{"id":78,"date":"2026-03-16T18:39:13","date_gmt":"2026-03-16T17:39:13","guid":{"rendered":"https:\/\/project.inria.fr\/finality1stphdschool\/?page_id=78"},"modified":"2026-09-04T21:38:02","modified_gmt":"2026-09-04T19:38:02","slug":"program","status":"publish","type":"page","link":"https:\/\/project.inria.fr\/finality1stphdschool\/program\/","title":{"rendered":"Program"},"content":{"rendered":"\nLocation: Jacques Morgenstern Amphitheatre, Kahn building, Inria Centre at Universit\u00e9 C\u00f4te d’Azur, 2004 Route des Lucioles, 06410 Biot, France\n
\n\n\n\n\n\n \n \n\n\n\n\n\n\n\n
Time\n<\/th>Tuesday 8 Sep\n<\/th>Wednesday 9 Sep\n<\/th>Thursday 10 Sep\n<\/th>Friday 11 Sep\n<\/th><\/tr>\n\n
08:30-09:00<\/td>\n Registration<\/td>\n<\/tr>\n\n
09:00-10:30<\/td>\n Opening<\/td>\nKeynote: AI in radio access networks: challenges and open problems<\/a>
\nSpeaker: Zwi Altman (Orange Lab)\n<\/td>\n		Course: Robust Machine Learning: A Quest to Learning in Untrusted Environment (I)<\/a>\n
\nSpeaker: Nirupam Gupta (University of Copenhagen)\n<\/td>\n		Course: Robust Machine Learning: A Quest to Learning in Untrusted Environment (II)<\/a>\n
\nSpeaker: Nirupam Gupta (University of Copenhagen)\n<\/td>\n<\/tr>\n\n
\n\nKeynote: Distributed AI at the Edge\n<\/a>\n
Speaker: Alexandru Dobrila (Hivenet\/Antimatter)\n<\/td>\n<\/tr>\n\n\n
10:30-11:00<\/td>\nBreak<\/td>\n<\/tr>\n\n
11:00-12:30<\/td>\n\nLecture: Distributed inference in the edge-network-cloud continuum<\/a>\n
Speaker: Fr\u00e9d\u00e9ric Giroire (CNRS)<\/td>\n		Lecture: Bayesian optimization: Theory and applications to telecommunications<\/a>
\nSpeaker: Lorenzo Maggi (NVIDIA)\n<\/td>\n		Course: Reinforcement learning: from bandits to structured MDPs (I)<\/a>\n
\nSpeaker: Bruno Gaujal (Inria)\n<\/td>\n		Course: Reinforcement learning: from bandits to structured MDPs (II)<\/a>\n
\nSpeaker: Bruno Gaujal (Inria)\n<\/td>\n<\/tr>\n\n
12:30-14:00<\/td>\nLunch<\/td>\n<\/tr>\n\n
14:00-15:30<\/td>\nLecture: The Road to Autonomous Networks: AI\/ML Foundations and Frontiers<\/a>\n
Speaker: Farnaz Moradi (Ericsson)\n<\/td>\n		Panel:<\/strong> Application and Role of AI in Industry
\nPanelists: \n
  • Zwi Altman (Orange)<\/li>\n
  • Alexandru Dobrila (Hivenet\/Antimatter)<\/li>\n
  • Lorenzo Maggi (NVIDIA)<\/li>\n
  • Farnaz Moradi (Ericsson)<\/li>\n<\/td>\n
    		• Student Presentations (Session 3<\/a>)<\/td>\nStudent Presentations (Session 5<\/a>)<\/td>\n<\/tr>\n\n
    15:30-16:00<\/td>\nBreak<\/td>\nEND<\/td>\n<\/tr>\n\n
    16:00-17:30<\/td>\nStudent Presentations (Session 1<\/a>)<\/td>\nStudent Presentations
    (Session 2<\/a>)<\/td>\n    		Student Presentations (Session 4<\/a>)<\/td>\n<\/tr>\n
    19:00-21:30<\/td>\n<\/td>\nSocial Dinner at l’Atelier 67<\/a><\/td>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n\n\n\n


    <\/p>\n\n\n\n

    Session 1 (Tuesday 8 Sep): Efficient Edge Inference<\/strong><\/summary>\n

    L\u00e9o Bernard \u2014 Threshold-based Routing for Energy-efficient Experts
    Kyrylo Tymchenko \u2014 Confidence-Shaped Regression Cascades for Efficient Edge Inference<\/p>\n<\/details>\n\n\n\n

