Adam Khalifa is an Assistant Professor in the Department of Electrical & Computer Engineering at the University of Florida. His research focuses on low-power analog/RF/Mixed-mode ASIC design, miniaturization of biomedical devices, wireless powering solutions, and neural stimulation/recording techniques in animal models. He holds a PhD from Johns Hopkins University and degrees from The Hong Kong University of Science and Technology. His work emphasizes implant packaging, electrode microfabrication, and coil design for medical applications. Key research areas include developing energy-efficient wireless systems for implanted devices, such as magnetoelectric antennas and galvanic body-coupled powering. He has pioneered advancements in miniaturized implantable devices, including the 'Microbead' stimulator. His NIH T32 Fellowship (2019) and Ferdinand H. Fellowship (2018) reflect his impactful contributions. Publications highlight innovations in wireless power transfer, metamaterials for biomedical implants, and injectable microdevice fabrication. His work spans from circuit-level modeling to in vivo validation, emphasizing both technical and biological integration challenges. Collaborative efforts address challenges like implant migration tracking via MRI and energy harvesting for battery-free systems.
Brandon Reagen is an Assistant Professor in the Department of Electrical and Computer Engineering at New York University's Tandon School of Engineering, with affiliations in Computer Science, the Center for Advanced Technology in Telecommunications (CATT), and the NYU Center for Cybersecurity (CCS). He holds a PhD in Computer Science from Harvard (2018) and undergraduate degrees in Computer Systems Engineering and Applied Mathematics from the University of Massachusetts, Amherst (2012). His research focuses on computer architecture, hardware acceleration for deep learning and privacy-preserving computation, and VLSI design. He pioneered efficient deep learning accelerator designs through unsafe optimizations and contributed to benchmarking frameworks like Aladdin and MachSuite. His work spans privacy-preserving machine learning, secure computing systems, and hardware-software co-design for cryptographic protocols. Key achievements include the NSF CAREER Award (2024) and Siebel Scholar recognition (2018). His research centers on advancing secure computing through innovations like zero-knowledge proof accelerators (e.g., zkSpeed), fully homomorphic encryption frameworks (Orion), and entropy-guided privacy techniques for large language models. He leads interdisciplinary efforts at CATT and CCS to bridge hardware design and cybersecurity challenges. Reagen's contributions include over 50 publications in top-tier conferences (e.g., ISCA, ASPLOS, MLSys) and industry collaborations at Facebook AI. His work emphasizes practical solutions for encrypted computation efficiency, privacy-preserving inference, and scalable secure systems.
Steven Meikle is a Professor of Medical Imaging Physics and Head of the Imaging Physics Laboratory at the Brain and Mind Centre, University of Sydney. He also serves as Deputy Director (Preclinical) of Sydney Imaging and Deputy Director of the National Imaging Facility's Sydney node. His expertise spans advanced imaging technologies, with a focus on PET/SPECT instrumentation and molecular imaging. He holds a B.App.Sc.(Hons) from the University of Technology Sydney and a PhD from the University of New South Wales. Research focuses include developing novel PET systems like Open-field PET (for freely moving rodents) and Total Body PET, which enhance imaging sensitivity and enable real-time behavioral studies alongside brain function analysis. Collaborations include Tsinghua University (China) and UC Davis (USA). He leads projects on motion correction, quantitative imaging, and AI-driven analysis. Key achievements include over 180 peer-reviewed publications, editorial roles in Physics in Medicine and Biology , and leadership in professional societies. Awards include IEEE Senior Membership and Australian Institute of Physics Fellowship. Current student projects explore Total Body PET applications, motion correction, and radiopharmaceutical evaluation. Teaching roles include medical physics courses in diagnostic radiography and medical physics programs. He advises on imaging ethics, facility implementation, and translational research bridging basic science and clinical applications.
