Michel M. Maharbiz is a Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley. He leads research on miniaturized bioelectronic interfaces, including neural dust implants and cyborg insects. He holds affiliations with the Berkeley Sensor & Actuator Center (BSAC), Center for Neural Engineering & Prostheses (CNEP), and SWARM Lab. His education includes a Ph.D. in EECS from UC Berkeley (2003) and a B.S. in EE from Cornell University (1997). Maharbiz's research integrates MEMS, ultrasonic systems, and synthetic biology to develop wireless neural interfaces, implantable sensors, and biohybrid devices. Key focus areas are neural dust technology for peripheral nerve recording, magnetoelastic strain sensors for medical applications, and electrochemical biosensing using bacterial flagellar motors. His publications emphasize neural interfaces, ultrasonic implants, and biomedical monitoring. Recent articles explore ultrasonic power delivery (2025), radiation detectors for oncology (2025), and fracture-healing smart plates (2019). Trends include miniaturization of wireless implants, closed-loop therapeutic systems, and novel biomaterials. Scientific Awards: McKnight Technological Innovations in Neuroscience Award (2017) Chan-Zuckerberg Biohub Investigator (2017) NSF CAREER Award (2009) MIT TR10 Top Emerging Technology (2009) Bakar Fellows Spark Award (2012) He directs the Maharbiz Lab, advancing neural dust and bioelectronic interfaces. Projects include impedance-based fracture monitoring, carbon fiber neural arrays, and hernia repair sensors. Funding includes NSF and industry partnerships for implantable device development.
Affiliation & Education Scott Hauck is a Professor at the University of Washington's Department of Electrical & Computer Engineering and an Adjunct Professor in Computer Science & Engineering. He leads the Adaptive Computing Machines and Emulators (ACME) Lab . He earned his BS in EECS from UC Berkeley (1990), and MS/PhD in CSE from the University of Washington (1992/1995). Research Focus Dr. Hauck specializes in FPGA-based reconfigurable computing with applications in: Quantum Computing: FPGA controllers for trapped-ion quantum systems enabling precise laser control and quantum state readout. Medical Imaging: Portable radiation sensors for personalized cancer therapy and PET scanner enhancements. High-Energy Physics: FPGA readout systems for ATLAS pixel detectors at CERN's Large Hadron Collider. AI Acceleration: Real-time machine learning inference for scientific applications via projects like hls4ml. His work bridges hardware innovation with computational physics, emphasizing real-time processing and low-latency systems. Publication Trends Recent research focuses on FPGA-accelerated machine learning for particle physics (e.g., transformer networks for LHC trigger systems) and quantum computing instrumentation. Earlier work established foundations in reconfigurable computing architectures and medical imaging electronics. Awards & Recognition Distinguished Teaching Award, University of Washington (2010) Advising & Funding Leads the ACME Lab with extensive funding from NSF, DARPA, NIH, DOE, and industry partners including Intel, Xilinx, and Microsoft. Mentored over 30 MS/PhD students in VLSI, reconfigurable systems, and scientific computing. Collaborations & Labs Directs the ACME Lab (EE1-307), collaborating with UW Radiology (Prof. Robert Miyaoka), UW Physics (Prof. Shih-Chieh Hsu), and Drexel University (Prof. Josh Agar). Projects include quantum control systems, LHC readout electronics, and medical sensor networks.
Raphael Hauser is an Associate Professor in Numerical Mathematics at the University of Oxford's Mathematical Institute, Director of Graduate Studies - Teaching, and Tanaka Fellow in Applied Mathematics at Pembroke College. His affiliations include membership in the Data Science, Numerical Analysis, and Mathematical and Computational Finance research groups, as well as a fellowship at the Alan Turing Institute. Education: PhD in Operations Research, Cornell University, Ithaca, USA Dipl. Math. ETH, Swiss Federal Institute of Technology (ETH Zurich), Switzerland Research interests span data science, numerical optimisation, medical imaging, distributed computing, and applied probability/statistics. His work integrates mathematical rigor with practical applications, particularly in optimization algorithms, machine learning theory, and medical imaging technology. Publications focus on optimization theory, stochastic processes, medical imaging systems, and computational finance, with recurring themes in non-convex optimization guarantees, PCA variants, and X-ray tomography innovations. Awards: Oxford University Teaching Award (2007) SIAM Optimization Prize (2005) SIAM Student Paper Prize (2000) Advising includes 15+ DPhil students and 40+ MSc students, with projects in optimization, finance, imaging, and machine learning. Current postdocs and students are affiliated with the Alan Turing Institute and industrial partners like Siemens and Macquarie Group. He leads teams in the Mathematical Institute's research groups and collaborates with the Alan Turing Institute on large-scale data science initiatives.
