Invited speakers
Prof. Johan Åkerman received his Ph.D. in Materials Physics from KTH Royal Institute of Technology in 1998. After a post-doc at the University of California, San Diego, he joined Motorola for four years to work on MRAM. In 2005, he returned to KTH in Sweden, and in 2008, he was recruited as Full Professor to the Physics Department at the University of Gothenburg. Since 2023, he is also a part-time Professor at Tohoku University, Sendai, Japan. He has worked on spintronic technology for the last 25 years, has authored over 350 scientific papers with more than 18,000 citations, and has founded three companies. His main projects are related to spin torque and spin Hall nano-oscillators, with particular focus on mutually synchronized oscillator networks for Ising machines and neuromorphic computing.
Laura Bégon-Lours leads the “Neuromorphic Electronics with Oxide (NEO)” group at ETH Zurich, in the Department of Information Technology and Electrical Engineering. Her research focuses on the development and application of nanoscale components that can be used as synapses in artificial neural networks. Her goal is to manufacture bio-inspired chips that work in a similar way to the human brain. In 2019 Laura Bégon-Lours won a Marie Curie Fellowship for her innovative work, and in 2023 she has also been the recipient of an SNSF Starting Grant.
Maxence is a researcher at Google DeepMind where he helps automating chip design using AI. Prior to this, he worked at Rain AI where he developed learning algorithms amenable to analog hardware and assisted engineering efforts on Rain’s first tape-out. Before, he worked at IBM Research on AI safety and interpretability and did his PhD under the supervision of Julie Grollier and Damien Querlioz in close collaboration with Yoshua Bengio. Maxence received his engineering degree from Ecole Polytechnique and studied theoretical physics at the university of Cambridge.
Advait Madhavan is an Electronics Engineer and UMD Assistant Research Scientist in the Alternative Computing Group in the Nanoscale Device Characterization Division of the Physical Measurement Laboratory at the National Institute of Standards and Technology, Gaithersburg, USA. He received a Ph.D. in Electrical and Computer Engineering from the University of California, Santa Barbara, and is a member of the IEEE and ACM organizations. His doctoral research introduced race logic, a delay-encoded hardware approach for dynamic-programming algorithms. His interests lie in various brain-inspired approaches to computation, such as temporal, analog, and stochastic codes. His expertise lies in analog and digital VLSI design and computer architecture, with the objective of building chips to interface with emerging technologies in order to realize these unconventional computing paradigms. He mentors graduate students at the University of Maryland through a NIST-UMD partnership.
Melika Payvand is an Assistant Professor at the Institute of Neuroinformatics, University of Zurich and ETH Zurich and leads the Emerging Intelligent Substrates
lab. She received her PhD in Electrical and Computer Engineering at the University of California Santa Barbara. Her research interest is in developing intelligent learning systems on physical substrates, inspired by the hierarchical structure-function correlate in the biological brain. She is the recipient of the 2023 prestigious Swiss National Science Foundation Starting Grant.
She has co-coordinated the European project NEUROTECH (neurotechai.eu), served as the co-chair of the International Conference on Neuromorphic Systems (ICONS) (https://iconsneuromorphic.cc) and has co-
organized the scientific program of the Capocaccia Neuromorphic Intelligence workshop (https://capocaccia.cc) from 2019-2023. She is the chair elect of the Neural Systems and Application Technical Committee of the IEEE Circuits and Systems Society and is in the technical program committee of the European Solid State Circuits.
Damien Querlioz is a CNRS Research Director at the Centre de Nanosciences et de Nanotechnologies of Université Paris-Saclay and CNRS. His research focuses on novel usages of emerging non-volatile memory and other nanodevices, in particular relying on inspirations from biology and machine learning. He received his predoctoral education at Ecole Normale Supérieure, Paris and his PhD from Université Paris-Sud in 2009. Before his appointment at CNRS, he was a Postdoctoral Scholar at Stanford University and at the Commissariat à l’Energie Atomique. In 2016, he was the recipient of an ERC Starting Grant to develop the concept of natively intelligent memory. In 2017, he received the CNRS Bronze medal. He has also been a co-recipient of the 2017 IEEE Guillemin-Cauer Best Paper Award and of the 2018 IEEE Biomedical Circuits and Systems Best Paper Award.
Dedalo Sanz Hernandez is a senior researcher in the Laboratoire Albert Fert laboratory. He is an expert in nanomagnetism, 3D nanostructure design, and the development of neuromorphic platforms. During his PhD in Cambridge with Amalio Fernandez Pacheco he explored the physics of 3D spintronic systems that he growed and imaged through a home-made MOKE. He then moved to Laboratoire Albert Fert to study neuromorphic computing. His current research work ranges from RF spintronics for energy harvesting, the development of imaging systems for probing the magnetization states of nanostructures to the design of large scale AI hardware.
Helmut Schultheiss finished his PhD in 2010 at the University of Technology Kaiserslautern in Germany. After his PhD he worked for three years at the Argonne National Laboratory in the U.S.A.. In 2014 he received the Emmy Noether fellowship of the German Science Foundation for starting his own research group at the Helmholtz-Center Dresden-Rossendorf in Germany. His research interest are magnons in micro- and nano-structures and their interaction with spin currents and magneto-optics.
Philippe Talatchian is a CEA research scientist at SPINTEC in Grenoble, France, working within the Artificial Intelligence team on the design and experimental implementation of neuromorphic spintronic devices. His research focuses on spintronic components and their integration into functional computing networks for AI. He received his Ph.D. from Université Paris-Saclay, conducted at the Lab. Albert Fert, under the supervision of Julie Grollier, held a postdoctoral position at NIST-Gaithersburg and the University of Maryland, in the group of Mark Stiles.
Daniel Brunner is a CNRS researcher with the FEMTO-ST, France. His interests include novel computing using quantum or nonlinear substrates with a focuses on photonic neural networks. He was received several University and the IOP’s 2010 Roys prize, the IOP Journal Of Physics: Photonics emerging leader 2021 prize as well as the CNRS Bronze medal in 2022. He edited one Book and three special issues, has presented his results 60+ times upon invitation, has published 70+ scientific articles, has been awarded a prestigious ERC Consolidator grant and is a pilot of the French PEPR Electronique project of the France 2030 initiative.
Ole Richter is an Assistant Professor at the Technical University of Denmark in the field of asynchronous Integrated Circuit (IC) design. His research focuses on bringing asynchronus IC Design into practical applications, smart sensors and closed loop robotics. He particularly investigates efficient and low-power bio-inspired neurosynapic AI processor pipelines, pushing the boundary of efficiency with unconventional architectures. He holds a Bachelors degree in Cognitive Computer Science from Bielefeld University (DE), Masters Degree in Neural Systems and Computation from UZH and ETH Zürich (CH) and a PhD the University of Groningen (NL) with the focus on Bio-inspired Circuits and Systems. He has 2 years of industrial experience in an edge-ai processor start-up (aiCTX AG, now Synsense AG, CH) in asynchronous and mixed-signal IC design and is a recurring Research Affiliate/Visiting Fellow at Yale University (US) in the Asynchronous VLSI and Architecture Group.
Prof. Ivan K. Schuller, the director of the Center for Advanced Nanoscience (CAN) at the University of California-San Diego, is a Solid State Physicist. He is winner of major awards such as the Lawrence Award-US Department of Energy, the Vannevar Bush fellowship-US Department of Defense and several awards from the American Physical Society, the Materials Research Society and the International Union of Materials
Research Societies.
Prof. Schuller received his Licenciado en Ciencia from the University of Chile, MS and PhD from Northwestern University and an Honoris Causa Doctorate from the Spanish Universidad Complutense the largest European University. He is a member of the Latin American, Chilean, Spanish, Belgian, and Colombian Academies of Science.
His more than 680 papers and 20 patents have been dedicated to many aspects of solid state and materials physics in Nano and Meso science with possible applications to Neuromorphic Computing and Sensors.
His extensive science related artistic activities have spanned the award-winning production and writing of plays, movies, YouTube videos and acting in a variety of venues. He was elected a fellow of the American Academy of Arts and Sciences.
Ming-Jay Yang is a research scientist and group leader at the Peter Grünberg Institute for Neuromorphic Compute Nodes (PGI-14), Forschungszentrum Jülich, Germany, directed by Prof. John Paul Strachan. He leads the Adaptive In-Memory Computing (AIM) Research Group, which focuses on prototyping neuromorphic hardware that leverages emerging memory technologies to achieve multi-timescale, multi-task adaptability in complex, multimodal applications. His research integrates machine learning, device characterization, and physics-based modeling to enable brain-inspired, energy-efficient computation in emerging in-memory computing hardware. Previously, he served as a senior researcher and consultant in Taiwan’s semiconductor industry, where he investigated cutting-edge, high-speed near-infrared (NIR) imaging sensors based on TSMC technologies for ranging and depth-sensing applications. He received his Ph.D. in EECS from National Tsing Hua University, where he focused on computational electrodynamics and the quantum optics of semiconductors and 2D materials for high-speed optoelectronics and quantum information processing.
Dr. Flaviano Morone is a Senior Researcher at New York University’s Center for Quantum Phenomena and a member of the Sequel Institute. His research applies quantum and probabilistic computing to solve hard optimization problems. He earned his Ph.D. in Theoretical and Mathematical Physics from Sapienza Universit`a di Roma. Dr. Morone is also a Haskell enthusiast.
Catherine (Katie) Schuman is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee (UT). She received her Ph.D. in Computer Science from UT in 2015, where she completed her dissertation on the use of evolutionary algorithms to train spiking neural networks for neuromorphic systems. Katie previously served as a research scientist at Oak Ridge National Laboratory, where her research focused on algorithms and applications of neuromorphic systems. Katie co-leads the TENNLab Neuromorphic Computing Research Group at UT. She has over 100 publications as well as seven patents in the field of neuromorphic computing. She received the Department of Energy Early Career Award in 2019.
