New Lecturer: Yukie Nagai, The University of Tokyo, Japan

Dr. Yukie Nagai has been investigating underlying neural mechanisms for social cognitive development by means of computational approaches. She designs neural network models for robots to learn to acquire cognitive functions such as self-other cognition, estimation of others’ intention and emotion, altruism, and so on based on the theory of predictive coding. The simulator reproducing atypical perception in autism spectrum disorder (ASD), which has been developed by her group, greatly impacts the society as it enables people with and without ASD to better understand potential causes for social difficulties. She was elected to “30 women in robotics you need to know about” in 2019 and “World’s 50 Most Renowned Women in Robotics” in 2020. She serves as the principal investigator of JST CREST “Cognitive Mirroring” and CREST “Cognitive Feeling” since December 2016 and October 2021, respectively.
She is also a member of International Research Center for Neurointelligence at the University of Tokyo since 2019, and a member of Next Generation Artificial Intelligence Research Center and Forefront Physics and Mathematics Program to Drive Transformation at the University of Tokyo since 2020.

New Lecturer: Edith Elkind, University of Oxford

Edith Elkind is a Professor of Computer Science at University of Oxford. She obtained her PhD from Princeton in 2005, and has worked in the UK, Israel, and Singapore before joining Oxford in 2013. She works in algorithmic game theory, with a focus on algorithms for collective decision making and coalition formation. Edith has published over 100 papers in leading AI conferences and journals, and has served as a program chair of WINE, AAMAS, ACM EC and COMSOC; she will serve as a program chair of IJCAI in 2023.

https://www.cs.ox.ac.uk/people/edith.elkind/

 

New Lecturer: Alex Davies, DeepMind, London, UK

Alex Davies is the founding lead of the AI for Maths initiative at DeepMind, the team which recently published their work on using AI in maths in Nature. Prior to DeepMind, Alex Davies worked at Google on Machine Intelligence and also as a guest lecturer at the University of Oxford. He obtained his Ph.D. from the University of Cambridge, supervised by Zoubin Ghahramani.

http://www.alexdavies.net

https://www.linkedin.com/in/alex-davies-13a53521/

https://www.linkedin.com/posts/alex-davies-13a53521_this-week-we-announced-our-work-collaborating-activity-6872872186252713984-JsFJ

 

New Lecturer: Silvio Savarese, Salesforce & Stanford University, USA

Silvio Savarese is Executive Vice President and Chief Scientist of Salesforce Research as well as an Adjunct Faculty of Computer Science at Stanford University. He earned his Ph.D. in Electrical Engineering from the California Institute of Technology in 2005 and was a Beckman Institute Fellow at the University of Illinois at Urbana-Champaign from 2005–2008. He joined Stanford in 2013 after being Assistant and then Associate Professor (with tenure) of Electrical and Computer Engineering at the University of Michigan, Ann Arbor, from 2008 to 2013. His research interests include computer vision, object recognition and scene understanding, shape representation and reconstruction, human activity recognition and visual psychophysics. He is recipient of several awards including a Best Student Paper Award at CVPR 2016, the James R. Croes Medal in 2013, a TRW Automotive Endowed Research Award in 2012, an NSF Career Award in 2011 and Google Research Award in 2010. In 2002 he was awarded the Walker von Brimer Award for outstanding research initiative.

New Lecturer: Mihaela van der Schaar, University of Cambridge, UK

Professor van der Schaar is John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge and a Turing Fellow at The Alan Turing Institute in London, where she leads the effort on data science and machine learning for personalised medicine. She is an IEEE Fellow (2009). She has received the Oon Prize on Preventative Medicine from the University of Cambridge (2018).  She has also been the recipient of an NSF Career Award, 3 IBM Faculty Awards, the IBM Exploratory Stream Analytics Innovation Award, the Philips Make a Difference Award and several best paper awards, including the IEEE Darlington Award. She holds 35 granted USA patents.

The current emphasis of her research is on machine learning with applications to medicine, finance and education. She has also worked on data science, network science, game theory, signal processing, communications, and multimedia.

https://www.vanderschaar-lab.com/publications/

14 papers @ NeurIPS ’21

4 papers @ ICML ’21

4 papers @ AISTATS ’21

5 papers @ ICLR ’21

9 papers @ NeurIPS ’20.

7 papers accepted at ICLM ’20.

2 papers @ ICLR ’20.

4 papers @ AISTATS ’20.

5 papers accepted at NeurIPS ’19.

ACDL 2022 (as ACDL 2021 and ACDL 2020): an Online & Onsite Course

The organizing committee of ACDL 2022 has decided to run the course on the originally scheduled dates (August 22-26, 2022), and to run it as a hybrid course:

  • onsite (in person) for those who can come to Tuscany, Italy and
  • online for those who cannot.

The Certosa di Pontignano (our conference venue) has enough space to obey the safety rules (put in place due to COVID-19). To accommodate a large number of participants, we are offering the option for either physical presence (onsite) or virtual participation (online). We would be delighted if all authors and participants manage to attend; however, we are aware that in the current special circumstances, it is best to hold the event in hybrid mode.

The Conference, will be held in person with virtual rooms  for participants using a remote connection (Zoom). The lectures  (e.g., live presentations or recorded ones) will also be made available online. We will make sure that the sessions also run live, such that the presenters can show and explain their results, and the attendees can ask questions and interact with the presenters. The sessions will be held one at a time which will allow participants from overseas to attend as many sessions as possible.

The keynote lectures (of the Lecturers who will give their consent to the recording of the lessons) will be recorded such that online participants can follow them either live or at any time they like to.

If the situation does not allow the event to take place in person, the event will instead be converted to a fully online mode.

Obviously, if ACDL 2022 will be converted into a fully online event, participants who paid the onsite registration fee will be refunded the difference, and will thus only pay the online registration fee.

Moreover, it is important to note that it is possible to change the mode of participation (the Registration):

from Onsite Registration → to Online Registration and similarly

from Online Registration → to Onsite Registration

We are offering the possibility to change the mode of participation to ACDL 2022. Those who register in one mode can easily change it by 22 July (one month before the course starts).

  • It is possible to take Onsite Registration and then change it to Online Registration and get a corresponding refund, but this decision must be made by 22 July.
  • Similarly, you can do Online Registration and then upgrade to Onsite Registration and pay the difference (via PayPal); this decision must also be made by 22 July.

If you have any questions please write to the organising committee: acdl@icas.cc

See you (in-person or virtually – in 3D or in 2D 🙂 ) in Siena – Tuscany  in August!

The ACDL 2022 Organizing Committee.