Prof. Magdalini Eirinaki
San José State University

Short Bio:


Dr. Magdalini Eirinaki is a Professor at the Computer Engineering Department and the program Director for the Master’s in Artificial Intelligence program at San Jose State University in California. Her research work covers recommender systems, machine learning, data mining, social graphs, and deep learning applications. Dr. Eirinaki is the recipient of the 2019 Newnan Brothers Award for Faculty Excellence, the 2017 Applied Materials Award for Excellence in Teaching and many of her students have been finalists in the California State University student research awards over the years.
Dr. Eirinaki received her PhD from the Department of Informatics of the Athens University Economics and Business and holds a Master’s degree in Advanced Computing from Imperial College and a Bachelor’s degree in Computer Science from University of Piraeus.

Recommender Systems: Methods, Challenges, and Opportunities

Abstract: In today’s data-driven world, recommender systems have revolutionized the way we discover and engage with content. In this presentation we will talk about the underlying methods that power these systems,  from collaborative filtering and content-based approaches to hybrid models powered by rich metadata. Through some real-life examples we will explore how recommender systems help businesses deliver personalized recommendations, enhance user engagement, and improve the user experience. Along the way, we will discuss inherent challenges, such as  data sparsity and cold start, scalability, evaluation, and ethical concerns related to privacy and bias. Finally, we will  highlight the immense potential and opportunities that lie ahead, especially in the era of deep neural networks and generative AI.

Dr. Christos Varytimidis

Short Bio:


Christos Varytimidis is currently a Principal Machine Learning Engineer at Workable. His work there includes designing, developing, and integrating AI systems based on Natural Language Processing and Understanding, Machine Learning, and Timeseries Analysis algorithms. Prior to that, he worked as a Machine Learning Engineer, with a focus on Computer Vision applications and NLP, for start-up companies in Silicon Valley, and as a Research Scientist for EU-funded research projects. His interests involve developing and integrating state-of-the-art machine learning algorithms for NLP and computer vision. Christos holds a PhD in Computer Vision from the School of Electrical and Computer Engineering in NTUA, and an Engineering Diploma from the same department.

AI systems in production environments

Abstract: In this talk, we will give insights into the usage of AI systems in real-world applications. What kinds of AI systems are used in production environments? What are the challenges? What are the steps from drafting a product requirement to a successful deployment? What is the lifecycle of such a system?

Dr. Ioulianna Litou

Short Bio:


Born in Albania, raised in Greece and worked in Greece, Belgium and currently Ireland. Iouliana is a Sr Project Manager at Meta with over 8 years of experience in R&D of Machine Learning, AI, and NLP projects, compilers, and distributed systems. She has experience in project management, team management, coordination, and facilitation of collaborative problem-solving, as well as mentorship and management of junior researchers and professionals. Additionally, she has experience in software security risk analysis, vulnerabilities identification, and project and software risk management. She has worked as a Researcher for different EU projects and as a Technical Project Manager/Lead Engineer at IBM prior to joining Meta.

Main Technologies:
Her main technologies include Python, Java, Scala, NLTK, GraphQL, Django, SQLAlchemy, SQL/NoSQL, IBM Cloud Services, Git, Watson Knowledge Studio, Vault, Redis, NodeRed, Postman, BPMN Flows, and C4 architecture modeling.

Background Studies:
 Ph.D. and master’s degree in computer science from Athens University of Economics and Business
 Global Online MBA from IE Business School


  • Senior Project Manager – Meta (Aug 2021– now)
  • Technical Project Manager – IBM (Mar 2019 – Aug 2021)
  • Researcher (Real-time & Distributed Systems Group) – UoA & AUEB (Nov 2013 – Jun 2019)
  • Web Developer – Freelancer (Jun 2011 – Jul 2015)

Navigating the challenges of a woman in Tech

Abstract: As much as we would like to believe otherwise, women in tech face some unique challenges. What are those? What can you do to overcome these and stand out? How can you do so, while staying true to your core values? These are fundamental questions to answer when navigating your way in a field that is traditionally a male dominant one. Also, it is important to understand that the challenges differ not solely based on the field, but the society as well. Further, did you know about the power of networking and mentoring in addressing these challenges? And how to know what to focus, given the plethora of skills required and the overwhelming speed of developments in the field? There’s always tips and tricks, that we can apply. And despite the recent developments in the field with layoffs, AI coding (chatGPT), etc., suggesting that this may be risky, or even saturated domain, we will touch on why these concerns are actually overstated.