Sharon Hüffner
About Sharon Hüffner
Sharon Hüffner serves as the Chief Scientist at Theta Lake, where she has worked since 2017. With over 15 years of experience in data science, she has held significant roles at various high-tech companies and holds a PhD in Mathematics and Computer Science.
Current Role at Theta Lake
Sharon Hüffner serves as the Chief Scientist at Theta Lake, a position she has held since 2017. Based in the Berlin Area, Germany, she leads the development of advanced classifiers that integrate both traditional and innovative natural language processing (NLP) and computer vision (CV) techniques. Her work focuses on enhancing security and compliance within collaboration platforms. Hüffner has played a significant role in advancing the company's capabilities in text classification and object detection, particularly in 2021, and has integrated few-shot and semi-supervised learning techniques into the organization's data science processes.
Previous Experience in Data Science
Before joining Theta Lake, Sharon Hüffner worked as a Senior Data Scientist at Proofpoint from 2015 to 2017. She also held the position of Algorithm Designer at Websense (formerly PortAuthority Technologies) from 2005 to 2008. Additionally, she served as a Consultant at Nexgate Social Media Security & Compliance, focusing on text classification and machine learning from 2012 to 2014. Her extensive experience spans over 15 years in data science, with roles in leading high-tech companies.
Educational Background
Sharon Hüffner has a strong academic background in computer science and mathematics. She earned her Bachelor of Science (BSc) in Mathematics and Computer Sciences from Tel Aviv University, completing her studies from 2002 to 2006. She then pursued a Master of Science (MSc) in Computer Sciences at the same university from 2006 to 2009. Following this, she obtained a Doctor of Philosophy (PhD) in Mathematics and Computer Science from Freie Universität Berlin, where she studied from 2009 to 2014.
Research and Development Roles
Sharon Hüffner has held various research roles throughout her career. She worked as an MSc Research Student in Computer Science at Tel Aviv University from 2008 to 2009 and as a Research Assistant at Freie Universität Berlin from 2009 to 2014. Her research experience has contributed to her expertise in applying spectral theory and algorithms to real-world networks, further enhancing her capabilities in data science and algorithm development.
Technical Skills and Expertise
Sharon Hüffner possesses a diverse skill set in data science, particularly in the areas of text classification, machine learning, and algorithm design. She has experience in developing classifiers that utilize both classic and advanced NLP and CV methods. Her technical expertise is complemented by her academic background, which includes a focus on mathematics and computer science, allowing her to apply theoretical concepts to practical applications in security and compliance.