Nicholas Antipa is an Assistant Professor at the University of California San Diego's Jacobs School of Engineering, in the Electrical and Computer Engineering department. His research focuses on the co-design of optical systems and algorithms to develop advanced computational imaging systems, leveraging innovations in 3D printing, sensors, machine learning, and AI. He holds a PhD in Computational Imaging from UC Berkeley and previously worked at the Lawrence Livermore National Lab on optical metrology for the National Ignition Facility. His work includes pioneering projects like the DiffuserCam and Miniscope3D, which enable high-dimensional optical signal capture and 3D microscopy. Education: PhD in Computational Imaging, UC Berkeley (2020) MS in Optics, University of Rochester Institute of Optics BS in Optical Science and Engineering, UC Davis Research Interests: Computational imaging systems, single-shot high-dimensional optical capture, lensless imaging, and applications in neuroscience and marine science. His lab explores novel optical designs, compressed sensing, and AI-driven imaging techniques to push the boundaries of conventional systems. Scientific Awards: Best Paper at ICCP 2019, 2016 Best Demo at ICCP 2017 No. 2 in Optica 15 Top-Cited Articles (2020) Affiliations: Director of the Computational Imaging Systems Lab at UCSD. Collaborates with institutions like Lawrence Livermore National Lab and the Scripps Institution of Oceanography for projects in marine sediment mapping and underwater object detection. His lab emphasizes open-source tools, such as the DiffuserCam Raspberry Pi tutorial.
California Institute of Technology (Caltech)United States
Harry Atwater is the Howard Hughes Professor of Applied Physics and Materials Science at the California Institute of Technology (Caltech). He serves as Director of the Joint Center for Artificial Photosynthesis (JCAP) and previously led the Light-Materials Interactions in Energy Conversion (LMI-EFRC) from 2009–2014. His research bridges photovoltaics, solar energy systems, plasmonics, and nanophotonics. Atwater pioneered the field of plasmonics and co-founded Alta Devices, a leader in GaAs photovoltaic technology. He holds over 200 publications and has been recognized with prestigious awards, including induction into the National Academy of Engineering (2015) and the ENI Prize (2012). His work spans cutting-edge innovations such as silicon wire array solar cells, metasurface technologies for optical manipulation, and space solar power systems. Current projects include developing lightsail propulsion for interstellar exploration and photothermocatalytic reactors for sustainable fuels. Atwater’s lab focuses on the intersection of nanophotonics and energy, exploring quantum emitters, carbon capture, and optomechanical systems. Research Highlights: Plasmonic light absorbers, metasurface-based imaging, and solar energy harvesting systems. Key Projects: Lightsail experiments, space-based solar power missions, and CO₂ reduction via electrochemical methods. Awards: Julius Springer Prize (2014), ISI Highly Cited Researcher (2014), and MRS Kavli Lecturer (2010).
Vivek Boominathan is an Assistant Research Professor in the Department of Electrical and Computer Engineering at Rice University. He is affiliated with the GLEE lab (Geometry, Light, & Imaging lab). His research focuses on computational imaging, combining computer vision, machine learning, applied optics, and nanofabrication to develop innovative imaging systems for applications such as robotics, medical sensing, and virtual/augmented reality. He has contributed to projects like PhlatCam (a lensless camera) and NeuWS (neural wavefront shaping). His work bridges optics, algorithms, and materials science to overcome traditional limitations in imaging systems. Boominathan's research interests include lensless imaging, optical meta-devices, turbulence mitigation, and bio-inspired imaging systems. He has developed systems like Foveated thermal imaging prototypes and real-time lensless microscopes. His lab emphasizes interdisciplinary approaches, integrating hardware design with machine learning. Key projects include: NeuWS: Neural wavefront shaping for imaging through scattering media CoIR: Compressive implicit radar for sensing applications FlatCam and PhlatCam: Ultra-thin lensless imaging devices Bioluminescence imaging in marine species His work has been published in top venues like Science Advances, Optica, and IEEE TPAMI. He collaborates with institutions like NASA JPL and industry partners on applied imaging solutions. Current research trends emphasize sensor-algorithm co-design and high-speed imaging systems for AR/VR applications. Boominathan holds a PhD in Electrical Engineering and has extensive postdoctoral experience in computational imaging. He advises projects in the GLEE lab and mentors students in hardware-software co-design for imaging systems. His lab focuses on translating theoretical innovations into practical devices with commercial potential.
