Thibault Douzon
Thibault Douzon is a French PhD candidate participating under the CIFRE industrial convention, improving the field of document understanding through language models and transformers.
Throughout his PhD journey, Thibault has navigated the intersection of academia and industry. His tenure at Esker, a prominent player in document processing and business workflow automation, allowed him to gain practical experience while shaping his expertise. Thibault has played a pivotal role in developing efficient language models that excel in extracting essential information from diverse business documents.
His contribution was further acknowledged when he was honored with the Nakano award at DAS 2022, recognizing his outstanding research paper entitled “Improving Information Extraction on Business Documents with Specific Pre-training Tasks” as the best of the event.
Peter Staar
Currently, Peter manages the ‘AI for Knowledge’ group at the IBM Research – Zurich Laboratory. The group focusses on the development of the Deep Search platform, which consists of cloud native services that ingest large corpora of technical documents and extracts the knowledge contained in them. Peter joined the IBM Research – Zurich Laboratory in July of 2014 as a post-doctoral researcher. The Belgium-born scientist first came to IBM Research as a summer student in 2006. Prior to joining IBM Research, He was a post-doctoral researcher in Theoretical Physics and PASC (Platform for Advanced Scientific Computing) at the Swiss Federal Institute of Technology (ETH) in Zurich, Switzerland.
He earned his PhD in Theoretical Physics and his M.Sc. degree in Physics at ETH Zurich in 2013 and 2009, respectively, and his B.S. degree in Physics (cum laude) from the KU Leuven, Belgium. Peter has twice been a finalist for the prestigious ACM Gordon Bell award, first in 2013 for his paper entitled ‘Taking a Quantum Leap in Time to Solution for Simulations of High-Tc Superconductors’ and then in 2015 for his paper entitled ‘An Extreme-Scale Implicit Solver for Complex PDEs: Highly Heterogeneous Flow in Earth Mantle.’ The last submission won the Gordon Bell prize. Other significant academic achievements include ‘Best Paper Award’ at IPDPS 2016 (for novel, linear-scaling graph analytics) and ‘Applied AI Application Award’ at IAAI 2021 (for novel PDF document conversion ML models).
John Corring
John Corring joined Microsoft as Senior Researcher in 2017 after completing his PhD at University of Florida in Computer Vision. During his tenure at Microsoft John has worked on and published on compositional modeling of text, layer separation, generative document modeling, and other problems as well as contributing to the state of the art in Azure OCR and document intelligence solutions.
Tong Sun
Tong is a research thought-leader and technology innovator with a 20+ years proven track of leadership in incubating, building and delivering cutting-edge AI/ML tools and methods that enable digital transformations cross multiple vertical domains, i.e. transportation, manufacturing, healthcare and retail. Most recently Tong has been spear-heading a generative AI research initiative at Adobe Research to reinvent the Future of Document Experiences. She holds 30+ issued US Patents, 55+ peer-reviewed publications in prestigious conferences and journals.