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Subhasish Mitra is the William E. Ayer Professor of Electrical Engineering and Computer Science at Stanford University, holding dual appointments in both departments. He leads the Stanford Robust Systems Group and serves on the leadership team of the Microelectronics Commons AI Hardware Hub under the US CHIPS and Science Act. His research spans Robust Computing, NanoSystems, Electronic Design Automation (EDA), and Neurosciences, with breakthroughs in X-Compact test compression, carbon nanotube computing, and 3D integration. He has held international roles like the Carnot Chair at CEA-LETI and Visiting Professorships globally. Education & Honors: Recipient of over 40 awards including the IEEE Computer Society’s Harry H. Goode Memorial Award, ACM/IEEE’s A. Richard Newton Technical Impact Award, and the Intel Achievement Award. He earned top academic accolades from IIT Kharagpur and Jadavpur University, and is a Fellow of ACM and IEEE. Research Impact: Pioneered first-of-their-kind systems like the carbon nanotube computer and monolithic 3D integration. His work on robust computing techniques like QED validation and X-Compact compression has industry-wide adoption, saving billions in manufacturing costs. Collaborates with industry leaders like Intel, Google, and Samsung. Publications & Grants: Over 400 publications, including award-winning papers in DAC, ISSCC, and IEEE journals. Leads grants from NSF, DoE, and industry partnerships. His lab explores cutting-edge topics like neuromorphic computing, 3D thermal scaffolding, and AI hardware acceleration. Administration & Outreach: Serves as Associate Chair (Faculty Affairs) for Stanford’s Computer Science Department. Recognized by students for mentorship, and frequently invited to global forums like the World Economic Forum and National Academy of Engineering.

• Robust Computing
• NanoSystems
• Electronic Design Automation (EDA)
• +3 more

Boris Murmann is Professor at Stanford University, specializing in integrated circuit design, mixed-signal computing, and energy-efficient AI hardware. His research advances neural interface technologies, analog design automation, and tinyML systems. Recent work develops ultra-low-power neural recording ICs for brain-computer interfaces, RRAM-based memory systems, and open-source semiconductor design frameworks. Publications demonstrate innovations in compressive sensing for neural data, hardware-algorithm co-design, and reinforcement learning for analog circuit synthesis. Significant contributions include Medusa (TinyML processor), EMBER (RRAM macro), and methodologies for coarsely-quantized computer vision and analog design automation.

• Integrated Circuits
• Mixed-Signal Computing
• Neural Recording Systems
• +1 more

Ningyuan Cao is an Assistant Professor in the Department of Electrical Engineering at the University of Notre Dame, College of Engineering. He leads the Circuit and System Intelligence Research Lab , focusing on the intersection of advanced hardware design and real-time/low-power machine learning applications. Education : Ph.D., Electrical and Electronics Engineering, Georgia Institute of Technology (2020) M.S., Electrical Engineering, Columbia University (2015) B.S., Electrical and Electronics Engineering, Shanghai Jiao Tong University (2013) His research investigates custom analog/mixed-signal circuits , digital architecture , and micro-system design for machine learning acceleration, distributed intelligence, and data-driven IC design automation. Key application domains include Internet-of-Everything, tactile internet, and mixed reality systems. Recent publications highlight work on Bayesian neural networks , privacy-preserving bio-signal encoders , transformer-based surrogate models , and compute-in-memory architectures . Technical themes span neuromorphic computing, uncertainty quantification, and hardware security.

• Machine Learning Acceleration
• Real-Time Systems
• Low-Power Circuits
• +7 more

Dr. Michael Stevens is a Senior Lecturer at University of New South Wales (UNSW) Canberra , where he focuses on advanced manufacturing and biomedical device control systems . His work bridges digital manufacturing for SMEs with smart artificial heart technologies , emphasizing industry collaboration and translational research. Specializes in physiological control systems for rotary blood pumps Develops unobtrusive fall detection systems for dementia patients Leads international projects on total artificial heart development Education : B.Eng (Medical - First Class Honours), Queensland University of Technology (2010) PhD in Physiological Control for Biventricular Assist Devices, University of Queensland (2014) Research Trends show consistent focus on: Machine learning for biomedical diagnostics (2018–2025) mmWave radar and thermal sensors in patient monitoring (2021–2024) Computational fluid dynamics in artificial heart modeling (2016–2024) Physiological control algorithms for rotary blood pumps (2011–2025) Scientific Awards : UNSW Scientia Education Award (2021) for contextual teaching Heart Foundation Runner-up for "Smart Artificial Hearts" pitch (2021) ARC PGC Supervisor Award (2017) for mentoring Grants & Supervision : Holds over $6 million in competitive funding including MRFF and ARC grants. Currently supervises 4 PhD students while maintaining industry partnerships with VitalCare and BiVACOR. Labs & Facilities : Works across UNSW Engineering labs and Graduate School of Biomedical Engineering platforms, including mock circulation loops and high-performance computing clusters for CFD simulations.

• Biomedical Engineering
• Advanced Manufacturing
• Digital Manufacturing
• +6 more

Farinaz Koushanfar is a Professor in the Department of Electrical and Computer Engineering at the Jacobs School of Engineering, University of California San Diego (UCSD) . She holds the Siavouche Nemat-Nasser Endowed Chair and serves as Founding Co-Director of the Center for Machine-Intelligence, Computing and Security . Her affiliations include NSF Trust-Hub (Co-PI) and NSF TILOS AI Institute . She also serves on the Editorial Board of The Proceedings of the IEEE . Research Focus: Prof. Koushanfar leads research in secure and efficient computing , including robust/safe AI , hardware/system security , AI-based optimization , and cryptographically secure privacy-preserving computing . Her work pioneered logic obfuscation/locking for chip security, automated co-design of AI systems , watermarking/tracing of deep learning models , and physical proofs of provenance . She explores co-design with cryptographic constructs for privacy preservation and manages nonlinearities in ciphertext domains. Article Trends: Recent publications show expertise in neural watermarking (deepfakes, media authentication), zero-knowledge proof frameworks , Trojan attack defenses in ML models, secure federated learning , and hardware acceleration of cryptographic protocols . Her work combines machine learning , cryptography , and physical design security across 2022-2025 publications. Scientific Awards: Fellow of ACM Fellow of IEEE Fellow of National Academy of Inventors (NAI) Fellow of Kavli Foundation of NAS Inducted to NAI 2024 Fellows Advising & Leadership: She has advised multiple PhD students who became faculty at top universities (e.g., Stanford, Purdue). She chairs conferences like ACM WiSec 2024 and co-led the NSF SaTC decadal review. Her lab ( ACES Lab ) produces award-winning graduates like Bita Rouhani (DAC Under-40 Innovators) and Shehzeen Hussain (UCSD Best Dissertation Award).

• Secure Computing
• Hardware/Software Co-Design
• Machine Learning
• +6 more

Dr Graeme Bragg is a Senior Teaching Fellow at the University of Southampton within the Department of Electronics and Computer Science . His work spans teaching, research, and technical development with a focus on event-driven computing, bioinformatics, and computational modeling. He actively supervises PhD students and collaborates on interdisciplinary projects. Research Interests: Parallel computing, event-driven systems, genotype imputation, Petri net simulations, subglacial hydrology modeling Teaching: Specializes in hardware description languages and computational methods for engineering students Technical Expertise: RISC-V architecture, FPGA acceleration, bespoke compute fabric development His recent publications demonstrate expertise in applying event-driven computing to diverse problems including: 2025: Automated marking systems for SystemVerilog labs 2025: Seasonal dynamics in subglacial hydrology 2023: Genotype imputation using custom hardware 2022: Optimization algorithms and graph analysis Current research explores: Custom RISC-V FPGA clusters for bioinformatics Event-triggered systems for scientific simulations Parallel computing solutions for molecular modeling Contact: gmb@ecs.soton.ac.uk | +44 23 8059 2784

