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Takuya OouraView profile

Assistant Professor

• Numerical Analysis
• Numerical Integration
• Algorithms
• +3 more

Takuya Ooura is an Assistant Professor at the Research Institute for Mathematical Sciences (RIMS) at Kyoto University, specializing in numerical analysis and mathematical software development. His work bridges theoretical mathematics with practical applications in scientific computing and software development. Dr. Ooura earned his educational credentials through a rigorous academic path: he graduated from Hokuriku High School in 1987; completed his undergraduate studies at Nagoya University's School of Science in 1992; earned his Master of Engineering from the Department of Applied Physics at the University of Tokyo in 1994; and completed his PhD (Engineering) from the same department in 1997. His academic journey continued with a Research Fellowship from the Japan Society for the Promotion of Science (1997) followed by a position as Research Associate at RIMS, Kyoto University (2000). Dr. Ooura's research focuses on numerical integration algorithms, particularly his groundbreaking double exponential formula for Fourier-type integrals, which has been incorporated into Mathematica's NIntegrate function. He has also developed a high-speed FFT library that's utilized in Google Chrome browser (visible in chrome://credits). His work on continuous Euler transformation for accelerating convergence of slowly decaying integrals represents significant innovation in numerical analysis. His research spans both theoretical development and practical implementation of mathematical algorithms with real-world applications. His publication record demonstrates consistent contributions to numerical analysis, with particular emphasis on quadrature methods, integral transforms, and high-precision computation. His work shows a clear progression from theoretical foundations to practical implementations, with several algorithms achieving widespread adoption in commercial and open-source software. Paper prize awarded by JSIAM (2000) for 'A continuous Euler transformation and its application to Fourier transforms of slowly decaying functions' Paper prize awarded by JSIAM (2001) for 'Improvement of the PI Calculation Algorithm and Implementation of Fast Multiple-Precision Computation' Paper prize awarded by JSIAM (2005) for 'An Improved Convergence Test for the Double Exponential Formula' Japan Society for Industrial and Applied Mathematics 4th Achievement Award (2014) for 'Pioneering and practical development of the double exponential numerical integration method' Dr. Ooura has developed several widely used mathematical software packages including the double exponential integral formula, Clenshaw-Curtis numerical integration rule, and a general-purpose FFT library. His FFT package is particularly notable for its speed and accuracy, with benchmark tests showing superior performance compared to other implementations. His software has been incorporated into major projects including Google Chrome and SETI@home, demonstrating the practical impact of his theoretical work. His future research directions include further development of numerical computation libraries and applying his methods to various computational problems.

Jeremy DahlView profile

Professor

• Medical Ultrasound Imaging
• Ultrasonic Beamforming
• Image Reconstruction
• +7 more

Jeremy Dahl is a Professor of Radiology (Pediatric Radiology) at Stanford University School of Medicine. He directs the Ultrasound Imaging & Instrumentation Lab and serves as Director of Research Academic Affairs in the Department of Radiology since 2020. He holds multiple affiliations across Stanford including Bio-X, the Cardiovascular Institute, Wu Tsai Human Performance Alliance, Maternal & Child Health Research Institute, Stanford Cancer Institute, and Wu Tsai Neurosciences Institute. Dr. Dahl received his B.S. in Electrical Engineering from the University of Cincinnati (1999) and Ph.D. in Biomedical Engineering from Duke University (2004). His research focuses on developing ultrasonic beamforming and image reconstruction methods for diagnostic imaging applications, particularly techniques that generate high-quality images in difficult-to-image patients. His laboratory specializes in B-mode and Doppler imaging techniques that utilize additional information from ultrasonic wavefields to improve image quality and develop real-time imaging systems for clinical applications including cardiac, liver, and fetal imaging. Dr. Dahl's research has led to significant advancements in ultrasound molecular imaging platforms, sound speed estimation, aberration correction, and reverberation noise suppression. His work often bridges engineering innovation with clinical applications for cancer detection and other diseases. His recent publications demonstrate strong focus on machine learning applications in ultrasound, distributed aberration correction, and molecular imaging techniques. Fellow, American Institute of Ultrasound in Medicine (2021) Senior Member, Institute of Electrical and Electronics Engineers (2020) Distinguished Investigator Award, The Academy for Radiology & Biomedical Imaging Research (2018) Outstanding Paper Award, IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society (2011) Dr. Dahl serves in editorial roles for major journals including IEEE Transactions on Medical Imaging (2017-2024) and IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control (2013-Present). His laboratory has successfully translated numerous innovations into clinical applications, with multiple patents including recent developments in pulsed focused ultrasound therapy and speed of sound quantification.