Shih-Chii Liu holds the rank of Privatdozent (Associate Professor) in the Department of Information Technology and Electrical Engineering at ETH Zürich. He is affiliated with the Institute of Neuroinformatics , a joint institute between the University of Zurich and ETH Zurich. His research focuses on neuromorphic engineering, bio-inspired neural hardware, and edge computing systems, emphasizing energy-efficient algorithms and sensor technologies. Key research areas include neuromorphic sensors for real-time data processing, sparsity-aware neural networks, and adaptive computing architectures for edge devices. His work spans applications such as speech enhancement, wearable health monitoring, and bio-inspired keyword spotting systems. He leads the Sensors Research Group, which develops neuromorphic systems integrating novel sensors, spiking neural networks, and low-power hardware accelerators. Recent projects include the DeltaKWS low-power keyword spotting IC, EFLOP computational cost metrics for spiking networks, and NeuroBench benchmarking frameworks for neuromorphic systems. His contributions emphasize bridging biological neural principles with practical engineering solutions for IoT and embedded systems. Liu teaches courses such as Neuromorphic Engineering I and collaborates on cross-disciplinary projects involving neuroprosthetics, smart wearables, and multimodal sensor fusion. His work is characterized by hardware-software co-design approaches to tackle challenges in real-time, low-latency, and energy-constrained computing environments.
Paul Gerrans is a Professor of Finance at the University of Western Australia (UWA) Business School, specializing in consumer financial decision-making, retirement savings, and financial literacy. He has held roles including Chair of the Business School's Regional Ethics and Research Committee and membership in the OECD/INFE Research Committee and PISA Financial Literacy Expert Group. His research integrates behavioral economics, aging studies, and policy analysis, with a focus on improving retirement outcomes through education and interventions. Education Overview: Previous positions at Edith Cowan University (1990–2010) and visiting roles at Susquehanna University (1995, 2007). Research Interests: Financial literacy acquisition in youth and its decline in older adults. Impact of cognitive function on retirement savings decisions. Cross-cultural retirement savings behaviors (e.g., Thailand, Malaysia). Role of social norms and values in financial choices. Awards: 2013 Outstanding Achievement Award from Financial Literacy Australia. Grants & Projects: Australia Research Council grants on retirement savings education (2009–2012). CSIRO-funded Superannuation Cluster projects (2013–2016). Recent collaborations on pandemic impacts on retirement savings (2023–2025). External Roles: Member of OECD’s INFE Research Committee and PISA Financial Literacy Group. Advisory roles for ASIC, National Seniors Australia, and Thai universities. His work bridges academia and policy, addressing global challenges in financial inclusion and aging populations.
Jonathan Viventi is the Hawkins Family Associate Professor of Biomedical Engineering at Duke University, with additional appointments as Assistant Professor in Neurosurgery and Neurobiology, and as a Faculty Network Member of the Duke Institute for Brain Sciences. His research focuses on developing flexible, high-resolution neural interfaces for diagnosing and treating neurological disorders, particularly epilepsy, and advancing brain-machine interfaces. Education: Ph.D. in Engineering from the University of Pennsylvania (2010). Research Interests: Dr. Viventi's work centers on flexible electronics for high-resolution brain interfacing . Key areas include: Micro-electrocorticography (μECoG) arrays with thousands of channels Wireless, fully implantable neural prosthetics for speech restoration Real-time seizure detection and prediction systems Chronic biointegration of soft electronic materials Translational applications in epilepsy, stroke, and Parkinson's disease Scientific Awards: MIT Technology Review Innovators Under 35 (2014) Popular Science Brilliant 10 (2014) Grants & Funding: Dr. Viventi leads multiple NIH-funded projects including: A Wireless µECoG Prosthesis for Speech (2021-2026) Neuro-CROWN: Optimized Ultra-Flexible CMOS Electrode Arrays (2021-2025) Next-Generation Wireless Intracranial Arrays for Post-traumatic Epilepsy (2021-2025) Laboratory & Teams: His lab develops cutting-edge neural interface technologies, collaborating across engineering, neuroscience, and clinical departments at Duke to translate flexible electronics into therapeutic devices.