• Parallel Computing
• Event-driven Systems
• Bioinformatics
• +5 more

Pasquale Davide Schiavone holds multiple research and teaching positions at École Polytechnique Fédérale de Lausanne (EPFL), serving as a Lecturer at the School of Computer and Communication Sciences (IC) and as a Scientist at both the Embedded Systems Laboratory (ESL) within the School of Engineering (STI) and PAT Administration. His interdisciplinary work bridges computer architecture, embedded systems design, and biomedical applications, with office located at ELG 136 in Lausanne, Switzerland. Dr. Schiavone's research focuses on ultra-low-power computing systems, particularly RISC-V architectures and TinyML applications for edge devices. His work develops open-source hardware platforms like X-HEEP and HEEPOCRATES that enable energy-efficient AI at the edge, with applications spanning biomedical monitoring, neural interfaces, and wearable computing. He explores innovative hardware-software co-design approaches to overcome energy constraints in resource-limited environments. His recent publications reveal a consistent research trajectory centered on open, configurable computing platforms for specialized applications. The work spans from fundamental RISC-V architecture improvements (ARCANE, e-GPU) to application-specific implementations for biomedical contexts (BiomedBench, neural interfaces). A strong emphasis on energy efficiency permeates all his research, whether through novel arithmetic approaches (Posit), system architecture (near-memory computing), or specialized accelerators (Strela, Quadrilatero). Lecturer, School of Computer and Communication Sciences (IC) Scientist, Embedded Systems Laboratory (ESL), School of Engineering (STI) Scientist, PAT Administration, School of Engineering (STI) Dr. Schiavone teaches courses on hardware compilation, presenting algorithms and methods for transforming hardware description languages into optimized circuit implementations. His Embedded Systems Laboratory work places him at the forefront of developing practical, open-source solutions for next-generation computing challenges in energy-constrained environments.

• Embedded Systems
• RISC-V Architecture
• Ultra-low-power Computing
• +5 more

Carsten Wulff is Associate Professor at NTNU's Department of Electronic Systems, focusing on analog CMOS design automation and circuit compilers. Research: Develops software tools for automated analog IC design, including ciccreator—an open-source compiler for generating custom integrated circuits. Aims to simplify analog design workflows through programmable frameworks. Teaching: Leads courses in Advanced Integrated Circuits (AIC) with public lecture notes and YouTube resources. Current focus includes Python-based circuit design tools.

• Analog CMOS Design
• Circuit Design Automation
• Integrated Circuit Compilers
• +2 more

Pedro Ferreira is a Professor at Iscte Business School, ISCTE - IUL, Lisbon, Portugal. His academic work spans multiple disciplines including business model innovation, cultural management, digital display systems, and consumer behavior. Key research areas: Business Model Innovation, Cultural Management, Digital Display Systems Interdisciplinary work: Healthcare Management, Energy Efficiency, Sensory Marketing Notable collaborations: Rock in Rio, Ferreira's de Castro Cultural Complex His publications demonstrate ecosystem-based approaches to cultural economics, with applications in virtual reality exhibitions and sustainable business practices. Recent work focuses on technology integration in perfume exhibitions and energy efficiency strategies. Earlier research includes pharmacological studies on P2X7 receptors in colitis and foundational financial accounting textbooks. He has analyzed group buying systems in Portugal and explored intersections between management theory and art. Academic contributions span 45 years, with a 2024 patent on digital display systems and a 1979 report on tomato industry economics. Current affiliations include: Iscte Business School ExecED at ISCTE INDEG-ISCTE Edifício INDEG-ISCTE, Lisbon

• Business Model Innovation
• Cultural Management
• Digital Display Systems
• +3 more

