��ݮ��Ƶ.AI and WIN Joint Workshop on “Artificial Intelligence for Science & Engineering”

Kendra Goertz — Thu, 06 Jan 2022 16:18:37 +0000

��ݮ��Ƶ.AI and WIN Joint Workshop on “Artificial Intelligence for Science & Engineering” Kendra Goertz Thu, 01/06/2022 - 11:18

��ݮ��Ƶ.AI and ��ݮ��Ƶ Institute for Nanotechnology (WIN) are co-hosting an “AI for Science & Engineering Workshop” with over 20 speakers sharing highlights on how they are using AI to generate new insights for potential breakthroughs. The talks will range from new materials discovery at micro and nano-scale, unconventional computing and quantum computers to applications for environment, water, biosensors and biomedical. The event will be three half-days with all the sessions recorded and shared thereafter on ��ݮ��Ƶ.AI and WIN websites.

DATES & TIMES:

Day 1: Tuesday, January 18th | 8:40 AM - 1:00 PM
Day 2: Wednesday, January 19th | 8:55 AM - 12:00 PM
Day 3: Thursday, January 20th | 10:00 AM - 3:00 PM

LOCATION:
Live Event via MS Teams

��ݮ��Ƶ AI & WIN Workshop Brochure - PDF

AGENDA:

Day 1 Agenda: Tuesday 18 January 2022

8:40 – 8:45am: Harold Godwin, Managing Director at ��ݮ��Ƶ.AI: Welcome and Territorial Acknowledgement
8:45 – 8:50am: Bessma Momani, Associate Vice-President for Interdisciplinary Research (Interim)
8:50 – 8:55am: Laurent Servant, Vice-President, International Networks, University of Bordeaux France
8:55 – 9:00am: Mary Wells, Dean of Engineering, University of ��ݮ��Ƶ
9:00 – 9:45am: Keynote Industry Speaker 1 – Jill Becker, Kebotix Inc

Technical Talk Session 1: AI for Security and Public Health Monitoring

9:45 – 10:05am: Jenny Benois-Pineau, University of Bordeaux, “Monitoring of Frail Subjects for Risk Situation Detection with AI Tools”
10:05 – 10:25am: Patricia Nieva or William Mallek, “ML models for distance optimization for infectious disease-tracing (including Covid-19) using Bluetooth enabled devices”
10:25 – 10:45pm: Gayo Diallo, University of Bordeaux, “Data and Knowledge Integration for Digital Public Health”

Technical Talks Session 2: AI for New Materials Discovery

10:45 – 11:05am: Peyton Shi, “AI – a potentially powerful tool for nano-material characterization”
11:05 – 11:25am: Rod Smith, “Empowering Spectroscopic Analysis Using the Interpretive Capabilities of ML”
11:25 – 11:45am: Scott Hopkins, “ML molecular properties from mass spectrometry data”
11:45 – 12:20pm: Break
12:20 – 12:40pm: Stephane Gorsse, University of Bordeaux, “Machine Learning Assisted Design and Development of High-entropy Alloys”
12:40 – 1:00pm: Mario Maglione, University of Bordeaux, “DIADEM Project: Towards AI in Materials Science”

Day 2 Agenda: Wednesday 19 January 2022

8:55 – 9:00am: Opening Remarks and Welcome - Terry B. McMahon, University of ��ݮ��Ƶ
9:00 – 9:45am: Keynote Speaker 2 – Laurent Simon, University of Bordeaux, "AI and the University of Bordeaux: Opportunities and Challenges"

Technical Talks Session 3: AI for Medical Applications and Diagnoses

9:45 – 10:05am: Mohammad Kohandel, “AI for biomedical data”
10:05 – 10:25am: Melanie Campbell, “Using AI to enable the eye as a window on neurodegenerative diseases of the brain”
10:25 – 10:45am: Juewen Liu, “Test tube evolution of DNA aptamers as biosensors”
10:45 – 11:00am: Break

