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SUMMARY:PHAROS Training Series - Course 12 "Compute-Efficient Methods for 
 Large Language Models"
DTSTART;VALUE=DATE-TIME:20260717T080000Z
DTEND;VALUE=DATE-TIME:20260717T110000Z
DTSTAMP;VALUE=DATE-TIME:20260815T001945Z
UID:indico-event-216@events.grnet.gr
DESCRIPTION:\n\nPHAROS AI Factory announces the 12th Course of its Trainin
 g Series\, under the title "Compute-Efficient Methods for Large Language M
 odels"\, under the topic LLMs\, organised in collaboration with Pharos-CY
 \, held online via Zoom.  \n\nDate: July 17th\, 2026\, at 11:00 EEST \n
 \nLocation: Online via Zoom\n\nPresentation Language: English\n\nAudience
 : Data Scientists\, ML Engineers\, AI Engineers\, Academic Researchers\n\
 nLevel: Intermediate\n\nPrerequisites: Machine Learning\, Python\n\nLearn
 ing Objectives: \n\nBy the end of the seminar\, participants will be able
  to:\n\n\n	Identify key efficiency methods for training\, fine-tuning\, an
 d inference.\n	Describe how LoRA enables parameter-efficient fine-tuning o
 f LLMs.\n	Apply a basic Hugging Face workflow for dataset preparation\, tr
 aining\, evaluation\, and inference.\n	Compare trade-offs between model pe
 rformance\, cost\, memory use\, and deployment efficiency.\n\n\nInstructor
 s’ Short Bios:\n\n\n	Professor Constantine Dovrolis is Director of the C
 omputation-based Science and Technology Research Center (CaSToRC) at The C
 yprus 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 200
 2 to 2025 and is an ACM Distinguished Member. His research spans machine l
 earning\, 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 syste
 ms. His work has appeared at venues including ICML\, NeurIPS\, CVPR\, and 
 TMLR. He also collaborates broadly across neuroscience\, biology\, medicin
 e\, and climate science\, with funding from NSF\, NIH\, DOE\, DARPA\, Hori
 zon Europe\, and Cyprus’ RIF.\n\n\n \n\n\n	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 coordin
 ator in multiple projects at research centers and universities. Dr. Bakas 
 holds a Ph.D. from the National Technical University of Athens and has lon
 g-standing teaching experience. He also brings extensive programming exper
 tise in a wide range of languages and frameworks\, and the training semina
 rs he has organized have reached a broad community of engineers.\n\n\n \n
 \n\n	Roman Dolgopolyi is an Artificial Intelligence Developer at GRNET. He
  has extensive experience in training\, fine-tuning\, and benchmarking bot
 h Large Language Models and Vision-Language Models. His previous work has 
 been recognized in reputable academic journals and venues\, including Spri
 nger Nature publications and the EMCIS Conference.\n\n\n \n\nNote: Please
  enter your institutional/corporate email when registering.\n\n \n\nhttps
 ://events.grnet.gr/event/216/
LOCATION:
URL:https://events.grnet.gr/event/216/
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