PHAROS AI Factory announces the 12th Course of its Training Series, under the title "Compute-Efficient Methods for Large Language Models", under the topic LLMs, organised in collaboration with Pharos-CY, held online via Zoom.
Date: July 17th, 2026, at 11:00 EEST
Location: Online via Zoom
Presentation Language: English
Audience: Data Scientists, ML Engineers, AI Engineers, Academic Researchers
Level: Intermediate
Prerequisites: Machine Learning, Python
Learning Objectives:
By the end of the seminar, participants will be able to:
- Identify key efficiency methods for training, fine-tuning, and inference.
- Describe how LoRA enables parameter-efficient fine-tuning of LLMs.
- Apply a basic Hugging Face workflow for dataset preparation, training, evaluation, and inference.
- Compare trade-offs between model performance, cost, memory use, and deployment efficiency.
Instructors’ Short Bios:
- Professor Constantine Dovrolis is Director of the Computation-based Science and Technology Research Center (CaSToRC) at The Cyprus Institute and, starting in September 2026, XM Chair in Artificial Intelligence at the University of Cyprus. He served on the faculty of the School of Computer Science at the Georgia Institute of Technology from 2002 to 2025 and is an ACM Distinguished Member. His research spans machine learning, network science, and data-driven modeling, with a recent focus on neuro-inspired artificial intelligence. A central question in his work is how principles underlying the structure and function of brain networks—such as sparsity, modularity, plasticity, and hierarchy—can guide the design of more adaptive, efficient, and interpretable learning systems. His work has appeared at venues including ICML, NeurIPS, CVPR, and TMLR. He also collaborates broadly across neuroscience, biology, medicine, and climate science, with funding from NSF, NIH, DOE, DARPA, Horizon Europe, and Cyprus’ RIF.
- Dr. Nikos Bakas is a Senior Data Scientist at GRNET with a broad background in Artificial Intelligence. He has authored numerous publications across AI thematic areas including Machine Learning, Numerical Methods, Optimization, and Large Language Models. He has served as principal investigator, researcher, and coordinator in multiple projects at research centers and universities. Dr. Bakas holds a Ph.D. from the National Technical University of Athens and has long-standing teaching experience. He also brings extensive programming expertise in a wide range of languages and frameworks, and the training seminars he has organized have reached a broad community of engineers.
- Roman Dolgopolyi is an Artificial Intelligence Developer at GRNET. He has extensive experience in training, fine-tuning, and benchmarking both Large Language Models and Vision-Language Models. His previous work has been recognized in reputable academic journals and venues, including Springer Nature publications and the EMCIS Conference.
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