Dr. Ben Mills is a Principal Research Fellow at the University of Southampton. His research focuses on the integration of deep learning with laser technologies, including applications in environmental monitoring, materials science, and biomedical imaging. He is a core member of the Smart Lasers and Special Fibres research group and leads projects such as Hearing Light and Lasers that Learn , funded by the EPSRC. His work spans laser beam shaping, material transfer, and diagnostic techniques using AI-driven photonics. Research Interests: Laser-material interactions Deep learning for optical systems Environmental sensing via lasers Biophotonics applications Additive/subtractive manufacturing Publications (2023–2025) highlight innovations in laser cleaning, beam optimization, and pollen imaging using low-cost hardware. His work bridges fundamental optics with applied machine learning solutions. External Contributions: Speaker at international conferences on AI in photonics (2019–2021) Keynote on predictive laser materials processing (2019) Presenter at invited sessions on particle sensing via deep learning (2020) Current Supervision: PhD students Luke Burke (Physics), Fedor Chernikov (ORC), and Yuchen Liu (ORC) work on laser beam control and environmental applications.
Swiss Federal Institute of Technology in LausanneSwitzerland
Paolo Prandoni is a Lecturer at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences (IC). He serves as a Scientist in the Audiovisual Communications Laboratory (LCAV) and teaches in the SSC-ENS and SIN-ENS units, focusing on signal processing theory and practical applications in audiovisual communications. He earned his PhD from EPFL after completing all prior education there, driven by childhood fascination with long-distance telephony. His doctoral work established foundations in communication systems that continue to inform his research. Prandoni's research spans audio/image processing, machine learning for media analysis, and DSP education. Key areas include computational photography (e.g., spectral imaging, stained glass rendering), speech quality assessment via transfer learning, music information retrieval (e.g., fingering prediction), and audience analytics through his company Quividi. His work consistently bridges theoretical signal processing with real-world implementation. Recent publications reveal a strategic shift toward machine learning integration in signal processing tasks, particularly non-intrusive speech assessment and lensless imaging reconstruction. Simultaneously, he advances DSP pedagogy through MOOC development and hands-on teaching tools using off-the-shelf hardware, emphasizing accessibility and practical skill development. No scientific awards are documented in the provided materials. He has advised PhD student Thanikachalam Niranjan (thesis: Image Based Relighting of Cultural Artifacts , 2016) and teaches Communication Systems and Computer Science courses. His educational impact extends through the open-access textbook Signal Processing for Communications (2008) and tools like MultiPub for maintainable online classes. Industry engagement includes Quividi co-founding (2006) and ongoing CSO role in attention analytics. As a core LCAV laboratory member, he collaborates on interdisciplinary projects including cultural heritage digitization, embedded signal processing systems, and real-time audience measurement, leveraging EPFL's infrastructure for both academic and commercial applications.
