Bio
Adam Day is a Data Scientist at SAGE Publishing. He has worked in the publishing industry since 2007 in a number of roles. As a data scientist, he has developed several methods for detecting research fraud.

Bio
Hong established and leads Atypon’s Intelligent Services Group, which designs and develops intelligent services to enrich, connect and analyze content and audience data by leveraging AI, big data, and cloud technologies. He also heads Atypon’s AI R&D Team, which designs artificial intelligence-based solutions and next-generation information discovery systems for scholarly research. His personal research passion is supporting publishers’ and researchers’ success in their transition to Open Access and Open Science. Before joining Atypon in January 2017, Hong applied machine learning algorithms for the insurance industry as the CTO of Digital Fineprint, served as a senior software engineer and development manager at Schlumberger, and developed racing games for the British video game developer Eutechnyx. Hong holds a PhD in 3D modeling with artificial intelligence algorithms from Aberystwyth University in Wales, an MBA in Digital Transformation & Strategy from University of Oxford, a master’s degree in computer science from The University of Sheffield, and certifications in AI and Cloud from Stanford University and Google. As well as serving as a distinguished expert in the National Key Laboratory of Knowledge Mining and Service for Medical Journals in China, Hong is widely published on computer science and AI topics and presents regularly at prominent industry events, most recently speaking on a panel for BioASQ with representatives from Google and NIH.

Bio
I’m Savvas, an Electrical and Computer Engineer from Thessaloniki, Greece. I completed a master’s of Data Science, at the University of Amsterdam, and currently I’m working as a Data Scientist for Elsevier. During my student years, work revolved around machine learning applications on graphs. Being part of a research team at Elsevier, I am part of an initiative to detect and distinguish paper mill activities, by employing NLP, graph and statistical methods for that purpose.