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AI with and for Open Science

#openAI, #AIAct
  • 26 September 2023 |
  • 09:00
Main Auditorium


Natalia Manola


This session will include two short keynote speaches and a panel discussion on the topic of “AI with and for Open Science”. It will tackle this from different views, Ethics – Algorithms – Infrastructure, with the aim to see how AI supports researchers in their scientific discovery and what are the key ingridients for open infrastructures to make this happen.

One of the primary ways AI is changing academia is through data analysis. Researchers can leverage AI algorithms to analyze vast amounts of data quickly and efficiently. This enables them to identify patterns, correlations, and trends that may not be easily discernible through traditional methods. Moreover, AI tools are being used to generate content, write code, resolve accessibility issues, reconfigure writing processes and detect plagiarism. All this is reshaping researcher practice and culture in how they communicate, how they share, how they view infrastructure.

This session will tackle the “AI with and for Open Science” topic from three views, Ethics – Algorithms – Infrastructure:

  • Ethics in AI - principles and frameworks that put ethics and responsibility into practice in data analytics; dilemmas and challenges posed by work in AI and Data Science in the context of being transparent and accountable.
  • Large Language Models (LLMs) – controlling the future of (open) access to science; how Generative AI tools may influence ways scientific output is accessed and legitimized; challenges and opportunities in developing and hosting these models and services. 
  • Open Infrastructure fit for LLM – having open-source text generation models and variations of them is a good thing as it enables research communities to adapt models to their domains faster, and to cut costs. How do we achieve this?
We will start with two short keynote speeches (20 min each) from
and continue with a roundtable discucssion including the audience.


Haris Papageorgiou

Research Director, Athena Research Center / Co-founder, Opix
Haris is a co-founder and Chief Technical Officer of Opix, and Research Director at the Institute for Language and Speech Processing (ILSP) of Athena Research & Innovation Centre. Haris is responsible for building advanced content analytics and language technology for scalable systems and big data infrastructures. He is the Coordinator of the Technical Committee and Technical Responsible of operating the clarin:el shared distributed infrastructure, which is the Greek part of the European CLARIN infrastructure, making language resources, technology and expertise available to the humanities and social sciences research communities at large. He has held Chief Scientist positions in more than 30 European and national projects in the area of multilingual, multimodal and multimedia processing. Haris holds a Ph.D. in Computer Science and a B.Sc. in Electrical Engineering from the National Technical University of Athens, Dept. of Electrical Engineering, Division of Computer Science.

Saikiran Chandha

Co-founder, SciSpace
Saikiran Chandha is the co-founder and CEO of SciSpace, the leading AI Research Assistant that uses large language models to automate parts of the research workflow. He holds a Master's in CS and is a Stanford Ignite Fellow. Previously, he built Typeset, an AI tool to automate formatting of manuscripts, reaching over 500k users. Recognized in Times of India's 40 under 40 and is an active contributor to Forbes business council, Fast Company and Entrepreneur magazine.

Kaylin Bugbee

Data Scientist, NASA
Kaylin Bugbee is an applications data manager for the National Aeronautics and Space Administration (NASA) at Marshall Space Flight Center (MSFC). Her research focuses on Earth science informatics with an emphasis on making NASA’s data systems sustainable, resilient and maintainable while also enabling open science through reinforcing transparency, reproducibility and open access. She also works to generate, repair, improve, care for, document and update NASA’s science data to ensure they are available not only today but for the scientists and decision makers of the future. Ms. Bugbee is currently leading the implementation of NASA’s Science Discovery Engine, an enhanced search capability that allows scientists to search, filter and access data and information from across NASA’s five science topic areas: Astrophysics, Biological and Physical Science, Earth Science, Heliophysics and Planetary Science.