Technical Talks Session 4: AI for Water Quality and Environment

11:00 – 11:20am: Frank Zhu, “PlasticNet – Deep learning for automatic microplastic recognition in water via FT-IR Spectroscopy”
11:20 – 11:40am: Vassili Karanassios, “Applications of Artificial Intelligence (and related topics) in Micro and Nano for Water and Health” (pre-recorded)
11:40am – 12:00pm: Sushanta Mitra, “Predictive capability of water quality monitoring sensors: Need for machine learning”

Day 3 Agenda: Thursday 20 January 2022

10:00 – 10:05am: Opening Remarks and Welcome - Mark Giesbrecht, Dean of Mathematics, University of ��ݮ��Ƶ
10:05 – 10:45am: Keynote Speaker 3 – Wilfred van der Wiel, NanoElectronics Group, Director BRAINS Centre for Brain-Inspired Nano Systems |

Technical Talks Session 5: AI for Improved Manufacturing and Industry Applications

10:45 – 11:05am: Kaan Erkorkmaz, “Boosting Manufacturing through Virtualization and Intelligence”
11:05 – 11:25am: Michel Fich, “ML tools for predicting maintenance requirements on a distant remote-controlled facility”
11:25 – 11:45am: Qinqin Zhu, “Dynamic Latent Variable Analytics for Inferential Sensor Modeling and Supervised Monitoring”
11:45am – 12:05pm: Laurent Simon, University of Bordeaux, “AI for Critical Systems: Progresses and Limits”
12:05 – 1:00pm – Break for lunch

Technical Talks Session 6: Foundational AI

1:00 – 1:20pm: Vijay Ganesh, “Logic Guided Machine Learning”
1:20 – 1:40pm: George Shaker, “AI-powered Radar Sensing”
1:40 – 2:00pm: Roger Melko, “Generative models and quantum computers”
2:00 – 2:20pm:– Yimin Wu, “Brain Inspired Computing for Artificial Intelligence”
2:20 – 2:40pm: Sylvain Saïghi, University of Bordeaux, “
2:40 – 3:00pm: Closing remarks and next steps: Sushanta Mitra (WIN) and Vijay Ganesh (��ݮ��Ƶ.Ai)

PRESENTER BIOS:

Opening Remarks Guest Speakers

Bessma Momani, Associate Vice-President for Interdisciplinary Research (Interim)

Profile: /political-science/people-profiles/bessma-momani

Laurent Servant, Vice-President, International Networks, University of Bordeaux France

Profile: https://www.u-bordeaux.fr/Universite/Organisation/Equipe-presidentielle/Les-vice-presidents/Laurent-Servant-vice-president-Reseaux-internationaux

Day 1, 2 and 3 - Keynote Speakers

Keynote Industry Speaker 1: Jill Becker, Kebotix Inc

Bio: Dr. Jill S. Becker is the CEO of Kebotix, a technology platform that is reinventing the materials industry and enables a new age of discovery of new materials using AI, machine learning, and robotics. Dr. Becker received her undergraduate degree from the University of Toronto, followed by Masters and Ph.D. in chemistry from Harvard University. Her Ph.D. thesis research led to the creation of Cambridge NanoTech Inc., which was subsequently acquired by Veeco. Dr. Becker is also involved in strategic consulting, venture capital, and entrepreneurship support at Harvard. She is a past Ernst and Young Entrepreneur of the Year winner in energy & materials and a member of YPO. In her spare time, she loves to travel and to spend time with her friends & family. Like most chemists, Jillis a foodie and deeply appreciates haute gastronomy.

Keynote Speaker 2: Laurent Simon , Professor - University of Bordeaux

Bio: Professor in Computer Science at the engineering school Bordeaux INP and at the LaBRI. His main research interest is around propositional logic and the design of efficient algorithms for solving real world problems represented under this formalism (typically Constraints and SAT). He is also working on the more general frameworks Knowledge Representation and Compilation.

Keynote Speaker 3: Wilfred van der wiel, Director of the BRAINS Center for Brain-Inspired Nano Systems - University of Twente

Bio: Wilfred G. van der Wiel (Gouda, 1975) is full professor of Nanoelectronics and director of the BRAINS Center for Brain-Inspired Nano Systems at the University of Twente, The Netherlands. He holds a second professorship at the Institute of Physics of the Westfälische Wilhelms Universität Münster, Germany. His research focuses on unconventional electronics for efficient information processing. Van der Wiel is a pioneer in Material Learning at the nanoscale, realizing computational functionality and artificial intelligence in designless nanomaterial substrates through principles analogous to Machine Learning. He is author of 125 journal articles receiving over 7,500 citations.