Judith Driscoll is Professor of Materials Science at the University of Cambridge in the Department of Materials Science & Metallurgy. She holds the prestigious Royal Academy of Engineering Chair in Emerging Technologies and serves as a Visiting Staff Member at Los Alamos National Laboratory. As the founding Editor-in-Chief of APL Materials, she has significantly contributed to the materials science community. Dr. Driscoll's research focuses on Energy Efficient Oxide Materials for Information and Communications Technologies and energy devices. Her work spans the development of non-volatile memory, resistive switching devices, and ferroelectric materials for neuromorphic computing applications. She investigates oxide thin films for applications ranging from data storage to energy generation and conversion, with particular emphasis on creating more energy-efficient device technologies to handle the exponential growth of data-centric applications. Her recent publications demonstrate strong trends in developing novel oxide-based memory devices with improved energy efficiency, particularly for AI applications. The work shows significant progress in hafnium-zirconium oxide ferroelectrics, resistive switching mechanisms, and vertically aligned nanocomposite structures for enhanced device performance. These innovations address critical challenges in reducing the unsustainable energy demands of modern computing, particularly for artificial intelligence systems. Fellow of the Royal Academy of Engineering Fellow of the Materials Research Society Fellow of the American Physical Society Fellow of IOM3, IOP, and Women Engineers Society Fellow of the American Academy of Arts and Sciences Recipient of ERC Advanced Grant Editor-in-Chief of APL Materials Dr. Driscoll leads a vibrant research group that has secured significant funding including her Royal Academy of Engineering Research Chair, an ERC Advanced Grant, and an ECCS-EPSRC grant in collaboration with researchers from the USA. She has founded the Cambridge Centre for Neuromorphic Computing (Neucam) in 2023. Her group operates world-leading growth equipment including pulsed laser deposition with RHEED control, high temperature oxide sputtering, and spatial ALD systems. She collaborates extensively across the University of Cambridge and with international partners to solve complex materials challenges, with her group's role often being to identify optimal materials for functional goals, predict fabrication methods, and then create and characterize these materials.
Kristofer Pister is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He co-directs the Berkeley Sensor and Actuator Center (BSAC) and the Ubiquitous Swarm Lab. His career spans groundbreaking innovations in Micro/Nano Electro Mechanical Systems (MEMS), Control Systems, and Low-Power Circuits, with a focus on Smart Dust and synthetic insects. Education: Ph.D. and M.S. in EECS from UC Berkeley (1992, 1989); B.A. in Applied Physics from UC San Diego (1986). His research areas include MEMS , Control Systems , Robotics , and Integrated Circuits , with recent work on self-powered micro-sensors, crystal-free radios, and interplanetary swarm networks. Key awards include the ISA Albert F. Sperry Founder Award (2009) , Alexander Schwarzkopf Prize (2006) , and the NSF CAREER Award (1996) . He has authored numerous influential publications in wireless sensor networks and microrobotics. His lab, Ubiquitous Swarm Lab , explores distributed robotics and swarm intelligence. Pister emphasizes open collaboration in research, ethical conduct in academia, and efficient resource utilization for graduate students.
