Prof. Guillermo De Ita Luna
Autonomous University of Puebla, Mexico
34 years as a Full Professor and researcher in the Computer
Science department at the Autonomous University of Puebla.
(BUAP), México. Currently, a member of the Mexican System of
Researchers at level 3 (the highest level). Guillermo De Ita
has made research stances in Texas A&M, Chicago University,
Lille – Inria France, as well as several Universities in
Mexico. He was the principal of the Computer Science Dept
(BUAP) from 1999 to 2003. He designed the engineering
program in computer science and participated as a founding
member of the master's and doctoral programs in Computer
Science at the Computer Science
Department from BUAP. He has supervised 59 thesis projects;
32 in bachelor ‘s level and 23 in posgrade level. He has
published 140 research articles in journals and conference
proceedings that underwent
rigorous double-blind peer review, along with 30 book
chapters. Additionally, he contributed as an author to the
publication of 5 books.
Prof. Antonios Saravanos
New York University (NYU), USA
Bio: Dr. Antonios Saravanos is Clinical (Full)
Professor of Information Systems at New York University
(NYU). He holds two doctorates, the first from Columbia
University (New York, USA) and the second from Bocconi
University (Milan, Italy), as well as graduate degrees from
the University of Oxford and the University of Cambridge in
the United Kingdom. A Senior Member of the Association for
Computing Machinery, Dr. Saravanos’s research examines the
drivers and barriers of technology adoption, trust, and
sustained engagement, with particular emphasis on
intelligent machines and “good tech”, examining the
influence of prosocial motivation and warm glow on user
intentions and continued use. He also collaborates on
applied AI projects that study learning dynamics in modern
models and develop predictive methods, including work in
medical imaging. In addition to his research, Dr. Saravanos
has played a significant role in curriculum development,
academic leadership, and faculty governance at NYU. He led
the creation of NYU’s first undergraduate "big data" degree,
the Bachelor of Science in Applied Data Analytics and
Visualization, served as its program coordinator from 2016
to 2022, and has been recognized for his efforts with the
NYU School of Professional Studies Outstanding Service Award
(2016) and the Teaching Excellence Award (2019).
Dr. Douglas Schmidt
William & Mary, USA
Bio: Dr. Douglas C. Schmidt is the Dean of the School
of Computing, Data Sciences & Physics at William & Mary,
where he leads initiatives at the intersection of artificial
intelligence, software engineering, and institutional
transformation. An internationally recognized researcher and
educator, his work explores how generative AI reshapes
software development, testing, and human-computer
collaboration, with a particular focus on intent-driven and
human-centered AI systems.
Before joining William & Mary, Schmidt held senior
leadership and faculty roles at Vanderbilt University and
Carnegie Mellon University’s Software Engineering Institute.
He has also collaborated extensively with industry and
government partners developing and testing large-scale,
software-reliant systems. He is a frequent speaker, author,
and advisor on the opportunities and risks of deploying AI
in real-world organizations, education, and critical
infrastructure. In his keynote, Schmidt examines how AI is
not just automating tasks, but redefining expertise, agency,
and the future of knowledge-driven institutions.