Day 1 - Technical Talk Session 1: AI for Security and Public Health Monitoring

Jenny Benois-Pineau, Assistant Professor - Universite de Bordeaux

Bio: Jenny Benois-Pineau is a professor of Computer Science at the University Bordeaux. Her topics of interest include image/multimedia, artificial intelligence in multimedia and healthcare. She is the author and co-author of more than 230 papers in international journals, conference proceedings, books and book chapters. She has tutored and co-tutored 27 PhD students She is associated editor of SPIC, ACM MTAP, senior associated editor JEI SPIE journals. She has served in numerous program committees in international conferences: ACM MM, ICMR, CIVR, CBMI, IPTA, MMM, and organized WS at the major conference as ACM MM, IEEE ICIP, ICPR … She has been coordinator or leading researcher in EU – funded and French national research projects and projects with French companies. She was invited for lecturing as a distinguished researcher at the Universities of Madrid, (Spain), Klagenfurt (Austria), Ben Gurion (Israel), NJIT (USA), UAM, CITEDI (Mexico) and gave invited lectures at the UNC at Chapel Hill, Carnegie Melon, Brooklynn Polytechnic (USA), University of Sussex (GB) and UCL (Belgium). She is a member of IEEE TC IVMSP. She has Knight of Academic Palms grade.

Patricia Nieva, Professor - University of ��ݮ��Ƶ

Bio: Dr. Patricia Nieva, PhD., P.Eng., is a Professor and Deputy Chair of the Department of Mechanical and Mechatronics Engineering at the University of ��ݮ��Ƶ. She founded and is the Director of the University of ��ݮ��Ƶ Sensors and Integrated Microsystems Laboratory (SIMSLab). She earned her doctorate in Electrical Engineering from Northeastern University (Boston, Massachusetts) in 2004 and is an expert on microsensors, nanosensors and intelligent sensor system solutions for real-time parameter monitoring and has led extensive research in the areas of point-of-care handheld devices and smart automotive sensors. Prof. Nieva is involved in projects such as embedded sensors for in-line performance monitoring of Lithium-Ion battery cells for electric vehicles and highly sensitive, fiber-optic based salivary sensors for hormone panel testing, and handheld cardiac monitors to measure the concentration of proteins in blood commonly linked to heart attack to alert a patient’s doctor before symptoms appear. She is also currently leading the development of intelligent Bluetooth-based wearables that combine advanced sensing technologies with Artificial Intelligence (AI) to enable COVID-19 digital contact tracing and continuous health monitoring.

Gayo Diallo, Associate Professor - Universite de Bordeaux

Bio: Gayo Diallo, HDR and PhD in Computer Sciences, is a member of the Bordeaux Laboratory of Computer Science and the Group Leader of the Computer Sciences Applied to Health research group (ERIAS) of the Bordeaux Population Health research center, INSERM 1219, a team dedicated to the design and development of methods and tools for the semantic integration of healthcare related data, in particular, for facilitating their secondary use in the context of Public Health issues. He joined University of Bordeaux, Bordeaux School of Public Health (ISPED), in 2009 after being a research assistant at City University of London (UK) and PostDoc researcher at the Laboratory of Applied Computer Sciences (LISI/ENSMA) Futuroscope Poitiers (France). He graduated from University of Grenoble Joseph Fourier in 2006 (PhD in Computer Science). His research interests include AI based approach for healthcare data and knowledge management and ICT for Development with a particular focus on the healthcare sector. He participated in various EU funded projects and authored or co-authored more than 50 peers reviewed papers. He is winner of the practical application prize of the 2015 edition of the Orange Data for Development Big Data Challenge (D4D) and the SAMPO France-Finland cooperation program in 2015 as well.