Prof. Dr. André Rubbia is a Full Professor of Experimental Physics at ETH Zurich's Department of Physics, holding this position since December 2003 after serving as Associate Professor from 1998. His research spans neutrino physics, astro-particle physics, and dark matter detection through major international collaborations including CERN, Gran Sasso National Laboratory, and Fermilab. He currently serves as Co-Spokesperson for the billion-dollar DUNE neutrino project at Fermilab, managing over 900 scientists. His educational background includes: Diploma in Physics from the University of Geneva (1990), with thesis work on the L3 experiment at CERN's LEP accelerator Ph.D. in Physics from MIT (1993) under Nobel Laureate S.C.C. Ting, focusing on high-energy electron-positron collisions Rubbia's research centers on fundamental particle interactions, particularly neutrino oscillations and physics beyond the Standard Model. He pioneered liquid Argon Time Projection Chamber (LAr TPC) technology and dual-phase detection systems, enabling breakthroughs in neutrino mass measurements and dark matter searches. His work spans underground laboratories (Gran Sasso, Canfranc), the LHC's CMS detector, and neutrino beam experiments like T2K. Recent explorations include antimatter gravity tests, electron-positron bound states, and dark hidden sector searches. His 2025 publications reveal intense focus on neutrino oscillation parameter precision (T2K, Hyper-Kamiokande), FASER's LHC neutrino program, and DarkSide-20k dark matter detector development. Key themes include cross-section measurements, advanced detector technologies (SiPMs, emulsion tracking), and statistical methods for oscillation analysis, reflecting integration of theoretical modeling with cutting-edge instrumentation. Scientific recognition includes: Breakthrough Prize for Fundamental Physics (2016) awarded to the international team for discovering matter-anti-matter asymmetry in neutrino oscillations APS Viewpoint selection for editing the paper announcing first electron neutrino appearance at accelerators Rubbia has supervised over fifty PhD and Master's theses while securing substantial research funding as Principal Investigator for 20+ Swiss National Science Foundation projects and Coordinator of two EU FP7 Design Studies. His DUNE leadership involves complex international grant management across 30+ countries. He leads ETH Zurich's experimental particle physics group across multiple facilities: the ICARUS neutrino detector at Gran Sasso, CMS at CERN, DUNE at Fermilab, and DarkSide-20k for direct dark matter detection. His team developed the first underground ton-scale liquid argon detector and maintains collaborations with Japanese (Super-Kamiokande) and American (Fermilab) institutions.
Dr. Arvydas Ruseckas is a Research Fellow at the School of Physics and Astronomy, University of St Andrews. His research focuses on organic photovoltaics, semiconductor materials, and optoelectronic systems. Key areas include exciton dynamics in solar cells, perovskite photovoltaics, and X-ray detector technologies. He collaborates extensively on interdisciplinary projects, bridging material science with marine biology and quantum optics. Research interests span organic solar cells, energy harvesting, and semiconductor physics, with contributions to understanding charge transfer mechanisms and material optimization. He has published widely on topics such as exciton diffusion, light-harvesting in red algae, and polariton condensates in organic semiconductors. His work often involves experimental studies of thin films, photoluminescence, and device performance, with a focus on advancing sustainable energy technologies and novel optoelectronic applications.
Mats Danielsson is a Professor at KTH Royal Institute of Technology, leading the Medical Imaging research group within the Department of Particle Astrophysics and Medical Imaging. He has coordinated major projects like the ERC Advanced Grant for the Si3 project (starting 2024) and the EIC Pathfinder's 1MICRON project (starting 2025). His work focuses on advancing photon-counting detectors, X-ray technologies, and medical imaging systems. Notable recognitions include the 2024 KTH Innovation Award and the 2022 Hans Wigzell Science Prize. Danielsson has co-founded companies such as Sectra Mamea AB and C-RAD AB, and holds 135 patents with over 150 scientific publications. Education: MSc (1990) and PhD (1996) from KTH, followed by postdoctoral research at Lawrence Berkeley National Lab (1996–1998). He joined KTH in 1999, where he has held his current professorship since then. His research spans medical imaging, detector innovation, and radiation physics applications in healthcare. Research Interests: Development of high-resolution CT detectors, photon-counting technologies, compact X-ray sources, and AI-driven image processing. His recent work emphasizes minimizing radiation exposure while enhancing diagnostic precision through novel detector designs and machine learning algorithms. Key Projects: ERC Si3 project (3D detector for nuclear medicine), EIC 1MICRON (micrometer-scale imaging), and MedTechLabs collaboration with Karolinska Institutet. He has pioneered innovations such as MicroDose mammography and advanced photon-counting spectral CT systems. Awards: KTH Innovation Award (2024), Hans Wigzell Prize (2022), IVA membership (2017), Polhem finalist (2014), and INGVAR Award (2004). Advising & Grants: Over 150 scientific publications, 135 patents, and leadership in multi-institutional projects. Teaches courses on medical imaging and modern physics at KTH. Labs/Teams: Director of the Medical Imaging Group at KTH, co-founder of MedTechLabs, and collaborator across academia and industry in medical imaging innovation.
