Magdalini Eirinaki
Professor, Computer Engineering Department
Academic Program Coordinator, MS in Artificial Intelligence
Preferred: magdalini.eirinaki@sjsu.edu
Telephone
Preferred: (408) 924-3828
Office: ENG 283F
Education
- PhD in Computer Science (Informatics), Athens Univ of Econ & Business, 2006
- MSc in Advanced Computing, Imperial College, London, United Kingdom, 2000
- BSc in Computer Science (Informatics), University of Piraeus, Greece, 1998
- Diploma in Music (Piano), Greek Ministry of Education, cum laude, 2006
Bio
Dr. Magdalini Eirinaki is a Professor at the Computer Engineering Department of the College of Engineering at SJSU. She also serves as the academic coordinator of the MS in Artificial Intelligence program. Her research interests span a broad range of machine learning, recommender systems, deep learning applications, social graph mining, and generative AI. She has published several papers in refereed journals and international conference proceedings in the above areas (links to selected publications are included below).
Prof. Eirinaki is an external member of the Board of Administration of Harokopio University. She also serves on the steering committee of the Silicon Valley Women in Engineering conference series and is a guest editor of FGCS's special issue on Big Data Computing Service and Machine Learning Applications. She is also serving in multiple senior roles in journals and conference in her research area.
Prof. Eirinaki is the recipient of the 2019 Newnan Brothers Award for Faculty Excellence, the 2017 Applied Materials Award for Excellence in Teaching and received the SJSU distinguished faculty mentor award in 2015, 2019, 2020, 2022, and 2023.
Her research is funded by NSF, CAHSI/Google, CA Learning Lab, EU Horizon (Marie Slodowska-Curie Actions), and IBM.
Links
- Selected publications (ORCID, DBLP, Google Scholar)
- Interviews
Recent News
- (5/2025) Martin Alvarez-Lopez (MS Software Engineering '25) presented his paper "The Impact of Tree Data on Urban Heat Island Mapping: A San Jose Case Study" at the 2025 IEEE Conference on Artificial Intelligence (IEEE CAI 2025).
- (4/2025) Tanvi Guttula (BS Software Engineering '24) and Johnathon Lu (BS Software Engineering '24) presented their paper "LifeTone: Personalized Skin Care Analysis at your Fingertips" at the 5th Annual Conference for CSU Undergraduates (CS CSU 2025).
- (3/2025) Our paper "Cloudsweeper: Leveraging Large Language Models to Personalize Sensitive Archive Search" was accepted as a poster and will appear in the proceedings of the 6th IEEE SVCC Conference.
- (2/2025) Our project "SpartanAI: Elevating Course Design with Faculty and Student-Centric AI Agent" was awarded an AIFAST Challenge Grant by the State of California (CA Learning Lab).
- (11/2024) Our paper "Federated Learning on Recommender Systems" appears in proceedings of IEEE Big Data 2025.
- (9/2024) Dr. Eirinaki and Dr. Potika participate in the "MUSIT" ("MUlti-Sensor Inferred Trajectories") project, that was selected for funding by EU's Horizon/Marie Sklodowska-Curie Actions.
- (9/2024) IBM donated $50K of cloud credit to Dr. Eirinaki's lab via the IBM SkillsBuild initiative, to develop an LLM-based project focused on sustainability.
- (8/2024) Dr. Eirinaki was elected to serve as an external member of the Board of Administration of Harokopio University.
- (7/2024) Our project "HSI Pilot Project: CollaborAIte: Empowering Faculty to Enhance Belonging, Retention, and Collaborative Learning Skills through AI Literacy Education" (with Dr. Y. Liu and Dr. W. Wu) got selected for funding by NSF.
- (7/2024) Our paper "Scalable and Autonomous Network Defense Using Reinforcement Learning" is published in IEEE Access.
- (7/2024) Our project "Cloudsweeper: Leveraging Language Models to Personalize Sensitive Archive Search" (with Dr. C. Kanich, UIC) got selected for funding by the CAHSI-Google Institutional Research program.
- (5/2024) Our paper "Multi-Resolution Diffusion for Privacy-Sensitive Recommender Systems" is published in IEEE Access. An earlier pre-print version is available via arXiv.
Funded by:
