Jonathan Baugh is a Professor in the Department of Chemistry at the University of Waterloo, serving as Director of the Quantum Information Graduate Program. His research focuses on quantum devices, nanoelectronics, and molecular electronics with affiliations at the Institute for Quantum Computing and Waterloo Institute for Nanotechnology. He leads the Baugh Research Lab, exploring quantum control, semiconductor spin qubits, and superconducting hybrid systems. Research interests include quantum information processing, nanoscale charge transport, and the development of next-generation photonic sources. His work bridges quantum physics and materials science, with recent breakthroughs in dopant-free semiconductors and single-molecule transistors. Publications emphasize scalable quantum architectures, noise mitigation in quantum control, and phase-coherent molecular electronics. Current projects involve cryogenic CMOS device modeling and topological quantum computing in silicon-based systems. No awards are explicitly listed, though his work has been highlighted in invited reviews and special sessions on quantum systems. Advising focuses on graduate students in quantum nanotechnology and condensed matter physics. His lab collaborates on integrated quantum networks and III-V/Si nanowire photodetectors. Labs/Teams: Baugh Research Lab (Quantum Nanoelectronics Group), Institute for Quantum Computing (IQC), Waterloo Institute for Nanotechnology (WIN).
Battista Biggio is a Full Professor at the University of Cagliari, Italy, affiliated with the Department of Electrical and Electronic Engineering under the Faculty of Engineering and Architecture. His research focuses on machine learning security, adversarial attacks, and cybersecurity. He co-founded the cybersecurity firm Pluribus One and has pioneered foundational work in poisoning attacks and adversarial robustness. Education: MSc (2006), PhD (2010). He holds editorial roles as Associate Editor-in-Chief for Elsevier's Pattern Recognition Journal and serves on IEEE TNNLS and IEEE CIM editorial boards. His awards include the 2022 ICML Test of Time Award and the 2021 Pattern Recognition Medal. He chairs IAPR TC1 and organizes conferences like S+SSPR and AISec. Research interests span adversarial machine learning, malware detection, and secure AI systems. He leads initiatives such as the sAIfer Lab and co-develops the SecML-Torch library. Teaching includes courses on Machine Learning Security and Industrial Software Development. Notable contributions include seminal papers like 'Poisoning Attacks against Support Vector Machines' and 'Wild Patterns.' He manages over 10 research projects and advises on AI security for industrial applications. His work bridges academic research with practical cybersecurity solutions.
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.
Julia Thom-Levy is a Professor of Physics in the College of Arts and Sciences at Cornell University, serving as Deputy Director of the Cornell Laboratory of Accelerator-Based Sciences and Education and Vice Provost for Academic Innovation. Her career at Cornell progressed from Assistant Professor (2005-2012) to Associate Professor (2012-2018) and Professor (2018-present), following prior research roles at SLAC and Fermilab. She earned her Physics Dipl. (1997) and Ph.D. (2001) from Hamburg University. Her research centers on experimental particle physics, with expertise in heavy quark physics, hadron collider physics, and silicon detector development for both particle physics and X-ray science applications. She leads critical work on CMS experiment upgrades at CERN's LHC, focusing on radiation-hard pixel detectors and Higgs boson/top quark physics analysis. Her 2013-2018 publications reveal a consistent focus on precision measurements in top quark physics and Higgs boson studies through CMS collaboration, alongside innovative detector technology development. The research demonstrates strong interdisciplinary connections between high-energy physics and advanced materials science. Awards and Honors: Fellow, German National Scholarship Foundation (1993-1997) She advises graduate student Lena Franklin and has mentored postdocs Joseph Reichert and Jose Monroy, along with undergraduates Hannah Hu, Benjamin Myers, Jeffrey Backus, and Alexander Albert. Her group secures significant funding including a $3.8M NSF grant for early universe research and $2.7M for the Active Learning Initiative. She directs detector R&D for CHESS light source applications and leads Cornell's academic innovation efforts through the Active Learning Initiative, which has transformed classroom instruction across STEM disciplines.
Mark Bocko is a Distinguished Professor of Electrical and Computer Engineering at the University of Rochester, affiliated with the Hajim School of Engineering & Applied Sciences. He holds roles as Director of the Center for Emerging and Innovative Sciences (CEIS) and Director of Audio & Music Engineering. He earned his PhD in Physics from the University of Rochester in 1984, focusing on gravitational wave detectors. His research spans audio signal processing, sensors, superconductivity, and quantum computing. Notable contributions include flat-panel loudspeaker development, non-contact ECG sensors, and quantum coherence studies in Josephson junctions. Research interests include audio and acoustic signal processing, computer audition, and sensor technologies. His work integrates interdisciplinary approaches, combining electrical engineering, physics, and computer science. Awards include the 2012 Goergen Award for Teaching and Mercer Brugler Distinguished Teaching Professor (2008–2011). Recent publications address modal crossover networks for loudspeakers, vibrational touch sensing, and room impulse response modeling. He has advised PhD students on topics like spatial audio rendering and musical vibrato analysis. His labs focus on advancing audio engineering and smart sensor systems through collaborative industry partnerships.