Dale Lawrence is a Professor in the Department of Aerospace Engineering Sciences at the University of Colorado Boulder, where he has served continuously since 1991. He directs research at the Research and Engineering Center for Unmanned Vehicles (RECUV), focusing on astrodynamics, satellite navigation systems, and autonomous aerial platforms for atmospheric science. His academic credentials include: PhD in Electrical Engineering from Cornell University (1985) MS in Electrical Engineering from Cornell University (1982) BS in Electrical Engineering from Colorado State University (1980) Professor Lawrence's research spans spacecraft attitude control , vibration isolation , and adaptive control systems , with pioneering work in haptic interfaces for scientific visualization and teleoperation. His recent work emphasizes unmanned aerial systems for Arctic atmospheric research, particularly turbulence measurement and boundary layer studies using custom UAV platforms like DataHawk. This work bridges aerospace engineering with climate science through field campaigns such as MOSAiC and LAPSE-RATE. His publication record reveals a clear trajectory toward Arctic atmospheric science and UAV-based sensing , with increasing focus on turbulence dynamics, sea-ice interactions, and autonomous system validation. The work consistently integrates hardware development (sensors, UAVs) with field deployment in extreme environments. Selected honors include: Best Commercial Potential Award at IEEE Symposium on Haptic Interfaces (2004) Best Paper Presentation at American Control Conference (1994) Teaching Excellence Awards from University of Cincinnati (1990, 1991) Distinguished Publication Award from Martin Marietta Astronautics (1988) Professor Lawrence has led major field campaigns including MOSAiC and LAPSE-RATE, securing funding from NSF and DOE for projects like ERASMUS and ShUREX. His RECUV team develops specialized UAV platforms (DataHawk, HELiX) for atmospheric research, with recent work focusing on machine self-confidence for autonomous decision-making in complex environments. While student advising details aren't specified, his projects involve extensive student participation in hardware development and field operations. He maintains active leadership in Arctic atmospheric research through the DataHawk UAV program and HELiX multispectral systems, with ongoing work on gossamer propeller technology for high-altitude applications and machine self-confidence frameworks for autonomous systems.

• Astrodynamics
• Satellite Navigation Systems
• Autonomous Systems
• +10 more

Alan Mantooth is a Distinguished Professor holding the Twenty-First Century Research Leadership Chair in Engineering within the Department of Electrical Engineering at the University of Arkansas, Fayetteville. He serves as Director of the National Center for Reliable Electric Power Transmission (NCREPT), Executive Director for GRAPES (NSF I/UCRC) and SEEDS (DoE Center), and Deputy Director of the NSF Engineering Research Center for Power Optimization of Electro-Thermal Systems (POETS). His educational background includes: B.S. in Electrical Engineering, University of Arkansas M.S. in Electrical Engineering, University of Arkansas Ph.D. in Electrical Engineering, Georgia Institute of Technology Dr. Mantooth's research centers on analog/mixed-signal IC design, power electronics CAD, and semiconductor device modeling with emphasis on harsh-environment applications. His pioneering work in silicon carbide (SiC) and gallium nitride (GaN) power systems has enabled high-temperature operation for electric vehicles and renewable energy infrastructure, significantly advancing reliability in extreme conditions. His 2025 publications reveal strong trends toward AI-driven power electronics (e.g., SolarFormer++ for PV profiling), wide-bandgap device modeling (β-Ga2O3, SiC), and innovative packaging solutions. Key themes include reliability engineering for extreme environments, multi-physics optimization, and explainable AI for safety-critical power systems. Major scientific recognition includes: IEEE Fellow (2009) for power electronic device modeling Three R&D 100 Awards (2009, 2014, 2016) for SiC power modules IEEE Power Electronics Society Technical Achievement Award (2019) Multiple university teaching/research awards including SEC Faculty Achievement Award (2015) As an exceptional mentor (UA Outstanding Mentor 2006-2008), he co-founded Lynguent and Ozark Integrated Circuits. His centers NCREPT, GRAPES, and SEEDS have secured major funding from NSF, DoE, and industry partners, supporting over 350 refereed publications and numerous patents. Current research focuses on AI-enhanced power electronics, recyclable packaging, and next-generation wide-bandgap device characterization. He leads the NCREPT test facility and multi-institutional teams developing grid-connected power electronic systems, secure energy delivery architectures, and thermal management solutions for high-power-density applications, with direct impact on electric transportation and renewable energy integration.

• Analog and Mixed-Signal IC Design
• Power Electronics
• Semiconductor Device Modeling
• +3 more

Jean-Baptiste Bégueret is a researcher with extensive contributions to integrated circuits , RF design , and low-power electronics . His work spans analog , digital , and mixed-signal systems.