• Microelectronics
• Nanotechnology
• RF Engineering
• +3 more

Prof. Dr. Amelie Hagelauer holds a professorship in Micro- and Nanosystem Technology at the TUM School of Computation, Information and Technology, Technical University of Munich. Her work focuses on advanced electronics and systems integration across quantum computing hardware, resistive memory technologies, and high-frequency RF systems. She has contributed to innovations in superconducting qubit readout architectures, multi-level RRAM designs, and 3D-integrated CMOS-compatible quantum devices. Research interests span quantum hardware design, nanoelectronic devices, RF front-end systems, and emerging memory technologies. Her work emphasizes practical implementation challenges such as low-power operation, high-voltage handling in RF switches, and wafer-scale fabrication processes. Recent projects include D-band radar systems, energy-efficient 60 GHz transceivers, and antenna tuning solutions for 5G applications. Publications from 2023-2025 showcase advancements in resistive switching device characterization, mitigation of TLS losses in superconducting qubits, and reconfigurable AI accelerators using RRAM-based digital twins. Her work bridges theoretical device physics with practical integrated circuit design, addressing scalability and reliability in next-gen electronics. Awards and grants: None explicitly listed in provided texts. Active collaborations include EU-funded projects on quantum computing platforms and TUM's Electronic Photonic Integration initiatives. Leads research teams in microsystem technology with emphasis on cross-disciplinary approaches combining CMOS processes, MEMS, and quantum engineering.

• Memristive Systems
• Neuromorphic Engineering
• Photonics
• +3 more

Elias Passerini is a Researcher at the Institute of Electromagnetic Fields (IEF), ETH Zürich, part of the Department of Information Technology and Electrical Engineering. His work focuses on memristive devices and their applications in neuromorphic computing, photonics, and nanoelectronics. He completed his doctoral thesis on 'Memristors for Neuromorphic Computing' in 2025, exploring volatility control and synaptic response tuning. His research emphasizes atomic-scale memristive systems, three-terminal architectures, and material innovations like Sn alloying for improved device stability. Key contributions include developing versatile nanoscale memristive switches with gate tuning capabilities and demonstrating metamaterial graphene photodetectors with record-breaking bandwidth. Passerini collaborates with the Center for Single-Atom Electronics and Photonics, advancing low-power neuromorphic hardware and optoelectronic integration. His publications span conferences like MEMRISYS and journals such as ACS Nano and Light: Science & Applications .

Chih-Hung ChenView profile

Professor

• Biomedical Technologies
• Microelectronics & VLSI
• Digital & Smart Systems
• +5 more

Dr. Chih-Hung (James) Chen is a Professor in the Department of Electrical & Computer Engineering at McMaster University. His research focuses on noise-related issues in semiconductor devices, low-noise circuit design for medical and communication applications, and thermal noise characterization in nano-scale transistors. He holds senior member status in IEEE and is a licensed Professional Engineer in Ontario. Education: Ph.D., McMaster University, 2002 M.A.Sc., Simon Fraser University, 1997 B.Sc., National Central University, Taiwan, 1991 Research interests include biomedical technologies, microelectronics & VLSI, and digital/smart systems. He has collaborated with companies like Sony Corporation, United Microelectronics Corporation, and Focus Microwaves. His work is supported by grants from the Canada Foundation for Innovation (CFI), NSERC, and the Ontario Innovation Trust (OIT). Notable achievements include serving on the International Advisory Committee of the International Conference on Noise and Fluctuations (2015) and as an editor for the Journal of Low Power Electronics and Applications since 2022. Teaching includes courses like Analysis and Design of RF ICs for Communications and Electronic Devices and Circuits 2. His research lab focuses on advancing noise measurement techniques and designing ultra-low-power analog circuits for emerging applications.

