Schedule

The schedule is as follows. All times are in Tunis time (GMT+1).

8h30 - 10h30

• Welcome [20 mins] Organizers [Kale-ab Tessera, Wiebke Toussaint, Sara Hooker]
• Spotlight talks [4 x 8 min talks]
• Keynote [45 mins] Efficient machine translation at the edge by Kenneth Heafield.

Kenneth Heafield is an Associate Professor at the University of Edinburgh working on fast and often good machine translation. He launched local machine translation for Firefox https://browser.mt/ and ran ParaCrawl that mined the web for translations. Previously, he wrote KenLM to train large language models before they were cool.

• Demo introduction [15 mins – extends into break 10:30- 14:00] Edge Impulse / Clinton Oduor

14h00 - 16h00

• Invited Keynote talk [40 mins] Jonathan Richard Schwarz

Jonathan is a Senior Research Scientist at DeepMind and a PhD Candidate at University College London. He is advised by Yee Whye Teh and Peter Latham and work on problems at the intersection of Probabilistic Modelling, Sparsity and Meta & Continual learning.

• Invited Keynote Talk [40 mins] Akhil Mathur

I work as a Principal Research Scientist and Tech Lead for Machine Learning at Nokia Bell Labs in Cambridge. I am also a Visiting Industry Fellow at the University of Cambridge and serve on the Editorial Board of ACM IMWUT journal as an Associate Editor. From 2019-2021, I was a member of the ACM Future of Computing Academy. My research interests are broadly in machine learning and mobile systems. Currently, I am working on projects involving Federated Learning, Self-Supervised Learning, On-Device ML, and Algorithmic Fairness — all in the context of mobile and embedded devices. In addition, I am also interested in exploring the design of novel ML-driven sensory systems and applications. Previously, I have done research in the areas of Ubiquitous Computing, Human-Computer Interaction, and ICT4D. I am a recipient of the Wolfond Fellowship at the University of Toronto, the mBillionth Award South Asia, and two Best Paper Honorable Mention Awards. My research has been covered by several media organizations including the New Yorker, Financial Times, Livemint and Canadian Broadcasting Corporation. I hold a Ph.D. in Machine Learning from the University College London where I worked under the supervision of Dr. Nic Lane and Prof. Nadia Berthouze. I also hold a Masters in Computer Science from the University of Toronto and a B.Tech. from DA-IICT where I was awarded the President’s Gold Medal.

• Demo introduction [10 mins – extends into break 16:00 - 16:30] Victor Dibia

16:30 -17:30

• Panel [60 mins]
• Closing remarks [5 mins]