10:00 - 17:00
Workshops, training and support
Turing AIUK Fringe Event
Institute for Analytics and Data Science (IADS)
JunKyu Lee j.lee@essex.ac.uk
In the proliferation of AI applications, the tandem challenges of energy consumption and security in machine learning have become urgent. To address these challenges and mould the future of trustworthy and energy-efficient machine learning research, this workshop seeks to establish a global network dedicated to fostering dialogue and collaboration.
The workshop will adopt a hybrid format that takes place at the University of Essex and online via Zoom. It will feature presentations from esteemed guest speakers at the forefront of international research in the field, followed by panel discussions. These speakers, including academics from universities in the UK, Europe and Asia and representatives from industries and public sectors, will shed light on the latest advancements within trustworthy and energy-efficient machine learning.
Registration and coffee
Welcome Address - Haris Mouratidis (IADS Director, University of Essex)
Energy-Efficient Computing for ML on GPUs - Cheol-Ho Hong (Assoc. Prof. at Chung-Ang Univ. Korea)
Security-aware machine learning - Insaf Ullah (IADS Fellow, University of Essex)
Security-aware machine learning - Chandrajit Pal (Senior Research Officer, CSEE, University of Essex)
Lunch Break (Sandwiches)
Keynote - Robust Deep Learning for Real-World Data and Data-Centric AI - Xinshao Wang (Principal Machine Learning Engineer, Terminal Industries, UK)”
Energy-Efficient Computing Techniques - JunKyu Lee (IADS Fellow, University of Essex)
Energy-Efficient Arithmetic Units for ML - Ioannis Tsiokanos (Visiting Scholar at Queen's University Belfast, UK and Senior Applied Fellow at CERN, Switzerland)
Energy-Efficient Computing for ML on FPGAs - Xiaojun Zhai (Reader, CSEE, University of Essex)
Energy-Efficient Communications - Lev Mukhanov (Lecturer, Queen's Mary University London)
Roundtable Discussion: Current Research Challenges and Future Directions
Closing event