PLENARY SPEAKERS
University of Oviedo (Spain)
Nanoscale magnetic textures in 3D: X-ray vector tomography and applications
María Vélez pursued her studies at University Complutense in Madrid where she obtained her PhD in 1995. After a postdoctoral stay at University of California San Diego, she joined the Physics Department of University of Oviedo in 1998 where she is currently a Full Professor in Condensed Matter Physics. Her research interests have been centered in the study of vortex propagation in hybrid superconducting/magnetic systems and, more recently, in the study of magnetic textures at the nanoscale in multilayers and in patterned structures in collaboration with the group of Prof. Salvador Ferrer at ALBA Synchrotron.
High Density Interconnect Pathfinding, Intel Corporation (USA)
Advanced packaging technologies for heterogeneous integration (HI)
Ravi Mahajan is an Intel Fellow responsible for Assembly and Packaging Technology Pathfinding for future silicon nodes. Ravi also represents Intel in academia through research advisory boards, conference leadership and participation in various student initiatives. He has led Pathfinding efforts to define Package Architectures, Technologies and Assembly Processes for multiple Intel silicon nodes including 90nm, 65nm, 45nm, 32nm, 22nm and 7nm silicon. Ravi joined Intel in 1992 after earning his Ph.D. in Mechanical Engineering from Lehigh University. He holds the original patents for silicon bridges that became the foundation for Intel’s EMIB technology. His early insights have led to high-performance, cost-effective cooling solutions for high-end microprocessors and the proliferation of photo-mechanics techniques for thermo-mechanical stress model validation. His contributions during his Intel career have earned him numerous industry honors, including the SRC’s 2015 Mahboob Khan Outstanding Industry Liaison Award, the 2016 THERMI Award from SEMITHERM, the 2016 Allan Kraus Thermal Management Medal & the 2018 InterPACK Achievement award from ASME, the 2019 “Outstanding Service and Leadership to the IEEE” Awards from IEEE Phoenix Section & Region 6 and most recently the 2020 Richard Chu ITherm Award and the 2020 ASME EPPD Excellence in Mechanics Award. He is one of the founding editors for the Intel Assembly and Test Technology Journal (IATTJ) and currently VP of Publications & Managing Editor-in-Chief of the IEEE Transactions of the CPMT. He has long been associated with ASME’s InterPACK conference and was Conference Co-Chair of the 2017 Conference. Ravi is a Fellow of two leading societies, ASME and IEEE. He was elected to the National Academy of Engineering in 2022 for contributions to advanced microelectronics packaging architectures and their thermal management.
ETH Zürich (Switzerland)
Magnetic Microrobots for Biomedical Applications
Prof. Dr. Salvador Pané i Vidal (Barcelona, 1980) is a Professor of Materials for Robotics at the Institute of Robotics and Intelligent Systems (IRIS) and Co-Director of the Multi-Scale Robotics Lab at ETH Zürich. He obtained his B.S., M.S., and PhD in Chemistry from University of Barcelona (UB). With over 170 publications in international peer-reviewed journals and educational books, Pané’s current focus is on integrating chemistry and electrochemistry with the field of small-scale robotics.
Particularly, Pané specializes in miniaturizing magnetic materials, conductive polymers, and smart materials for targeted drug delivery. Prof. Pané has been coordinator and PI of several EU projects (including FET Open, FET Pro-active, EIC Opern), and has been awarded with an ERC Starting Grant (2013) and a Consolidator Grant (2019). He chaired the COST Action "e-MINDS" from 2015 to 2019. He is also advisory editor for the journals Applied Materials Today (Elsevier) and Small Science (Wiley). He also represents Switzerland in the European Academy of Surface Technology (EAST). He has co-founded two startups, Magnes AG and Oxyle AG. In 2019, he received the Big-on-Small Award for his contribution in the field of micro- and nanorobotics. He was also granted an ERC Proof-of-Concept award in 2019.
Instituto de Ciencia y Tecnología del Carbono (INCAR), Spain
Rosa María Menéndez López (born February 12, 1956, in Corollos, Cudillero, Asturias) is a distinguished Spanish scientist. She made history as the first woman to preside over the Spanish National Research Council (CSIC), serving in this role from November 2017 until June 2022.
Rosa earned her degree in Organic Chemistry from the University of Oviedo in 1980 and later obtained her doctorate from the same institution in 1986. She commenced her career at the CSIC, initially at the National Coal Institute, now known as the Institute of Carbon Science and Technology (INCAR), based in Oviedo.
In addition to her role at CSIC, Menéndez López served as Vice President of Science Europe from June 1, 2018, representing the interests of the scientific community across 43 European research and innovation funding agencies. She remains a staunch advocate for women in science and is actively involved in initiatives such as the Margarita Salas Foundation, dedicated to advancing the role of women in scientific fields.
IBM (USA)
Quantum Computing: what, why and what next?
Shesha Raghunathan joined IBM in 2011 and is currently Global Lead for Startup Ecosystem in IBM Quantum. He is responsible for all engagement touch points with quantum startups– including technology access, collaboration, go-to-market, networking opportunities.
In his previous role, he was part of strategic partnership team in IBM Quantum that explored opportunities to engage with Governments/Research Labs on large deals. Prior to that, he was part of Electronic Design Automation (EDA) Timing analysis development team and worked on various aspect of analysis including noise, timing abstraction, reporting along with analytics and machine learning.
Shesha got his PhD in Electrical Engineering (Quantum Computing) from University of Southern California, LA in 2010. His current research interests include near-term quantum algorithms, circuit optimization and quantum machine learning.