Duminda WijesekeraView profile

Professor

• Cybersecurity
• Cyber-Physical Systems
• Digital Forensics
• +5 more

Duminda Wijesekera serves as Professor in the Department of Cyber Security Engineering and Department of Computer Science at George Mason University, where he was inaugural chairman of the Cyber Security Engineering Department until December 2022. He concurrently held the position of visiting research scientist at the National Institute of Standards and Technology (NIST) from 2007-2022 and maintains status as a fellow at the Potomac Institute of Policy Studies. He leads the Mason Innovation Laboratory at Mason Square, driving translational research in cyber-physical security. His educational foundation includes: PhD in Computer Science, University of Minnesota (1997) PhD in Mathematical Logic, Cornell University (1990) BSc in Mathematics, University of Colombo Professor Wijesekera's research centers on cyber-physical system security , with pioneering work in Intelligent Transportation Systems spanning trains, aircraft, and connected vehicles. His digital forensics innovations establish frameworks for evidence-based scenario reconstruction and error management, while his formal methods research provides mathematical guarantees for safety-critical systems. Current projects address Next G-based edge services, digital twin vulnerability detection, and healthcare security architectures, consistently bridging theoretical rigor with real-world infrastructure protection. Analysis of his 2022-2025 publications reveals intense focus on autonomous vehicle security (38% of recent output), including traffic signal control optimization, ramming attack countermeasures, and CARLA-based scenario validation. Digital forensics using AI (20%) and secure manufacturing/edge computing (27%) constitute other major thrusts, demonstrating how formal verification and machine learning converge to solve complex cyber-physical security challenges across transportation, energy, and healthcare domains. His scientific recognition includes: CCI Impact Award (2022) for groundbreaking cyber-physical security contributions Fellowship at the Potomac Institute of Policy Studies for cybersecurity policy leadership Professor Wijesekera has secured substantial research funding through: NIST grants for health record security frameworks (2014-2015) US Department of Transportation projects on wireless frequency mapping for high-speed rail (2013-2014) Cyber Security Research Alliance funding for trust architectures in cyber-physical systems (2014) Commonwealth Cyber Initiative awards for autonomous vehicle security and energy-efficient manufacturing His industry partnerships with Honeywell and NIST ensure practical impact of theoretical research. The Mason Innovation Laboratory under his direction serves as an interdisciplinary hub for cyber-physical security, integrating researchers from computer science, electrical engineering, and policy studies to develop deployable solutions for transportation networks, power grids, and critical infrastructure protection.

Daniele IelminiView profile

Professor

• Non-volatile memory technologies
• Resistive switching memory (RRAM)
• Phase change memory (PCM)
• +5 more

Daniele Ielmini is a Professor at the Department of Electronics, Information and Bioengineering at Politecnico di Milano, Italy, where he leads research in non-volatile memory technologies and neuromorphic computing. He received his Laurea (with merit) and Ph.D. in Nuclear Engineering from Politecnico di Milano in 1995 and 2000, respectively, and has held visiting positions at Intel Corporation (2006), Stanford University (2006), and the University of Illinois at Urbana-Champaign (2010). His research focuses on the modeling and characterization of non-volatile memories, including nanocrystal memory, charge trap memory, phase change memory (PCM), resistive switching memory (RRAM), and spin-transfer torque magnetic memory (STT-MRAM). He has co-edited the book 'Resistive switching – from fundamental redox-processes to device applications' and published over 300 papers with more than 10,000 citations and an H-index of 69 (Scopus, September 2023). Prof. Ielmini's recent publications demonstrate a strong trend toward in-memory computing and neuromorphic applications, with particular emphasis on closed-loop analog computing architectures, reservoir computing with 2D materials, and hardware security implementations using emerging memory technologies. His work bridges fundamental device physics with practical computing applications, especially for energy-efficient AI acceleration. Intel Outstanding Researcher Award (2013) ERC Consolidator Grant (2014) IEEE-EDS Paul Rappaport Award (2015) Fellow of the IEEE Prof. Ielmini leads multiple ERC-funded projects including SHANNON (Secure Hardware with Advanced Nonvolatile memories), NEURO2D (neuromorphic systems based on reservoir computing in MoS2), and ANIMATE (closed-loop in-memory computing). His research group includes post-doctoral researchers, PhD students, and M.Sc. students working on various aspects of emerging memory technologies and their applications. He serves as Associate Editor for IEEE Trans. Nanotechnology and Semiconductor Science and Technology (IOP), and has served in several Technical Subcommittees of international conferences including IEEE-IEDM, IEEE-IRPS, and IEEE-ISCAS. His laboratory at Politecnico di Milano is equipped with advanced semiconductor device testing equipment including probe-stations, semiconductor parameter analyzers, high-speed waveform generators, and other specialized instruments for nano-electronic research. The lab collaborates with major semiconductor companies including Micron Technology Inc. and STMicroelectronics, as well as participating in national and international research projects.

