non-parametric graphical models for computer vision. Also, he worked at the Center for Data Science (NYU) in New York City for two years from 2014 to 2016. While at the Columbia University Data Science Institute he was responsible for developing machine learning and computer vision solutions to real world problems. Finally, he is a PhD Student at University of Bonn in Bonn, Germany, where he is focused on structured methods for semantic segmentation of images.