Gerald Friedland. Gerald Friedland is a German-American computer scientist and author specializing in multimedia computing, machine learning, and artificial intelligence. He is a principal scientist at Amazon Web Services and a professor at the Electrical Engineering and Computer Science Department of the University of California, Berkeley. He focuses on AutoML and generative AI. His work has advanced large-scale multimedia analysis, privacy-aware AI, and explainable machine learning.

Education 
Friedland completed his education in Germany, earning his Abitur in 1998. He received a Master of Science in Computer Science with a minor in Linguistics from Freie Universität Berlin in 2002. His master’s thesis, "Towards a Generic Cross Platform Media Editor: An Editing Tool for E-Chalk," was recognized as the best computer science master’s thesis in German-speaking countries by the German Association for Computer Science.

In 2006, Friedland earned his Ph.D. in Computer Science from Freie Universität Berlin, graduating summa cum laude. His dissertation, "Adaptive Audio and Video Processing for Electronic Chalkboard Lectures," was nominated for the university's Ernst-Reuter Award.

Career 
Friedland began his career in academia as a Research Associate in the AI group at Freie Universität Berlin from 2002 to 2006 under Raúl Rojas. During this time, he developed the "Simple Interactive Object Extraction (SIOX)" algorithm, now widely used in open-source tools like GIMP and Blender and conducted research on lecture webcasting technologies.

From 2006 to 2016, Friedland worked full-time with the International Computer Science Institute (ICSI) in Berkeley, California. He held various roles, from postdoctoral student over Principal Investigator to Director of the Audio and Multimedia group. As a Principal Data Scientist at Lawrence Livermore National Laboratory (2016–2019), Friedland led a team addressing challenges in explainable AI. 

In 2014, he founded Audeme, a company developing cloud-independent speech recognition hardware. In 2019, he co-founded Brainome, Inc. which he joined full-time until 2022 as CTO, leading the development of no-code machine learning solutions, leveraging the information-theory view of machine learning described in Information-Driven Machine Learning: Data Science as an Engineering Discipline.

Friedland served as director of conferences for ACM SIGMM (2017–2021), program co-chair for ACM Multimedia (2017), and associate editor for IEEE Multimedia Magazine and ACM Transactions on Multimedia Computing.

Research 
Friedland is a computer scientist specializing in the processing and analysis of multimedia data and machine learning. He is mostly known as the original author of the widely used "Simple Interactive Object Extraction" image and video segmentation algorithm, created as part of his PhD thesis, and as the co-author of a textbook on Multimedia Computing. He also led the initiative to create and release the YFCC100M corpus (see also: List of datasets for machine learning research), the largest freely available research corpus of consumer-produced videos and images. He co-founded the field of geolocation estimation for images and videos, sometimes also referred to as placing. Friedland also frequently uncovers privacy risks in multimedia publishing practice and heads the development of the teachingprivacy.org portal which provides educational materials for use in US high-schools as part of the AP Computer Science Principles and the Code.org initiative. Friedland is also the co-creator of MOVI, an open-source speech recognition board that allows the creation of cloudless voice interfaces for Internet of things devices.

Awards 

 UNESCO IRCAI Global Top-100 AI Project (2021) for his measurement-based approach to AI
 AI2000 Most Influential Scholar of the Decade (2009–2019)
 ACM Multimedia Grand Challenge Winner (2009)
 Best Paper Award at the IEEE International Conference on Multimedia Big Data (2019)
 Make Magazine Editor’s Choice Award (2015)

Publications 
Friedland has authored six books, including:
 Information-Driven Machine Learning: Data Science as an Engineering Discipline (Springer-Nature, 2023).
 Introduction to Multimedia Computing (Cambridge University Press, 2014).
 Beginning Programming Using Retro Computing (Apress, 2018).

He has also published over 100 peer-reviewed journal and conference articles on topics ranging from machine learning to multimedia computing.

References 

1978 births
Living people
German electrical engineers
German computer scientists
Lawrence Livermore National Laboratory staff
UC Berkeley College of Engineering faculty
German expatriates in the United States
Free University of Berlin alumni