Jeffrey GuastoView profile

Associate Professor

• Biophysics
• Soft Matter Physics
• Microscale Fluid Mechanics
• +5 more

Jeffrey Guasto , Associate Professor at Tufts University, holds joint appointments in the School of Engineering (Mechanical Engineering) and School of Arts and Sciences (Physics & Astronomy). His work bridges engineering, physics, and biology to study transport properties in complex systems. Ph.D., Engineering (2009), Brown University Sc.M., Engineering (2004), Brown University Dual B.S. in Physics and Mechanical Engineering (2003), Lehigh University Research Interests focus on: Biophysics : Flagellar mechanics, chemotaxis, cell-fluid interactions Soft Matter : Active suspensions, colloids, viscoelastic materials Microfluidics : Device design for cell motility studies and gradient generation Environmental Transport : Microbial ecology in porous systems Scientific Trends from his 77+ publications show emphasis on microscale fluid dynamics, bacterial transport mechanisms, and viscoelastic flow instabilities. His 2024 Nature Microbiology work reveals phage-infected bacteria driving marine chemotaxis, while 2023 PNAS research explores stress topology in viscoelastic flows. Scientific Awards : NSF CAREER Award (2016) for cell dispersal mechanisms Collaborative NSF grants (2015-2023) Advising includes mentoring 15+ students and postdocs. His grants portfolio features 9+ awards, notably NSF grants for viral-microbe interactions (2018) and flagellar mechanics (2020). Labs & Teams : Leads the Guasto Laboratory at Tufts, integrating microfluidics and high-speed imaging for studying microbial transport, while collaborating with MIT, Harvard, and international institutions.

Wade SmithView profile

Senior Lecturer

• Dynamics, vibration and vibration control
• Signal processing
• Modelling and simulation
• +7 more

Dr. Wade Smith is a Senior Lecturer within the School of Mechanical and Manufacturing Engineering at the University of New South Wales. He is an active member of the WAVES research group (Wear, Aeroacoustics and Vibration in Engineering Systems) and conducts his research in the Tribology and Machine Condition Monitoring laboratory. His primary research interests include vibration-based diagnostics of rotating machinery, prognostics of rotating machinery, gear wear monitoring and prediction, simulation and modeling of rotating machines for diagnostic applications, and signal processing of machine vibration signatures using cyclostationarity. His work has significant applications in industrial machinery health monitoring and predictive maintenance systems. Dr. Smith's recent publications demonstrate a consistent focus on advanced diagnostic techniques for rotating machinery, with particular emphasis on gear systems and bearings. His research integrates traditional mechanical engineering principles with modern signal processing and machine learning approaches to develop more effective condition monitoring solutions. He actively supervises PhD and Masters students on projects related to gear diagnostics, wear monitoring, and vibration analysis. His current research projects include gear diagnostics in planetary gearboxes using internal sensors, gear wear monitoring and prediction, sliding contact-induced vibration studies, and transmission-error-based gear diagnostics. Dr. Smith's laboratory is equipped with specialized facilities including gearbox test rigs (both planetary and parallel configurations), a rolling element bearing test rig, an engine test rig, friction rig, tribometer, high-quality microscope, and extensive instrumentation for vibration analysis. His research has attracted collaborations with institutions including Queensland University of Technology, SpectraQuest (USA), Weir Minerals, University of Technology Sydney, RWTH Aachen University (Germany), and Safran.