Jiwoong Park is Professor of Chemistry and Chair of the Department of Chemistry at the University of Chicago, and simultaneously Professor of Molecular Engineering in the Pritzker School of Molecular Engineering. His interdisciplinary research group, the Park Group, is jointly affiliated with the James Franck Institute and the Materials Research Science and Engineering Center (MRSEC) at UChicago, and operates from the Gordon Center for Integrative Science. Education & Training Ph.D., University of California, Berkeley (2003) B.S., Seoul National University (1996) Junior Fellow, Rowland Institute, Harvard University (2003–2006) Assistant → Associate Professor, Department of Chemistry and Chemical Biology, Cornell University (2006–2016) Research Interests Park’s research centers on the science and technology of precisely engineered nanomaterials, particularly atomically-thin two-dimensional (2D) crystals and van der Waals solids. Spanning chemistry, physics, materials science and electrical engineering, his group develops novel synthetic, imaging and characterization techniques to uncover new physical phenomena and translate them into scalable device technologies. Key thrusts include growth of wafer-scale molecular crystals, optical and transport spectroscopy of 2D semiconductors, mechanical behavior of polycrystalline nanomembranes, and integration of these materials into photonic, electronic and energy-harvesting devices. Scientific Awards Elected Fellow of the American Physical Society (2022) – “for the development of synthetic, imaging, and characterization techniques of atomically thin materials and the discovery of novel properties of van der Waals solids.” Clarivate Highly Cited Researcher (2023) – recognition for multiple papers ranking in the global top 1% by citations in Materials Science and Chemistry. Group & Collaborations The Park Group is an interdisciplinary team of postdocs, graduate researchers and undergraduates housed in the Gordon Center for Integrative Science. The group actively collaborates with colleagues across the Department of Chemistry, Department of Physics, and the Pritzker School of Molecular Engineering, leveraging shared facilities at the James Franck Institute and MRSEC to push the frontiers of 2D material science.
Angela Di Fulvio is an Associate Professor and Donald Biggar Willett Faculty Scholar at the University of Illinois at Urbana-Champaign, holding joint appointments in the Department of Nuclear, Plasma, and Radiological Engineering and the Center for Digital Agriculture at NCSA. She leads the Nuclear Measurement Laboratory (NML), focusing on radiation detection technologies for nonproliferation, medical physics, and nuclear security. Her academic journey includes a Ph.D. in Nuclear Engineering and Industrial Safety from the University of Pisa (2012), preceded by M.Sc. and B.Sc. degrees in Bioengineering. Her research emphasizes neutron detection instrumentation, radiation protection in therapy, and safeguards applications. Key areas include next-generation thermal neutron detectors, boron neutron capture therapy dosimetry, and spent nuclear fuel imaging. She has pioneered work on pulse shape discrimination using commercial ASICs and developed algorithms for neutron-gamma discrimination in harsh environments. Di Fulvio’s 15+ peer-reviewed articles span advanced detection systems, Monte Carlo modeling, and machine learning for radiation imaging. Notable contributions include a physics-based forward model for spent fuel imaging and variational autoencoder-based pulse discrimination. Her work has been recognized with the Dean’s Award for Excellence in Research. Professional roles include Associate Editor of Radiation Measurements and editorial board member of Nature Scientific Reports . She chairs APS’s Instrumentation and Measurement Science group and ANS’s Nuclear Nonproliferation Policy Division. Recent courses taught include NPRE 451-452 labs, Nuclear Safeguards, and Student Research Seminars.