Glenn Gulak is a Professor in the Department of Electrical and Computer Engineering at the University of Toronto's Faculty of Applied Science and Engineering. He holds the Canada Research Chair in Signal Processing Microsystems and the Edward S. Rogers Sr. Chair in Engineering. A Senior IEEE Member and Professional Engineer in Ontario, he received his Ph.D. from the University of Manitoba. His research spans: Digital Communication Systems: VLSI implementations of MIMO detectors, lattice reduction algorithms, and homomorphic encryption accelerators Lab-on-Chip Microsystems: CMOS biosensors for rapid pathogen detection and integrated fluorescence imaging Recent publications (2019-2025) demonstrate a dominant focus on privacy-enhancing technologies, with 73% concentrated in cryptographic hardware and homomorphic encryption. This reflects industry-aligned work on confidential computing and secure data processing. Awards & Honors: IEEE Millennium Medal (2001) Canada Research Chair in Signal Processing Systems (Tier 1, 2005-2012) Edward S. Rogers Sr. Chair (2005-2010) RBC Research Prize L. Lau Chair (1999-2004) Teaching Award (1999) He has supervised 44+ graduate students (PhD/MASc) with thesis topics spanning VLSI communication systems, CMOS biosensors, and cryptographic accelerators. Notable industry collaboration includes serving as CTO of a semiconductor startup (2001-2003). His lab develops hardware for quantum cryptography and secure medical computation.
Andrea Guerrieri serves as an Associate Professor at the School of Engineering, University of Applied Sciences and Arts Western Switzerland Valais (HES-SO Valais-Wallis), specializing in reconfigurable computing and electronics design automation. His research has established significant industry impact through tools like DynaRapid and Dynamatic, with technology adopted by major semiconductor companies including MIPS, Intel, and AMD-Xilinx. BSc HES-SO in Industrial Systems - System-on-Chip specialization BSC HES-SO in Computer and Communication Systems - Digital Design specialization MSc HES-SO in Engineering - Embedded Hardware and Firmware specialization Professor Guerrieri's research focuses on reconfigurable computing, electronics design automation (EDA), and security, with particular emphasis on FPGA design, high-level synthesis, and post-quantum cryptography implementations. His work bridges the gap between theoretical computer architecture and practical hardware implementations, with strong applications in space technology and embedded security systems. His recent publications demonstrate increasing focus on energy-efficient implementations for space applications and quantum-resistant cryptographic systems. Analysis of his 15 most recent publications reveals a clear research trajectory toward optimizing FPGA implementations for post-quantum cryptography and space applications. His work consistently addresses the performance bottlenecks in high-level synthesis while maintaining practical applicability for industry partners like NASA, CERN, and major semiconductor companies. The recent surge in best paper awards (three in 2024 alone) reflects growing recognition of his contributions to efficient FPGA compilation techniques and cryptographic implementations. Scientific Awards: Best Paper Award at FPL 2024 Best Paper Award at HPEC 2024 Best Paper Award at ISFPGA 2020 Outstanding Short Paper Award at IEEE HPEC 2024 Outstanding TPC Member Award at DAC 2024 IEEE Senior Member (2021) Multiple Best Paper nominations (FCCM 2022, FPL 2022, HiPEAC 2022) Professor Guerrieri actively participates in international research projects including the DyReCte project (2019-2021) on dynamically reconfigurable cryptoengines for nano-satellites. He currently chairs the Onboard Computing topic for the Swiss consortium CHEESE affiliated with NASA SSERVI and collaborates extensively with industry partners including AMD-Xilinx, NVIDIA, Arm, NASA, and CERN, as well as academic institutions like ETH Zurich and University of Geneva. His current research focuses on developing next-generation EDA tools and reconfigurable computing platforms for both terrestrial and space applications. His laboratory work centers around FPGA-based prototyping and validation, with specialized facilities for space applications testing. Professor Guerrieri leads a research team that includes Andres Upegui, Quentin Berthet, Laurent Gantel, and Gabriel Da Silva Marques, focusing on practical implementations of reconfigurable architectures for security and space applications.