Alastair KeyView profile

Research Fellow

• Paleolithic Archaeology
• Stone Tool Technology
• Hominin Behavior
• +3 more

Dr. Alastair Key serves as Director of Studies in Archaeology and Official Fellow in Archaeology at Queens' College, University of Cambridge. His research bridges Paleolithic archaeology, stone tool technology, and hominin behavioral evolution through experimental and computational approaches. Director of Studies and Official Fellow at Queens' College, Cambridge Specializes in Paleolithic stone tool analysis, Acheulean technology, and hominin adaptation Conducts experimental archaeology and computational modelling to assess tool functionality Key's research focuses on Acheulean handaxe production , lithic microwear patterns , and ergonomic constraints in prehistoric tool use . He has extensively published on topics including glacial-stage hominin occupations , Oldowan toolmakers , and machine learning applications to archaeological analysis . His recent publications (2025-2023) span diverse subfields: Acheulean chronology , hominin tool use biomechanics , experimental projectile testing , and computational morphometric methods . The work often integrates multidisciplinary datasets and open-source analytical tools to address fundamental questions about human technological evolution. Current research directions include stone tool sharpness quantification , handaxe social signaling potential , and cross-species tool use comparisons through primate studies.

John D. CresslerView profile

Professor

• Silicon-Germanium Heterojunction Bipolar Transistors (SiGe HBT)
• Mixed-Signal Semiconductor Devices
• RF and Microwave Circuit Design
• +5 more

Professor John D. Cressler is a tenured faculty member at the Georgia Institute of Technology, holding a position within the School of Electrical and Computer Engineering in the College of Engineering. His research focuses on cutting-edge semiconductor technologies, particularly silicon-germanium heterojunction bipolar transistors (SiGe HBTs) for mixed-signal applications spanning RF, microwave, mm-wave, analog, and digital domains. His research interests center on atomic-scale bandgap engineering for next-generation semiconductor devices, with emphasis on SiGe HBT technology development, radiation-hardened circuits for space applications, cryogenic electronics, and device-circuit interactions. His team explores fundamental device theory, broadband noise analysis, profile optimization, 2-D/3-D simulation, compact modeling, and radiation effects. Current projects include Europa-surface mission electronics, D-band/sub-THz systems, and radiation-tolerant receiver designs. Analysis of his 15 most recent publications (2024-2025) reveals a dominant focus on radiation-hardened electronics for space applications (40% of works), millimeter-wave circuit design (30%), and SiGe HBT reliability optimization (30%). Key trends include Europa mission electronics development, D-band/sub-THz circuit innovation, and advanced radiation mitigation techniques using SiGe BiCMOS technology. Professor Cressler teaches multiple courses including ECE 3040 (Microelectronic Circuits), ECE 3450 (Semiconductor Devices), ECE 6444 (Silicon-Based Heterostructure Devices and Circuits), and the interdisciplinary IAC 2002 course on Science, Engineering and Religion. His research is supported by industrial collaborations and Georgia Tech facilities including the Georgia Electronic Design Center (GEDC), NanoTECH, and C-STAR.

• Machine Learning in Electronics
• Electrostatic Discharge (ESD) Protection
• Circuit Reliability
• +3 more

Elyse Rosenbaum is the Melvin and Anne Louise Hassebrock Professor in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. She also serves as the Acting Associate Dean for Research at the Grainger College of Engineering. She is the director of the NSF-supported Center for Advanced Electronics through Machine Learning (CAEML), a collaboration between the University of Illinois, North Carolina State University, and Penn State University. Education: Ph.D. in Electrical Engineering, University of California, Berkeley, 1992 M.S. in Electrical Engineering, Stanford University B.S. in Electrical Engineering, Cornell University (with distinction) Research Interests: Her research focuses on machine learning applications in electronics, ESD-robust high-speed I/O circuit design, compact modeling, behavioral modeling of circuits, and CDM-ESD protection for advanced packaging technologies. Scientific Awards: IEEE Fellow for contributions to electrostatic discharge reliability of integrated circuits Best Student Paper Award, IEDM Outstanding and Best Paper Awards, EOS/ESD Symposium Technical Excellence Award, SRC NSF CAREER Award IBM Faculty Award ESD Association’s Industry Pioneer Recognition Award Advising and Grants: She supervises graduate and undergraduate researchers, primarily focusing on those with strong academic records and relevant experience. Her work is supported by NSF and other prominent organizations. Labs and Teams: She leads the CAEML center, which aims to apply machine learning to optimize microelectronic circuits and systems, enhancing design automation and reliability.