Heidi Ottevaere is a Professor at the Faculty of Engineering of the Vrije Universiteit Brussel (VUB) since October 1, 2009. She serves as the head of the Instrumentation and Metrology platform at the Photonics Innovation Center and leads the 'biophotonics' research unit of the Brussels Photonics Team (B-PHOT), which is chaired by Prof. Hugo Thienpont. Her work focuses on the design, fabrication, and characterization of photonic components and systems for diverse applications in medical diagnostics, environmental monitoring, and industrial processes. Dr. Ottevaere earned her Electrotechnical Engineering degree with majors in Photonics from Vrije Universiteit Brussel in 1997 and completed her PhD in Applied Sciences at the same institution in 2003. Her doctoral research focused on 'Refractive microlenses and micro-optical structures for multi-parameter sensing: a touch of micro-photonics.' Professor Ottevaere's research spans multiple cutting-edge areas of photonics with particular emphasis on biophotonics, micro-optics, and optical metrology . Her work bridges fundamental science with practical applications, developing novel photonic components and systems that address real-world challenges. She has pioneered research in miniaturized optical systems for medical diagnostics, environmental monitoring, and industrial applications. Her current research focuses on advancing lab-on-a-chip technologies, microfluidic optical sensors, and novel optical fiber systems for biomedical applications. She has developed microminiaturized, integrated plastic detection units for absorbance and laser-induced fluorescence measurements in microfluidic channels, enabling portable, robust, and disposable diagnostic systems. Her recent publications demonstrate a strong trend toward integrated optical sensing systems with applications in medical diagnostics and environmental monitoring. There's a clear progression from fundamental optical component design to complete system integration, with increasing emphasis on artificial intelligence for data analysis and computational imaging techniques. Her work bridges photonics with biomedical engineering, materials science, and data science, reflecting the interdisciplinary nature of modern photonics research. Dr. Ottevaere has been recognized with several prestigious awards: Best Application award (2008) Educational award - Bronze (2019) MOC09 Contribution Award Winners (2009) As an educator and mentor, Professor Ottevaere has promoted 9 PhD students and supervised numerous master's theses. She has secured substantial research funding from diverse sources including the Fund for Scientific Research Flanders (FWO), the Institute for the Promotion of Innovation by Science and Technology in Flanders (IWT), and multiple European Framework Programs. Her current portfolio includes projects on miniaturized biosensors for drinking water screening, precision manufacturing, and photonics education initiatives in Uzbekistan. She has coordinated multiple strategic research and networking projects with regional, national, and international funding bodies. Professor Ottevaere leads the biophotonics research unit within the Brussels Photonics Team (B-PHOT), one of Europe's leading photonics research groups. Her team includes researchers working on optical metrology, micro-optics fabrication, and biophotonic applications. She collaborates extensively with industry partners including Melexis, Umicore, and Anteryon, as well as academic institutions across Europe through various EU-funded projects. She has been instrumental in developing the interuniversity engineering curriculum 'Master in Photonics' which received the EC Erasmus Mundus quality label in 2006, and continues to be the driving force behind photonics education at VUB.
Christine Keating is the Shapiro Professor of Chemistry at Pennsylvania State University's Department of Chemistry. She is affiliated with the Huck Institutes for the Life Sciences and the Materials Research Institute, and serves on the graduate faculty of the Bioengineering Department. Her research focuses on self-assembled artificial cells, prebiotic compartmentalization, bioinspired materials synthesis, and particle assembly. Her work bridges physical chemistry, colloid science, and biological chemistry. Education: B.S. in Biology and Chemistry from Saint Francis College (1991), Ph.D. in Chemistry from Penn State (1997). Research Themes: Artificial cells and cytomimetic chemistry Prebiotic compartmentalization via coacervation Bioinspired materials using phase-separated microenvironments Optical applications of reconfigurable particle assemblies Awards: Over 20 honors including the Langmuir Lectureship (2024), AAAS Fellowship (2014), and NSF CAREER Award (2003-2008). Grants: Active funding includes projects on protocells and Rules of Life collaboration through NSF. Advises graduate students in interdisciplinary programs. Labs: Leads the Keating Group and participates in the ProteoCell Project, a six-university NSF initiative.
Nick Antipa is an Assistant Professor at the University of California, San Diego, affiliated with the Jacobs School of Engineering and the Department of Electrical and Computer Engineering. His work focuses on computational imaging systems that integrate optics, sensors, and algorithms to enable novel imaging modalities. PhD in Electrical Engineering from UC Berkeley Former optical metrology engineer at Lawrence Livermore National Lab Research interests span computational imaging , lensless camera design , and single-shot high-dimensional optical signal capture . His lab develops systems like DiffuserCam for compressive 3D imaging and Miniscope3D for miniature fluorescence microscopy. Recent publications address differentiable wave optics, high-speed video reconstruction, and marine imaging applications. Awards include Best Paper at ICCP 2016/2019 and Best Demo at ICCP 2017. His lab explores machine learning-driven optical design and differentiable rendering frameworks for end-to-end optimization of imaging systems. Current projects include oceanographic imaging, computational photography, and infrared spectroscopy acceleration.