Day 1 - Technical Talks Session 2: AI for New Materials Discovery

Peyton Shi, PhD candidate - University of ��ݮ��Ƶ

Bio: Peyton (Yinqiu) Shi obtained her BSc degree in Physics from the University of Toronto in 2014. In the summer of 2013, she conducted a research project at Forschungszentrum Jülich in Germany on Au-free InSb nanowires, which gave her much appreciation for nanotechnology. Peyton joined the group first as an M.Sc student in September, 2014. Then in 2015, she transferred directly to the PhD program to continue working on the project which focuses on the epitaxial growth and fabrication of InSb Quantum Well heterostructures for the experimental realization of Majorana bound states (MBS). This project is conducted in collaboration with the Coherent Spintronics Group of the Institute for Quantum Computing (IQC).

Peyton was born and raised in Nanjing, a beautiful historical city in China. During her spare time, she enjoys cooking, doing yoga, jogging, skiing, painting, dancing and playing pipa (a traditional Chinese lute). Peyton is also a huge fan of travelling and adventures.

Rod Smith, Assistant Professor - University of ��ݮ��Ƶ

Bio: Dr. Rodney Smith is an Assistant Professor at the University of ��ݮ��Ƶ. His PhD from Memorial University of Newfoundland was followed by postdoctoral fellowships at the University of Calgary and the University of British Columbia, and an Alexander von Humboldt Research Fellowship at the Freie Universität Berlin. His research interests lie in spectroscopic analysis and in heterogeneous electrocatalysis. He has a special interest in identifying how structural imperfections affect electrochemical behavior and alter reaction mechanisms. His research team approaches the problem by correlating structural descriptors for series solid state materials to their electrochemical behavior.

Scott Hopkins, Associate Professor - University of ��ݮ��Ƶ

Bio: Scott Hopkins is an Associate Professor of chemistry at the University of ��ݮ��Ƶ. He completed his PhD in high-resolution spectroscopy in 2006 at the University of New Brunswick, then undertook postdoctoral studies in photodissociation dynamics and gas phase cluster science at Queen’s University, the University of Cambridge, and the University of Oxford where he held the Ramsay Memorial Fellowship. Scott joined the University of ��ݮ��Ƶ in 2011 where he established a research program that focuses on determining the structures and properties of gas phase clusters. To date, he has published >80 peer-reviewed articles and has authored three patents.

Stéphane Gorsse, Professor - Universite de Bordeaux

Bio: Stéphane Gorsse is professor of materials science at the Institute of Condensed Matter Chemistry of Bordeaux which is a joint research unit of the French National Center for Scientific Research (CNRS), the University of Bordeaux and Bordeaux Institute of Technology.

His topics of interest include physical metallurgy, phase transformation, computational thermodynamic and alloy design. He is the author and co-author of more than 100 papers in international peer reviewed journals. He has been coordinator or leading researcher in EU – funded and French national research projects and projects with companies. He gave about 50 invited lectures in international conferences and in overseas universities as invited researcher:

- Belgium: Univ. Catholique de Louvain, and Univ. Libre de Bruxelles,

- USA: Harvard Univ., Caltech, Air Force Research Lab., Univ. North Texas,

- India: Indian Institute of Science (IISs, Bangalore),

- Japan: National Institute of Materials Science (NIMS),

- Taiwan: National Tsing Hua Univ. (Hsinchu).

He has received the 2018 Constellium Prize from the French Academy of Sciences for his contribution to metallurgy.

Mario Maglione, ICMCB, CNRS - Universite de Bordeaux

Bio: Mario Maglione received the Ph.D. degree from the Federal Polytechnical School of Lausanne (EPFL), Lausanne, Switzerland (1987).

Following three years with IBM Zürich Laboratories, Switerland and post-doctoral positions with Mainz University, Germany, and IBM Zürich, he joined in 1988, as a Junior CNRS Scientist, the Physics Laboratory, University of Burgundy, Dijon, France. In 2000, he joined the CNRS Institute for Condensed Matter Chemistry, University of Bordeaux, Pessac, France. He has been a Director of this Institute from 2012 up to 2021. He is now a co-leader of the nationwide project DIADEM dedicated to Artificial Intelligence for Accelerated Materials Discovery. He has coauthored more than 250 papers and has been invited to 55 international conferences. His research interests are mostly concerned with the investigation of ferroelectric materials of any shape from single crystals to ceramics, nanocomposites and thin films.