Robert M. Weikle, IIView profile

Professor

• Millimeter-wave electronics
• Terahertz technology
• Applied electromagnetics
• +9 more

Robert M. Weikle, II is a Professor in the Charles L. Brown Department of Electrical and Computer Engineering at the University of Virginia, with a courtesy appointment in the Department of Physics. He earned his B.S. from Rice University (1986), M.S. (1987), and Ph.D. (1992) in Electrical Engineering from Caltech, followed by postdoctoral work at Chalmers University of Technology (1992). His research focuses on millimeter-wave and terahertz electronics , applied electromagnetics, integrated antennas, low-noise sensors, and heterogeneous integration of compound semiconductors. His work bridges electronics and photonics for spectrum access, with applications in astronomy, spectroscopy, and metrology. He has published extensively on micromachined silicon substrates, superconducting materials, and emerging technologies. Scientific Awards: IEEE Microwave Prize (1993) David A. Harrison III Award (1999) University of Virginia All-University Outstanding Teaching Award (2000) Edlich-Henderson Innovator of the Year (2016) Fulbright Scholar (2001) As Chief Technology Officer and co-founder of Dominion Microprobes, Inc., he commercializes micromachined wafer probes for high-frequency metrology. His lab, located in E220 Thornton Hall and the Jesse W. Beams Physics Building, has produced 15+ recent publications on submillimeter-wave devices, THz probes, and calibration techniques.

YING-TSONG LINView profile

Professor

• Applied Ocean Sciences
• Autonomous Ocean Platforms
• Internal Waves and Ocean Mixing
• +3 more

YING-TSONG LIN is an Acting Professor at the Scripps Institution of Oceanography (SIO), UC San Diego. His research focuses on applied ocean sciences, autonomous ocean platforms, internal waves, ocean acoustics, and instrumentation. He leads projects like the New England Shelf Break Acoustics (NESBA) experiment, emphasizing real-time acoustic modeling and environmental interactions. Research interests include 3D acoustic propagation modeling, ocean mixing dynamics, and seabed characterization. His work integrates high-performance computing and distributed sensor networks for oceanographic studies. Recent studies address underwater explosions, renewable energy impacts, and vessel localization using acoustic coherence. Publications emphasize advancements in hydroacoustic modeling, seabed inversion techniques, and environmental asymmetry effects. His contributions span interdisciplinary areas like bioacoustics and seismic-to-acoustic wave conversions. Labs/Teams: Involved with SIO's Acoustics and Oceanography research groups, focusing on autonomous platforms and global observing systems.

Danial ChitnisView profile

Lecturer

• Microelectronics
• Biomedical Engineering
• Quantum Technology
• +3 more

Dr. Danial Chitnis is a Chancellor's Fellow and Lecturer in Electronics at the School of Engineering, University of Edinburgh. He holds a DPhil in Engineering Science from the University of Oxford (2013) and has expertise in microelectronics, biomedical engineering, and quantum imaging. His research focuses on SPAD arrays, time-of-flight sensors, and wearable optical systems for biomedical applications. Education: BSc in Electronics Engineering, Chamran University of Ahvaz (2002–2007) MSc in Advanced Microelectronics Systems Engineering, University of Bristol (2007–2008) DPhil in Engineering Science, University of Oxford (2009–2013) Research Interests: Single-Photon Avalanche Diode (SPAD) arrays for optical communications and biomedical imaging Quantum-enhanced imaging via QuantIC Hub Wearable sensors for near-infrared spectroscopy (NIRS) AI-driven automation in test and measurement systems Articles Trends: Recent work emphasizes AI integration in electronics design, photon-counting receivers for 6G networks, and portable biomedical devices. Notable contributions include SYCL-based acceleration of circuit simulations and FPGA-driven time-to-digital converters. Grants & Collaborations: Principal Investigator of multiple grants, including EPSRC-funded projects on AI-enhanced human-machine interfaces and quantum technology applications. Collaborates with UCL, QuantIC, and industry partners like Keysight Technologies. Labs/Teams: Co-investigator at QuantIC, the UK Quantum Technology Hub in Quantum Enhanced Imaging. Leads interdisciplinary research on detector arrays and systems for quantum physics and consumer cameras.