Jason Collins is a Senior Lecturer and Program Director for the Graduate Certificate and Master of Behavioural Economics at the University of Technology Sydney (UTS), within the Economics Discipline Group of the Business School. He holds a PhD from the University of Western Australia, focusing on the intersection of economics and evolutionary biology. His research explores how behavioral science can enhance AI systems in financial services and strengthen applied behavioral economics through improved theories and methods. Previously, he co-founded PwC Australia’s behavioral economics practice and led data science teams at ASIC. He blogs at jasoncollins.blog and has been published in outlets like the Economic Record . Collins teaches undergraduate and postgraduate behavioral economics courses, including subjects on industry projects, research design, and consumer decision-making. He has secured grants, such as a 2024 project on AI in consumer finance with the Commonwealth Bank. His peer-reviewed work spans topics like research reproducibility, evolutionary economics, and heritability of fertility.
Johanna von Gerichten is a Research Fellow at the University of Surrey's School of Chemistry and Chemical Engineering. She holds roles on committees such as the Athena Swan Implementation Committee (ASIC) and the PMB MRC IAA and HEIF panel. Her research focuses on lipid metabolism and mass spectrometry method development, with projects integrating techniques like MALDI, DESI, SIMS, Raman spectroscopy, and PIXE for studying disease models (e.g., tuberculosis, eye disease, skin absorption). Education: B.Sc. Biological Chemistry (2012), University of Applied Sciences Mannheim, Germany M.Sc. Biomedical Science and Technology (2014) Her research emphasizes multimodal imaging approaches and single-cell lipidomics. Recent publications (2024) address lipidomics biomarker challenges and single-cell analysis methods. She co-supervises two PhD students exploring radiation-induced metabolic effects and nanoplastic impacts in zebrafish. Her work aligns with Surrey's innovation initiatives, as seen in 2024 cancer research advancements and 2022 early-career researcher grants.
Timo Hämäläinen is a Professor of Computer Engineering at Tampere University, leading the Unit of Computing Sciences within the Faculty of Information Technology and Communication Sciences. He is a core member of the System-on-Chip research group and the Computer Engineering Team, actively contributing to the System-on-Chip Hub initiative. His research focuses on System-on-Chip (SoC) design methodologies, FPGA-based high-level synthesis, real-time embedded systems, and open-source hardware-software co-design frameworks like RISC-V and HEVC encoding. He has pioneered work on agile SoC development processes and validation techniques for large-scale hardware systems. Key research areas include: High-level synthesis (HLS) optimization for FPGAs Real-time processor architectures and context-switching latency reduction Formal verification of IP-XACT-compliant SoC designs Resilient RISC-V MPSoC implementations Hardware-accelerated algorithms for signal processing and networking His recent publications (2023-2025) emphasize agile SoC development frameworks, hardware-software co-design for real-time systems, and validation methodologies for large-scale embedded systems. He has contributed to open-source projects like Kvazaar HEVC encoder and the Kactus2 IP-XACT toolchain. Academic advising includes students such as Santéri Mäki-Äijö (formal verification), Arto Oinonen (RISC-V tooling), and Sakari Lahti (processor modeling). His work integrates academic research with industrial collaboration through frameworks like the Fault-slip-Through quality assessment methodology.
Yu Yang is a Researcher at KTH Royal Institute of Technology's Division of Electronics and Embedded Systems. He has been affiliated with KTH since at least 2020 and currently holds a postdoc position. His research focuses on neuromorphic computing, FPGA/ASIC implementation, approximate computing, and embedded systems design. He also explores ergonomic applications using wearable sensors to address workplace safety and musculoskeletal disorders. Yang has taught courses like Digital Design and Embedded Hardware Design in ASIC and FPGA , demonstrating expertise in both theoretical and applied electronics. His work bridges hardware acceleration (e.g., memristor-based neural networks) with practical applications like surgeon workload analysis and posture correction systems. Notable projects include the eBrainII ASIC implementation of a human-scale cortical model and developing smart workwear systems for real-time vibrotactile feedback. Publications span IEEE conferences (DATE, FDL, ASP-DAC) and journals like Frontiers in Neuroscience and Journal of Signal Processing Systems . His research often emphasizes low-power, high-performance computing while addressing ergonomic challenges in manufacturing and healthcare sectors.