Aurora Maccarone serves as an RAEng Research Fellow within the Institute of Photonics and Quantum Sciences at Heriot-Watt University's School of Engineering & Physical Sciences. Her work focuses on advanced photonics applications for challenging environments, particularly underwater and obscured conditions. Her research expertise spans: Single-photon LiDAR systems for underwater 3D imaging Photon-counting detector arrays for depth profiling Real-time reconstruction algorithms for obscurant-penetrating imaging Quantum sensing applications in marine environments Recent publications demonstrate consistent innovation in single-photon imaging techniques, with emphasis on underwater applications (2023-2024) and obscurant penetration (2022). Her work shows strong interdisciplinary connections between optical engineering, computational imaging, and environmental sensing. Key publications reveal growing impact in underwater LiDAR technology, with multiple high-citation papers on photon-efficient imaging systems. Dr. Maccarone actively supervises PhD students and has created significant research datasets. Her collaborations span international institutions, with notable contributions to sensor hardware development and computational imaging algorithms. Recent work shows increasing integration of machine learning techniques with traditional photon-counting approaches.
Olivier Pfister is a Professor in the Department of Physics at the University of Virginia , with courtesy appointments in Electrical and Computer Engineering (2022–). His research focuses on experimental quantum optics and quantum information , particularly leveraging optical frequency combs to develop scalable quantum computing platforms. The Quantum Fields and Quantum Information (QFQI) group , which he leads, has pioneered techniques for generating multipartite entanglement in continuous-variable systems, achieving cluster-state entanglement in 60+ qumodes (with potential scaling to thousands). Collaborations span institutions like NIST, University of Sydney, CUNY, and Jefferson Laboratory, with applications in quantum simulation , non-Gaussian state characterization , and hybrid quantum technologies . Key contributions include the 2013 APS Fellowship for groundbreaking work on quantum frequency combs, NSF Distinguished Research Awards , and patents in quantum photonic devices. His group’s NSF-funded research (e.g., QLCI Preliminary Proposal, $3.2M; RAISE-EquIP, $750K) explores fault-tolerant quantum computing, machine learning integration, and microresonator-based entanglement. Pfister’s scientific awards include the 2013 UVA Distinguished Research Career Award and the 1996 JILA Clever Idea Contest Second Prize . His students and postdocs (e.g., Amr Hossameldin , Miller Eaton , Rajveer Nehra ) have published extensively on quantum tomography, cluster states, and photonic detector design. Pfister also serves on advisory and planning committees at UVA, emphasizing interdisciplinary collaboration across physics , engineering , and quantum information .
Professor Bert Smith is a distinguished academic at the University of Oxford, serving as a Fellow of Lincoln College. He holds the position of Professor in the Faculty of Classics, with a specialization in Greek Archaeology and Roman Art/Archaeology. His academic journey includes MA, MPhil, and DPhil degrees from Oxford University. Prior to his current role, he was a Harkness Fellow at Princeton University (1983-85) and taught Hellenistic and Roman art at New York University’s Institute of Fine Arts (1986-1995). His research focuses on the art and visual cultures of the ancient Mediterranean, particularly the relationship between visual representation and social/political contexts. As director of the Aphrodisias excavation project since 1991, he has contributed significantly to understanding the archaeology of Greek cities in the Eastern Roman Empire. Key achievements include a British Academy/Philip Leverhulme Fellowship (2007-2008) and leadership in the AHRC-funded 'Last Statues of Antiquity' project (2009-2012), resulting in a collaborative book (2016). Teaching responsibilities include lectures and seminars on Greek and Roman art and archaeology. His publications span over four decades, with notable works on sarcophagi iconography, Aphrodisias excavations, and Hellenistic art. He actively collaborates with institutions like the Oxford Centre for Greek and Roman Antiquity (OCGRA). Current research continues to explore late antiquity art and archaeology through fieldwork and interdisciplinary projects.
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.
Donna Naples is a Professor in the Department of Physics & Astronomy at the University of Pittsburgh, affiliated with the Dietrich School. Her research focuses on neutrino physics, particularly their fundamental properties and oscillations. She is involved in major experiments such as NOvA, MicroBooNE, and the upcoming DUNE project at Fermilab. Her work contributes to understanding neutrino masses, mixing matrices, and potential sterile neutrinos. Naples has been recognized as a Fellow of the American Physical Society (2018). Research Interests: Neutrino oscillations and cross-section measurements High-intensity neutrino beam experiments (NuMI) Detector development for neutrino physics Search for sterile neutrinos and beyond-Standard-Model interactions Key Contributions: Leadership in the MicroBooNE detector design Analysis of MINERvA neutrino interaction data Role in planning the DUNE experiment Awards: Fellow of the American Physical Society (2018) Advising & Collaboration: Advises graduate student Fan Gao Collaborates with international teams on neutrino experiments
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.
Luca Demetrio is an Assistant Professor at the University of Genoa, Italy, specializing in adversarial machine learning and cybersecurity. Previously, he was a Post-doctoral Researcher at the PRA Lab within the Department of Electrical and Electronic Engineering at the University of Cagliari. He holds bachelor's (2015), master's (2017), and Ph.D. (2021) degrees from the University of Genova, with his doctoral thesis focusing on formalizing evasion attacks against security detectors. His research emphasizes enhancing the robustness of machine learning models against adversarial attacks, particularly targeting malware detectors, SQL injection defenses, and Windows security systems. He leads the development of SecML Malware, a Python library for generating adversarial Windows malware, and contributes to the SecML framework. His work has been published in top-tier journals like ACM TOPS and IEEE TIFS. Key research interests include adversarial example generation, malware analysis, and cybersecurity defense mechanisms. He has explored query-efficient attacks on phishing detectors, certified adversarial robustness via randomized smoothing, and robust synthetic data-driven threat detection. His recent studies (2023–2025) address challenges in hardening machine learning models against evasion attacks, adversarial SQL injection countermeasures, and securing autonomous driving systems from adversarial reinforcement learning attacks.
