Invited Speakers

Opening Keynote

Jezabel R. García

AI Research Manager
Multiverse Computing

Jezabel R. Garcia is an AI Research Manager at Multiverse Computing, where she leads research on reinforcement learning and alignment, model compression and efficiency, and model evaluation. Before joining Multiverse, she spent several years at MediaTek Research, as a Senior Deep Learning Researcher, publishing on meta-learning and generalisation bounds for neural kernel models. She came to machine learning from experimental physics, having studied at the Max Planck Institute for Physics, where she worked on Cosmology and Astroparticle Physics. She also reviews for ML conferences and has represented Multiverse in UN discussions on international AI governance.

Opening Keynote

Antonio Tiene

Director of Research
Multiverse Computing

Antonio Tiene is the Director of Research at Multiverse Computing, where he directs the development of CompactifAI, the company's model compression and optimization framework. His work centers on a coordinated pipeline that combines tensor-network-based profiling, structured compression, and a healing stage that restores model quality through synthetic data generation, LLM-as-judge evaluation, quantization-aware training, and distillation. He has applied this methodology across more than 25 model families, spanning text, multimodal, audio, vision, and video architectures, including extreme compression projects for on-device deployment. He also oversees research on reinforcement learning, synthetic data generation, and knowledge editing, and has spearheaded a quantum-inspired AI research track exploring tensor network approaches to LLM architectures.

Afternoon Keynote

Elisabetta Farella, PhD

Head of E3DA Research Unit
Fondazione Bruno Kessler (FBK)

Elisabetta Farella, PhD, is head of the Energy Efficient Embedded Digital Architectures (E3DA) Research Unit at Fondazione Bruno Kessler (FBK) in Trento, Italy, where she leads research on Edge AI and TinyML. Her work focuses on energy-efficient and adaptive artificial intelligence for resource-constrained devices, spanning both inference and learning across the edge–cloud continuum. She works on a variety of data modalities, including computer vision, audio, and biosignal processing, enabling intelligent and sustainable systems at the extreme edge. Her research spans smart sensing, wearable computing, and the Internet of Things, with the goal of enabling distributed intelligence in real-world applications. She has extensive experience in national and European research projects and collaborates closely with both industry and academia. She contributes to the CAITE project within the IPCEI-CIS initiative as part of its core leadership team, advancing next-generation AI systems across edge and cloud environments. Elisabetta serves on the technical program committees of several international conferences in the areas of IoT, embedded systems, and Edge AI, and is Associate Editor of the Sustainable Computing: Informatics and Systems journal. She has co-authored more than 180 publications in international journals and conferences.