• Integrated Circuits
• RF Circuit Design
• Low-Power Electronics
• +3 more

Francesca Montagna is an Associate Professor at the Department of Management and Production Engineering (DIGEP) , Politecnico di Torino . She serves as Director of the University Strategies Study Center and holds leadership roles in the Politecnico University Centre for Social Affairs. Her research focuses on Innovation Management , Product Development , and Decision-Making Processes in engineering design. Scientific disciplinary sector: IIND-04/A - Manufacturing Technologies and Systems ERC sectors: Industrial design, Management, Decision-Making, Technological Change SDG Goal 9: Industry, Innovation, and Infrastructure Her recent work explores data-driven design , digital transformation , and operations management in manufacturing. She has supervised 8 PhD students, including Graziana Blandino and Teresa Monti , and contributed to projects like NO-STRESS Manufacturing and AIGEDA . Awards include Elsevier's Top 5 Most Highly Cited Papers in Design Studies (2014-2016) . Francesca collaborates with entities such as EIT-Manufacturing and Legacoop Piemonte , and actively participates in international conferences like the International Conference on Engineering Design (ICED) . She is a reviewer for journals including Journal of Engineering Design and Research in Engineering Design .

• Innovation Management
• Product Development
• Engineering Design
• +4 more

Sergio Gago-Masague is a Teaching Professor at the University of California, Irvine (UCI), where he serves in the Department of Computer Science within the School of Information and Computer Sciences. He directs the Engaging Technology and Application Design Lab, focusing on cross-disciplinary research in assistive and educational technologies. Previously, he worked as a Research Scientist at UCI’s California Institute for Telecommunications and Information Technology and lectured in informatics before transitioning to his current role in 2018. His research spans health informatics, human-computer interaction, software engineering, and computer science education. Key projects include developing the Pain Buddy mHealth tool for pediatric cancer pain management, the Maestro platform for teaching AI robustness, and predictive models for improving CS student retention. He has pioneered the use of gamification in education and embedded systems for health monitoring. Education: Ph.D. in Product Engineering, Universitat Politècnica de Catalunya Recent work emphasizes ethical AI in music industry applications, bias mitigation in student admissions algorithms, and leveraging large language models (LLMs) in post-pandemic education. His articles reflect trends in wearable health tech (e.g., transdermal alcohol prediction via hyperdimensional computing) and CS education innovations like customized student-project matching in capstone courses. Recipient of the 2024 UCI Celebration of Teaching Award and a 2023 ICS Awards honoree, Gago-Masague has also contributed to institutional initiatives like the HSI Project for early academic interventions. His lab fosters collaborations across disciplines to design socially impactful technologies.

• Educational Technologies
• Health Informatics
• Human-Computer Interaction
• +7 more

Stefanie Elgeti is Associate Professor and Private Lecturer at the Chair for Computational Analysis of Technical Systems (CATS), Faculty of Mechanical Engineering, RWTH Aachen University. She previously held a professorship in lightweight design at TU Vienna starting in 2019. Her research integrates computational mechanics with manufacturing process optimization, focusing on plastics extrusion, injection molding, and high-pressure die casting. Diploma in Mechanical Engineering, majoring in 'Manufacturing Techniques for Microsystems' PhD (2011): 'Free-Surface Flows in Shape Optimization of Extrusion Dies' Habilitation (2016): 'CAD-Conforming Finite Element Methods in Engineering Design' Her research centers on solving inverse problems in manufacturing through numerical simulation. She employs advanced techniques such as free-surface flow modeling, non-Newtonian material models, spline-based finite elements, and PDE-constrained shape optimization. Her group simulates entire process chains from filling to solidification and warpage prediction, enabling design optimization of cavities and cooling systems. The recent publications (2022–2024) reveal a strong trend toward integrating artificial intelligence—particularly physics-informed neural networks and Bayesian optimization—into traditional simulation workflows. There is increasing emphasis on warpage compensation, shape optimization of extrusion dies, and modeling of biomedical and environmental systems, showcasing a broadening scope from industrial manufacturing to interdisciplinary applications. She is actively involved in academic service, having served as vice-spokesperson of GAMM-Juniors (2013–2014) and currently co-chairing the ECCOMAS Young Investigator Group. While no formal awards are listed, her leadership roles and editorial contributions reflect significant recognition in the computational mechanics community. Prof. Elgeti advises students and leads multiple research initiatives at CATS, including work groups focused on production engineering, fluid-structure interaction, and INTERESST. Her team develops model hierarchies and digital twins for industrial processes, aiming to bridge simulation and real-world manufacturing through intelligent, adaptive systems.

• Computational Mechanics
• Numerical Simulation
• Shape Optimization
• +12 more