    Session 2 (Wednesday 9 Sep): Resource Allocation and Efficient Training<\/strong><\/summary>\n

    Isidoor Pinillo Esquivel \u2014 Quantized Online Gradient Descent for Constant-Time Caching with Dynamic Regret Guarantees
    Mariya Peter \u2014 Fairness-Aware Optimal Transport Framework for Flow Allocation in Interconnected Network Systems
    Nicolas Helson \u2014 Network-Adaptive Gradient Compression for Faster ML Model Training in Datacenters<\/p>\n<\/details>\n\n\n\n

    Session 3 (Thursday 10 Sep): Federated Learning: Fairness, Robustness, and Unlearning<\/strong><\/summary>\n

    Neeraja Sudhakaran \u2014 Towards Fair Federated Learning: Analyzing the Impact of Data Heterogeneity and Data Repair
    Jingye Wang \u2014 The Praetorian Guard: Unveiling the Vulnerability of Trust-Based Defense in Federated Learning
    Florian Zimmer \u2014 Enabling Decentralised Federated Unlearning in Industrial Cross-Organisational Environments
    Panos Raptis \u2014 Dynamic Fairness in Multi-Task Edge Learning<\/p>\n<\/details>\n\n\n\n

    Session 4 (Thursday 10 Sep): Reinforcement Learning and AI-Driven Network Intelligence<\/strong><\/summary>\n

    Sooraj Skanda \u2014 Model-Based Multi-Agent Reinforcement Learning for Integrated Sensing and Communication
    Andreas Pattichis \u2014 Continual Learning from Streams of Unlabeled Data in LLM Systems
    Michele Simeone \u2014 Exploring KPI Trade-offs in O-RAN Conflict Resolution with Deep Reinforcement Learning
    Luigi Rachiele \u2014 From Fixed Pipelines to Agentic Decisions: An LLM Orchestrator for Anomaly Detection in Mobile Network Drive Tests<\/p>\n<\/details>\n\n\n\n

    Session 5 (Friday 11 Sep): Learning and Control under Resource Constraints<\/strong><\/summary>\n

    Muyun Li \u2014 RL-based Edge Access Control for Time-Sensitive Tasks under Resource Contention
    Oihan Azkarate Iriarte \u2014 Optimal Control and Learning of Tandem Queues with Transfer Costs
    Haoming Lin \u2014 Structure of Optimal Admission Control under Resource Constraints
    Berfin Dinc \u2014 Closed-Loop Control with Delayed Information<\/p>\n<\/details>\n\n\n\n

    <\/p>\n","protected":false},"excerpt":{"rendered":"

    Location: Jacques Morgenstern Amphitheatre, Kahn building, Inria Centre at Universit\u00e9 C\u00f4te d’Azur, 2004 Route des Lucioles, 06410 Biot, France Time Tuesday 8 Sep Wednesday 9 Sep Thursday 10 Sep Friday 11 Sep 08:30-09:00 Registration 09:00-10:30 Opening Keynote: AI in radio access networks: challenges and open problems Speaker: Zwi Altman (Orange\u2026<\/p>\n

    Continue reading<\/span><\/i><\/a> <\/p>\n","protected":false},"author":58,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":"","_members_access_role":[],"_members_access_error":""},"class_list":["post-78","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/project.inria.fr\/finality1stphdschool\/wp-json\/wp\/v2\/pages\/78","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/project.inria.fr\/finality1stphdschool\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/project.inria.fr\/finality1stphdschool\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/finality1stphdschool\/wp-json\/wp\/v2\/users\/58"}],"replies":[{"embeddable":true,"href":"https:\/\/project.inria.fr\/finality1stphdschool\/wp-json\/wp\/v2\/comments?post=78"}],"version-history":[{"count":61,"href":"https:\/\/project.inria.fr\/finality1stphdschool\/wp-json\/wp\/v2\/pages\/78\/revisions"}],"predecessor-version":[{"id":455,"href":"https:\/\/project.inria.fr\/finality1stphdschool\/wp-json\/wp\/v2\/pages\/78\/revisions\/455"}],"wp:attachment":[{"href":"https:\/\/project.inria.fr\/finality1stphdschool\/wp-json\/wp\/v2\/media?parent=78"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}