Piergiulio Mannocci received his Ph.D. in Information Technology in 2023 from Politecnico di Milano, where he is currently an Associate Researcher in the Department of Electronics, Information and Bioengineering. He has served on the Technical Program Committee of the
Design, Automation and Test in Europe Conference (DATE 2025), and as a Guest Editor for the IEEE Transactions on Circuits and Systems II: Express Briefs. His research focuses on emerging computing paradigms for artificial intelligence and machine learning, with particular emphasis on in-memory computing based on both emerging post-CMOS memory technologies and CMOS memories.
Wilfred G. van der Wiel (Gouda, 1975) is full professor of Nanoelectronics and co-director of the BRAINS Center for Neuromorphic Computing at the University of Twente, The Netherlands. He holds a second professorship at the Institute of Physics of the University of 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 the author of more than 125 journal articles receiving over 14,000 citations.
Weiming Yao is an Assistant professor in the Photonic Integration Group at Eindhoven University of Technology (TU/e). He currently investigates how photonic circuit technology can be used to develop fast and energy-efficient hardware to perform computations, among others for artificial intelligence applications. His background is on high-density, high-speed photonic circuits for communications. From 2017 to 2019, he was affiliated with the Photonic Integration Technology Centre (PITC), where he led a Dutch open innovation project for scalable fabrication of photonic ICs. He is also co-applicant of the JePPIX Pilot line project for scalable manufacturing of photonic circuits. His key field of expertise lies in high-speed opto-electronic components and neuromorphic photonic hardware. In 2019 he was awarded a Dutch Research Council Personal Grant (Veni) for research on integrated spiking laser neurons. Since 2024, he is the coordinator of the EIC Pathfinder SPIKEPro project in which he aims to explore energy-efficient spiking hardware nodes for neuromorphic information processing.
Kaushik Roy is the Edward G. Tiedemann, Jr., Distinguished Professor of Electrical and Computer Engineering at Purdue University. He received his BTech from Indian Institute of Technology, Kharagpur, PhD from University of Illinois at Urbana-Champaign in 1990 and joined the Semiconductor Process and Design Center of Texas Instruments, Dallas, where he worked for three years on FPGA architecture development and low-power circuit design. His current research focuses on cognitive algorithms, circuits and architecture for energy-efficient neuromorphic computing/ machine learning, and neuro-mimetic devices. Kaushik has supervised more than100 PhD dissertations and his students are well placed in universities and industry. He is the co-author of two books on Low Power CMOS VLSI Design (John Wiley & McGraw Hill). Dr. Roy received the National Science Foundation Career Development Award in 1995, IBM faculty partnership award, ATT/Lucent Foundation award, 2005 SRC Technical Excellence Award, SRC Inventors Award, Purdue College of Engineering Research Excellence Award, Outstanding Mentor Award in 2021, Humboldt Research Award in 2010, 2010 IEEE Circuits and Systems Society Technical Achievement Award (Charles Desoer Award), IEEE TCVLSI Distinguished Research Award in 2021, Distinguished Alumnus Award from Indian Institute of Technology (IIT), Kharagpur, Fulbright-Nehru Distinguished Chair, DoD Vannevar Bush Faculty Fellow (2014-2019), SRC Aristotle Award in 2015, Purdue Arden L. Bement Jr. Award in 2020, SRC Innovation Award in 2022, honorary doctorate from Aarhus University in 2023
Special guest – Moderator
Isabel obtained a Master Degree in Physics (Semiconductor Physics) from the University of the Basque Country (Spain) and subsequently, earned a Doctoral Degree in Science (Microelectronics-Materials for Sensors) from the University of Navarra (Spain).
She started her career at AT&T Microelectronics transferred to AT&T-Bell Laboratories (USA) in the field of modelling and simulation of electronic components. Back in Spain, she joined one of the leading manufacturers of Power Discrete components, as an R&D Engineer and later, became Manager of Engineering and Production of the Wafer Fab, what gave her a wide picture of the microelectronics industry. At that position, she started her links with the European Commission as the representative of the group in Eurimus (Eureka Initiative for promotion of microsystem uses) Technical Committee.
Several years later, Isabel transitioned to Project Management in the field of Materials and Microtechnologies for Electronics in the largest technology center in Spain, Tecnalia, where she has initiated, managed and coordinated several new initiatives like the Nanotechnologies Program or the Printed Electronics Platform. She has also been Director of several Business Areas leading their market-technology and IP strategy. During all those years, she has been managing a large portfolio of European and private projects in the field of Micro-Nanofabrication, Functional Surfaces, Sensors and Printed Electronics.
All along her career, she has combined her job with activities as expert in innovation by performing Technology Due Diligences, evaluating new business opportunities for Venture capitals and Family offices or as Innovation Radar Expert for EU projects. She holds a title in Expert in Management of Innovation and Technology from Deusto Business School.
In September 2022 she joined the European Innovation Council as Programme Manager for Sustainable Electronics.