Day 2 - Technical Talks Session 3: AI for Medical Applications and Diagnoses

Mohammad Kohandel, Associate Professor - University of ��ݮ��Ƶ

Bio: Mohammad Kohandel is an Associate Professor at the Department of Applied Mathematics of the University of ��ݮ��Ƶ. His Lab is currently focused on integrating experimental studies and quantitative approaches to address several problems in biomedical sciences, particularly in cancer biology. His research activities include applying existing and novel quantitative models and computational methods to study combinations of cancer therapies, nano-scale drug delivery systems, drug resistance in cancer, and quantum sensors.

Melanie Campbell, Professor - University of ��ݮ��Ƶ

Bio: Melanie Campbell is a professor in the Department of Physics and is cross-appointed to the School of Optometry, and to the Department of System Design Engineering. Melanie carries out research on optical properties of the eye, optical systems and eye-imaging systems for treatment and diagnosis. Some applications of her research include two-photon therapy, Alzheimer's diagnosis and diabetic retinopathy.

Juewen Liu, Professor - University of ��ݮ��Ƶ

Bio: Dr. Juewen Liu is a professor of chemistry at the University of ��ݮ��Ƶ and a University Research Chair. He is interested in developing DNA and aptamer-based biosensors for detecting heavy metal ions, small molecules and proteins. He received a Fred Beamish Award (2014) and a McBryde Medal (2018) from the Canadian Society for Chemistry for his contribution in bioanalytical chemistry. He is a College member of the Royal Society of Canada. He serves as a Section Editor for Biosensors & Bioelectronics, a Contributing Editor for TrAC, and is on the editorial advisory board of Langmuir. He has published over 300 papers, receiving over 30,000 citations with an H-index of 84.

Day 2 - Technical Talks Session 4: AI for Water Quality and Environment

Frank Zhu, Ph.D - University of ��ݮ��Ƶ

Bio: My name is Frank Zhu. I am Ph.D. student from the department of civil and environmental engineering. My Ph.D. project focuses on the fate and transport of microplastics(MPs) in wastewater treatment plants. I aim to develop novel analytical methods leveraging deep learning and image analysis for the rapid and accurate detection of microplastics in wastewater samples. I specially focus on the use of deep learning for the recognition of spectra of MPs in environmental samples that vary significantly from the spectra of pure polymers.

Vassili Karanassios, Professor - University of ��ݮ��Ƶ

Bio: Vassili Karanassios is a Professor of Chemistry at the University of ��ݮ��Ƶ (Ontario, Canada) and a co-founder of a degree-program in nano-technology engineering at the same University. Professor Karanassios received his Ph.D. from the University of Alberta (Edmonton, Canada) and was a Post Doctoral Fellow at McGill University (Montreal, Canada). In 2009, he held a Leverhulme award in the UK where he was a visiting Professor in Chemistry (Sheffield University), an Overseas Fellow of Churchill college (Cambridge University, UK), and a visiting Professor of Engineering (Cambridge University, UK) in the Center for Advanced Photonics and Electronics (CAPE).

Professor Karanassios and his group published (among others) on microfluidics and nanofluidics, on 3D printing and on rapid prototyping, on battery-operated microplasmas, on spectral interference correction using Artificial Neural Networks (ANNs) and Deep Learning, and on smartphone-enabled data acquisition and signal-processing from a variety of sensors for on-site chemical analysis and (potentially) for IoT applications.

Sushanta Mitra, Professor - University of ��ݮ��Ƶ

Bio: Sushanta Mitra is a Professor in the Department of Mechanical & Mechatronics Engineering. He serves as the Executive Director of Canada’s largest nanotechnology institute – the ��ݮ��Ƶ Institute for Nanotechnology (WIN). For his contributions in science and engineering, he is elected fellow of several professional organizations, including the Canadian Academy of Engineering, the Royal Society of Chemistry, the American Physical Society, the American Association for the Advancement of Science and a foreign fellow of both the Indian National Academy of Engineering and the National Academy of Sciences India. He has an entrepreneurial mind, being the Founder & CEO of a Canadian startup, Aquabits Inc. (on quantum computing) and a Dutch startup, SLE Enterprises B.V. (on ultra-fast encapsulation technology), supported by the University of ��ݮ��Ƶ. His passion for working with communities in India in the water sector continues through Indian startup Earthface Analytics, for which he is a co-founder along with colleagues from IIT Kanpur and MIT USA.