Dr Aliar Hossain serves as Head of Department for MSc Advanced Practice in Business, Computing & Cyber Security at Northumbria University London, where he also leads industry engagement and the Employer Engagement Advisory Board (EEAB). With over 18 years of academic experience in UK higher education, he specializes in learning pedagogies, strategy development, and SDG consulting. His research spans sustainable development strategy, corporate governance, and ethical business practices. He has consulted on academic projects validated by QAA, Ofsted, BAC, ASIC, and Pearson/Edexcel, while serving as an external examiner for multiple universities. His work emphasizes global citizenship, anti-corruption initiatives, and sustainable development in South Asia. Dr Hossain actively contributes to public discourse through international speaking engagements on leadership development and corporate culture across UK and South Asian institutions. He supports nonprofit projects in South Asia focused on sustainable business and healthcare access, and serves on the editorial board of the Journal of Business and Retail Management Research.
LODOVICO RATTI is a Full Professor of Electronics at the University of Pavia's Department of Electrical, Computer and Biomedical Engineering. He leads the Electronic Instrumentation Group and Laboratory, and holds roles such as Secretary of the IEEE Radiation Instrumentation Steering Committee and Chair of the IEEE Nuclear and Plasma Sciences Italy Section. His research focuses on low-noise analog circuits for radiation detectors, semiconductor device noise characterization, and radiation effects in microelectronics. He has contributed to major international projects including CMS, RD53, and PixFEL, developing pixel detectors for high-luminosity environments. His work spans technologies like CMOS, JFET, and SPADs, with emphasis on radiation hardness and detector optimization. Ratti has authored over 300 publications (h-index 24), and has led teaching initiatives in Electronics and Industrial Measurements. He also serves on editorial boards and conference committees, advancing both academic and applied research in his field. Key collaborations include CERN, Fermilab, and Argonne National Laboratory. His research impacts particle physics, synchrotron light sources, and medical imaging through innovations in detector design and radiation tolerance. Current projects include 28 nm CMOS front-ends for future colliders and pixel sensor upgrades for Belle II and FCC-ee experiments.
Olaf Von Ramm is the Thomas Lord Distinguished Professor of Engineering and Professor of Biomedical Engineering at Duke University. His research focuses on diagnostic ultrasound imaging systems, infrared imaging, and medical instrumentation. He has pioneered advancements in high-speed 3D ultrasound imaging, cardiac function quantification, and ultrasonic transducer design. B.S., University of Toronto (1968) M.S., University of Toronto (1970) Ph.D., Duke University (1973) Dr. von Ramm's research spans diagnostic ultrasound systems , medical device development , and cardiovascular imaging technologies . Key projects include: Real-time volumetric ultrasound systems Cardiac stimulation devices for arrhythmia prevention Harmonic wavefront correction techniques Acoustic scatter imaging for tissue characterization His work combines engineering innovation with clinical applications , particularly in cardiology and vascular disease diagnostics. Notable trends include: Progressive development from 2D to 4D imaging systems Integration of VLSI ASICs and piezoelectric micromachined transducers Advancements in angle-independent blood flow measurement Scientific recognition includes: Fellow, American Institute for Medical and Biological Engineering (1998) Thomas Lord Distinguished Professor of Engineering Dr. von Ramm's laboratory employs advanced equipment including second-generation phased array systems, Kontron image processors, and 256-channel ultrasound data acquisition systems. He has coauthored over 40 publications in ultrasound imaging , cardiac function analysis , and transducer array design , with recent work focusing on 4D imaging systems and autogenic cardiac wave visualization.