Kyle McCall is an Assistant Professor in the Department of Materials Science and Engineering at the University of Texas at Dallas, within the Erik Jonsson School of Engineering and Computer Science. He holds a PhD in Applied Physics from Northwestern University (2019) and a B.S. in Physics and Mathematics from the University of Notre Dame (2014). He served as a Postdoctoral Research Fellow at ETH Zurich, Switzerland, from 2019 to 2021. Research Interests: Dr. McCall's research lies at the intersection of materials science, chemistry, and physics, focusing on the synthesis and characterization of complex semiconductors for energy and radiation detection applications. His group employs a materials-by-design approach to develop novel functional optoelectronic materials, particularly halide perovskites and related compounds. Key areas include crystal growth (via Bridgman method), X-ray crystallography, and the development of materials for solar cells, light-emitting devices, X-ray photodetectors, and neutron/gamma-ray scintillators. Publication Trends: His recent publications (all from 2021) highlight a strong focus on halide perovskite materials for radiation detection and optoelectronics. Themes include room-temperature gamma-ray detection, neutron imaging using luminescent materials, structural instabilities in perovskites, and optical behavior tuning via cation engineering. The work combines fundamental structure-property studies with device-relevant performance metrics. Scientific Awards and Memberships: Member, American Chemical Society (ACS) Member, Materials Research Society (MRS) Advising and Grants: As a tenure-track faculty member, Dr. McCall leads the McCall Research Group at UT Dallas, mentoring students in interdisciplinary materials research. He was part of the 2021 cohort of new tenured/tenure-track faculty at UT Dallas. While specific grants are not listed, his research program is clearly supported by institutional funding and infrastructure, including crystal growth and characterization facilities. Laboratories and Teams: He founded the crystal growth component of the ETH+ SynMatLab facility during his postdoc at ETH Zurich. At UT Dallas, he leads his own research group focused on materials chemistry and functional device integration, continuing his work on single crystal growth and optoelectronic characterization.
Dr. Craig S. Levin is a Professor of Radiology at Stanford University's Molecular Imaging Program at Stanford (Nuclear Medicine), with courtesy appointments in Physics, Electrical Engineering, and Bioengineering. He also holds memberships in Bio-X, the Cardiovascular Institute, the Wu Tsai Human Performance Alliance, and the Stanford Cancer Institute. Dr. Levin received his B.S. Summa Cum Laude in Physics and Mathematics from UCLA in 1985, followed by M.S., M.Phil., and Ph.D. degrees in Physics from Yale University in 1987 and 1993. His educational achievements were recognized with multiple honors including Phi Beta Kappa, Sigma Pi Sigma, and various departmental awards at UCLA. Dr. Levin's research focuses on the development of novel instrumentation and software algorithms for molecular imaging. His work spans medical physics, biomedical engineering, and instrumentation development with specific emphasis on positron emission tomography (PET), gamma camera technology, and multimodal imaging systems. His laboratory explores new concepts in radiation detection, image reconstruction algorithms, and the application of these technologies to cancer, heart disease, and neurological disorders. A notable aspect of his research involves pushing the physical limits of sensitivity and spatial, spectral, and/or temporal resolutions in imaging systems. His recent publications demonstrate a strong focus on enhancing PET technology, particularly time-of-flight capabilities, with significant work on improving coincidence timing resolution, developing MR-compatible PET systems, and applying deep learning techniques to image reconstruction and normalization. His research shows a clear trajectory toward higher resolution imaging with improved quantitative accuracy for both clinical and preclinical applications. Dr. Levin's scientific achievements have been recognized with numerous awards: American Institute for Medical and Biological Engineering's College of Fellows Academy of Radiology Research Distinguished Investigator Recognition Award National Research Service Award from NIH (1993-5) Pilot Research Award from the Society of Nuclear Medicine (1996) Multiple honors from UCLA including Phi Beta Kappa and Sigma Pi Sigma Full Tuition and Research Fellowship and Bates Graduate Fellowship from Yale University As an educator and mentor, Dr. Levin directs the NIH-NCI funded T32 Stanford Molecular Imaging Scholars postdoctoral training program and serves as a Doctoral Dissertation Advisor for students in Bioengineering and Biophysics. He currently advises five postdoctoral scholars and three doctoral candidates. His laboratory, the Molecular Imaging Instrumentation Laboratory, comprises approximately 20 members who work on developing new imaging technologies and translating them into clinical applications. Dr. Levin has secured substantial NIH funding as Principal Investigator along with grants from other government agencies, industry partners, and private institutions to support his research program. Dr. Levin's Molecular Imaging Instrumentation Laboratory is at the forefront of developing new imaging technologies that bridge physics, engineering, and medicine. The lab focuses on creating instrumentation for in vivo imaging of cellular and molecular signatures of disease, with particular emphasis on pushing the physical limits of imaging performance. Their work spans computer modeling, sensor development, electronics design, data acquisition systems, and advanced image processing algorithms. The lab maintains strong industry partnerships to translate their innovations into products used for patient care worldwide.