Day 3 - Technical Talks Session 5: AI for Improved Manufacturing and Industry Applications

Kaan Erkorkmaz, Professor - University of ��ݮ��Ƶ

Bio: Kaan Erkorkmaz is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of ��ݮ��Ƶ. He is a Fellow of the International Academy for Production Engineering (CIRP) and also a Registered Professional Engineer in the Province of Ontario. Professor Erkorkmaz’s research interests are in the areas of precision manufacturing, machining, and dynamics; controls, and optimal trajectory planning for machine tools; with the objective of increasing the productivity, part quality, and resource efficiency in manufacturing operations.

Michel Fich, Professor - University of ��ݮ��Ƶ

Bio: A faculty member at U��ݮ��Ƶ since 1986, Professor Fich began building telescopes in high school. His PhD thesis work at UCalifornia (Berkeley) required the design and fabrication of a radio telescope receiver system. Since then he has been involved in numerous other astronomical instrument and telescope projects and has had a leadership role in several in the past two decades. His research publications include the first measurements of the dark matter content of our Milky Way galaxy, observations that constrain the structural evolution of galaxies, and several aspects of star formation. http://astro.uwaterloo.ca/~fich/

Qinqin Zhu, Assistant Professor - University of ��ݮ��Ƶ

Bio: Prof. Qinqin Zhu is an assistant professor in the department of Chemical Engineering at the University of ��ݮ��Ƶ. She is also a faculty member in the ��ݮ��Ƶ Artificial Intelligence Institute (��ݮ��Ƶ.AI), ��ݮ��Ƶ Institute for Nanotechnology (WIN), and ��ݮ��Ƶ Institute for Sustainable Energy (WISE). Prof. Zhu received her PhD degree from the Chemical Engineering department at the University of Southern California. Prior to UW, she worked as a senior research scientist at Facebook Inc. in the United States. Prof. Zhu's research mainly focuses on developing advanced statistical machine learning methods, process data analytics techniques and optimization algorithms in the era of big data with applications to statistical process monitoring and fault diagnosis. Her research addresses theoretical challenges and problems of practical importance in the area of process systems engineering. By leveraging the power of mathematical modeling and optimization, her group strives to develop advanced multivariate statistical analysis algorithms that enhance decision making in complex engineering systems.

Laurent Simon , Professor - University of Bordeaux

Day 3 - Technical Talks Session 6: Foundational AI

Vijay Ganesh, Co-Director - ��ݮ��Ƶ.AI

Bio: Dr. Vijay Ganesh is an associate professor at the University of ��ݮ��Ƶ and the Co-Director of the ��ݮ��Ƶ Artificial Intelligence Institute. Prior to joining ��ݮ��Ƶ in 2012, he was a research scientist at MIT (2007-2012) and completed his PhD in computer science from Stanford in 2007. Vijay's primary area of research is the theory and practice of SAT/SMT solvers aimed at AI, software engineering, security, mathematics, and physics. In this context he has led the development of many SAT/SMT solvers, most notably, STP, Z3 string, MapleSAT, and MathCheck. He has also proved several decidability and complexity results in the context of first-order theories. He has won over 25 awards, honors, and medals to-date for his research, including an ACM Impact Paper Award at ISSTA 2019, ACM Test of Time Award at CCS 2016, and a Ten-Year Most Influential Paper citation at DATE 2008. He is the Editor-in-Chief of the Springer book series "Progress in Computer Science and Applied Logic" (PCSAL) and has co-chaired many conferences, workshops, and seminars including a Simons Institute semester @ Berkeley on Boolean Satisfiability in 2021.

