Schedule - GMT+1 TIME ZONE (EU/London)

TO ATTEND THE VIRTUAL WORKSHOP PLEASE GO TO [link]

FRIDAY 23rd JULY


FIRST SESSION

10:00 AM GMT+1 -- Introduction and opening remarks. Workshop organizers.

10:10 AM GMT+1 -- Invited talk: ENGINEER BAINOMUGISHA "Deploying end-to-end machine learning systems for social impact"

10:50 AM GMT+1 -- Invited talk JOHN ARMOUR "Machine Learning and Legal Decisions"

11:30 AM GMT+1 -- Panel discussion: Applications in the legal system

  • Chair: JOHN ARMOUR, University of Oxford

  • Jessica Montgomery, University of Cambridge. "ML for policy: deploying machine learning to tackle public policy challenges "

  • Teresa Scantamburlo, European Centre for Living Technology. "The laborious exercise of human oversight in workforce surveillance "

  • Charles Brecque, Legislate.tech. "Can machine learning ever take the lawyer out of the loop completely? Can machine learning make the legal system fairer, make contracts less confusing and give legal advice?"

12:30 PM GMT+1 - 12:40 PM UTC-- BREAK

12:40 PM GMT+1 -- Invited talk ROBERTO BONDESAN "Machine Learning for Chip Design"

01.30 PM GMT+1 -- Invited talk RICHARD SUSSKIND "The role of AI in online court service"

02.15 PM GMT+1 - 2.30 PM GMT+1 -- BREAK


SECOND SESSION

02:30 PM GMT+1 - 03:30 PM GMT+1 -- Contributed talks

      • "Who is Responsible for Adversarial Defense?". Kishor Datta Gupta ( University of Memphis ), Dipankar Dasgupta ( University of Memphis )

      • "Towards Efficient Machine Unlearning via Incremental View Maintenance". Sebastian Schelter ( University of Amsterdam )

      • "Data Quality Assertions for Machine Learning Pipeline". Till Doehmen ( Fraunhofer FIT ), Mark Raasveldt ( CWI ), Hannes Mühleisen ( Centrum Wiskunde & Informatica ), Sebastian Schelter ( University of Amsterdam )

      • "MLDemon: Deployment Monitoring for Machine Learning Systems". Tony Ginart ( Stanford University ), Martin Zhang ( Harvard School of Public Health ), James Zou ( Stanford University )

      • "Have the Cake and Eat It Too? Higher Accuracy and Less Expense when Using Multi-label ML APIs Online". Lingjiao Chen ( Stanford University ), James Zou ( Stanford University ), Matei Zaharia ( Stanford and Databricks )

      • "Competition over data: when does data purchase benefit users? ". Yongchan Kwon ( Stanford University ), Tony Ginart ( Stanford University ), James Zou ( Stanford University )

03:30 PM GMT+1 -- Virtual Poster session

4:00 PM GMT+1 -- Panel Discussion: Deployment and monitoring on constrained hardware and devices

              • Chair: STEPHEN ROBERTS, University of Oxford

              • Partha Maji, ARM. "How can we extract true model uncertainty with little to no additional computational costs?", "Are popular Bayesian techniques equally expressible after they have gone through several stages of model compression?"

              • Cecilia Mascolo, University of Cambridge. "On-device Uncertainty Estimation"

              • Ivan Kiskin, University of Oxford. "Data Drift", "Updating ML lifecycle"

              • Yunpeng Li, University of Surrey. "Server-side vs client-side implementation"

              • Maria Nyamukuru, Dartmouth College. "Pathways to unified embedded machine learning algorithms"


05:00 PM GMT+1 - 05:10 PM GMT+1 -- BREAK


5:10 PM GMT+1 -- Invited talk SHALMALI JOSHI "Ethics of developing ML in healthcare"

5:50 PM GMT+1 -- Invited talk: NEERAJA J. YADWADKAR "Model-less Inference Serving for ease-to-use and cost-efficiency"

6:30 PM GMT+1 -- Panel discussion: Invited speakers

              • Chair: STEPHEN ROBERTS, University of Oxford

7:30 PM GMT+1 -- Final remarks. Workshop organizers.

7:40 PM GMT+1 -- End of the day