David A. Muller serves as the Samuel B. Eckert Professor of Engineering in the School of Applied and Engineering Physics at Cornell University and co-directs the Kavli Institute at Cornell for Nanoscale Science. His research group focuses on developing quantitative electron microscopy methods to understand materials properties at the atomic scale, with particular emphasis on sustainable energy applications and quantum materials. Muller's laboratory utilizes some of the world's highest resolution electron microscopes housed in specially designed, environmentally isolated rooms. Muller received his undergraduate education at the University of Sydney and earned his Ph.D. in Physics from Cornell University in 1996. Between 1997 and 2003, he was a member of the technical staff at Bell Laboratories, where he applied his expertise in imaging single atoms and atomic-scale spectroscopy to determine the physical limits of transistor miniaturization. In 2003, he returned to Cornell as a faculty member, where he has since established himself as a leader in advanced electron microscopy techniques. Muller's research spans multiple frontiers in materials science, with particular focus on understanding how electronic-structure changes at the atomic scale control macroscopic behavior in diverse systems like turbine blades, fuel cells, and transistors. His current work emphasizes the physics of renewable energy materials, atomic-scale control of materials to create electronic phases that cannot exist in bulk, and developing hardware and algorithms for 'big data' acquisition from high-bandwidth pixelated electron microscope detectors. His group's work bridges theoretical physics and experimental techniques, requiring researchers who can think in both real and reciprocal space while considering both fundamental principles and practical applications. Analysis of Muller's recent publications reveals a strong trend toward advancing electron ptychography and 4D-STEM techniques for atomic-scale imaging. His group has pioneered methods for 3D atomic-scale metrology, strain mapping, and imaging of radiation-sensitive materials. The research spans applications from semiconductor technology to quantum materials and energy storage systems, demonstrating the versatility of his microscopy approaches across multiple scientific domains. Top 100 Young Innovator by Tech Review Magazine (2003) Burton Medal from Microscopy Society of America (2006) Ernst Ruska Prize of German Society for Electron Microscopy (2021) John Cowley Medal from International Federation of Societies for Microscopy (2023) Fellow of American Physical Society Fellow of American Association for the Advancement of Science Fellow of Microscopy Society of America Muller has mentored an extensive group of students and postdocs who have gone on to successful careers in academia and industry. His former students hold faculty positions at institutions including Rice University, University of Southern California, Seoul National University, Colorado School of Mines, and the University of Michigan, among others. His research has been supported by substantial grants, including a $22.5M NSF grant that accelerates materials discovery. The Muller lab maintains close collaborations with the Kavli Institute at Cornell and PARADIM (Platform for the Accelerated Realization, Analysis, and Discovery of Interface Materials). The Muller lab operates at the forefront of electron microscopy, housing specialized instrumentation including high-resolution transmission electron microscopes in environmentally isolated rooms. The group collaborates extensively with other research teams at Cornell and worldwide, focusing on understanding materials atom by atom. Current research directions include applying machine learning to electron microscopy data analysis, developing cryogenic techniques for studying low-melting-point materials, and exploring quantum phenomena in engineered materials 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.
Tom Dhaene is a Full Professor at Ghent University, affiliated with the Department of Information Technology (INTEC-IDLab) within the Faculty of Engineering and Architecture (FEA). He also holds a position at imec, a research and innovation hub in nanoelectronics and digital technologies. Research Unit: Internet Technology and Data Science Lab (IDLab) Academic Rank: Full Professor Affiliations: Ghent University, imec His research focuses on data-efficient machine learning, surrogate modeling, Gaussian processes, Bayesian optimization, and system identification. He has developed widely used software tools such as the SUMO toolbox and ooDACE, and holds 5 U.S. patents. His work bridges theoretical advancements with practical applications in engineering and biomedical domains. Recent publications highlight his contributions to physics-informed machine learning, antenna design, microwave optimization, and healthcare applications. Notably, he explores Bayesian active learning, multi-objective optimization under uncertainty, and efficient modeling techniques for complex systems. Prof. Dhaene's research has been recognized through over 500 peer-reviewed publications and collaborations across academia, industry, and government sectors globally.