George Shaker , Adjunct Associate Professor - University of ��ݮ��Ƶ

Bio: Prof. George Shaker is the lab director of the Wireless Sensors and Devices Laboratory at the University of ��ݮ��Ƶ where he is an (Adjunct + Research) associate professor at the Department of Electrical and Computer Engineering as well as the Department of Mechanical and Mechatronics Engineering. George is also with the University of ��ݮ��Ƶ Schlegel Research Institute for Aging as a Research Scientist. Previously, he was an NSERC scholar at Georgia Institute of Technology. He also held multiple roles with RIM's (BlackBerry). He has co-authored over 100 peer-reviewed publications, 30 patents, and has received over 40 international research awards.

Roger Melko, Professor - University of ��ݮ��Ƶ

Bio: Roger Melko is a professor at the University of ��ݮ��Ƶ, associate faculty at the Perimeter Institute for Theoretical Physics, and the Canada Research Chair in Computational Quantum Many-Body Physics. He received his PhD from the University of California, Santa Barbara in 2005. His research involves the development of computer strategies for the theoretical study of quantum materials, atomic matter, and quantum information systems. He was the recipient of the 2012 IUPAP Young Scientist Prize in Computational Physics, the 2016 Canadian Association of Physicists (CAP) Herzberg Medal, and the 2021 CAP Brockhouse Medal.

Yimin Wu, Assistant Professor - University of ��ݮ��Ƶ

Bio: Dr. Yimin Wu is an assistant Professor in the Department of Mechanical and Mechatronics Engineering and ��ݮ��Ƶ Institute of Nanotechnology (WIN), Director of Materials Interfaces Foundry, at the University of ��ݮ��Ƶ. Dr. Wu received his DPhil degree in Materials from the University of Oxford on 2D electronics in 2013. Then, he worked as a SinBeRise Postdoctoral Fellow at the University of California, Berkeley, and Lawrence Berkeley National Laboratory. Prior to joining the faculty at ��ݮ��Ƶ in 2019, he was focusing on the advanced catalysts and battery research in the Center for Nanoscale Materials and Joint Center for Energy Storage Research (JCESR), Argonne National Laboratory and worked as a research assistant professor at University of Illinois, USA. He has authored and co-authored more than 50 peer-reviewed journal papers, which includes Nature, Nature Energy, Nature communications. He is also listed as a primary inventor on 1 US/international patent. His research has been highlighted by Canadian Press, CBC news, the Independent, BNN Bloomberg, Fast Company, and French Science Magazine. He has been awarded more than 10 awards including Nanoscale Emerging Investigator (2022), WIN research leaders award (2020), MIT Technical Review Innovators Under 35 Award Finalist (2020), SinBeRise Postdoctoral Fellowship at the University of California, Berkeley (2013), UK EPRSC Doctoral Prize (2012).Wu has delivered over 25 invited lectures across the world in last 5 years. His research group has received funding from federal and provincial government agencies (Natural Science and Engineering Research Council of Canada, Canadian Foundation for Innovation, National Research Council Canada, Ontario Center of Excellence, and MITACS). /materials-interface-foundry/

Sylvain Saïghi, Professor - University of Bordeaux

Bio: Sylvain Saïghi is Professor at University of Bordeaux and head of the research group “Architecture of Silicon Neural Networks”. He defended his PhD in 2004 on the design of analogue operators dedicated to silicon neurons. He has performed pioneering work in developing biologically realistic and tunable silicon neurons. He has also authored and co-authored more than 60 peer-review publications (Google scholar: 2107 citations, h-index: 20). Thanks to a Fulbright Scholar grant, he was Visiting Associate-Professor at Johns Hopkins University, Baltimore (MD), for 6 months in 2011. He was involved in the EU FACETS project and was the scientific leader for IMS Laboratory in the EU FACETS-ITN project.

Moreover, he was the coordinator of the MHANN ANR French project that aimed to build a prototype of a bio-inspired architecture, using ferroelectric memristors. Currently, he is the coordinator of the H2020 EU project ULPEC that aims at developing an ultra-low power event-based camera composed of CMOS pixels, CMOS neurons and memristive devices on the same chip. He is also currently an active partner in the NEUROTECH EU project, which intends to support the development of the European community in neuromorphic computing technologies. He recently obtained one of the chair for research on Artificial Intelligence granted by the French National Agency for research (ANR) in the frame of the French action plan for IA.