Professor Andrew Maiden is a faculty member at the University of Sheffield's School of Electrical and Electronic Engineering, specializing in Computational Imaging. He leads the Semiconductor Materials and Devices Research Group. His research focuses on advancing optical systems through computational methods like ptychography, which enhances microscopy and imaging precision. With a PhD from Durham University (2005) and an MEng from the University of Birmingham (2001), Maiden's career includes pioneering work with Professor John Rodenburg on ptychography and a brief industry stint commercializing microscopy technologies. He teaches Digital Signal Processing (DSP) to third-year students and advises researchers such as Cao S (PhD graduate). Research interests include Coherent Diffractive Imaging (CDI), electron microscopy phase imaging, and inverse problem solutions. His work bridges computational algorithms with practical applications in optics and materials science. Maiden has contributed to over 50 peer-reviewed publications and holds patents on ptychography-related imaging techniques. His lab focuses on developing high-resolution imaging tools without traditional lenses, emphasizing low-dose radiation and high-throughput bio-imaging. Teaching and mentorship play key roles in his academic contributions, shaping future engineers in signal processing and computational methods. Collaborations span academia and industry, reflecting his dual focus on innovation and real-world application.
Professor Michalis Zervas serves as Professor of Optical Communications at the University of Southampton's Optoelectronics Research Centre (ORC), leading pioneering research in photonics and laser technologies. His work integrates advanced optical systems with artificial intelligence to solve complex challenges in telecommunications, manufacturing, and medical diagnostics through major collaborations with industry and international research bodies. His primary research spans Optical Communications, Photonics, and Fibre Lasers, with specialized focus on deep learning applications for laser control optimization, coherent beam combination, and optical fibre sensor development. Current investigations include high-power photonics systems for industrial manufacturing and novel laser-based biomedical diagnostic platforms that bridge physics with healthcare innovation. Recent publications (2025) reveal a decisive trend toward AI-photonic integration, where deep learning algorithms enhance precision in laser-material interactions across diverse applications—from microbead cleaning and paint analysis to psoriasis treatment simulation and diatom imaging. This interdisciplinary approach demonstrates consistent methodological innovation in merging computational intelligence with fundamental laser physics. Supervises 6 PhD students including Rosemary Catriona Clark and Fedor Chernikov in ORC's photonics programs Secures major funding from EPSRC (Smart Fibre-Optic High Power Photonics, Hearing Light) and US Air Force Office of Scientific Research Leads collaborative projects with Professor Sir David Payne and Professor Johan Nilsson across national manufacturing hubs As co-leader of the Smart Lasers and Special Fibres research group within the Advanced Laser Laboratory, Zervas drives experimental photonics innovation through state-of-the-art fibre laser systems and optical resonator technologies. His team maintains strategic partnerships with global industry leaders in photonics manufacturing and medical device development.
Dr James A. Grant-Jacob is a Senior Research Fellow at the Optoelectronics Research Centre (ORC) , University of Southampton. His work spans high harmonic generation, phase retrieval, laser fabrication, and artificial intelligence applications in photonics. PhD (2011): Table-Top XUV Nanoscope , University of Southampton MSc in Physics: Strings and branes in exotic space-times His research integrates deep learning with laser-based processes for applications in medical imaging, environmental monitoring, and manufacturing . Recent projects include Lasers that Learn and PhototheRapy Enabled Via Artificially-Intelligent Lasers (PREVAIL) . Key article trends include AI-driven laser optimization (2025: 8/10 papers), biomedical applications (psoriasis treatment, pollen sensing), and low-cost optical systems (Raspberry Pi-based imaging). Collaborations with NVIDIA, Dyson, and Southampton General Hospital highlight his translational focus. Students mentored include: Fedor Chernikov (PhD ORC) Yuchen Liu (PhD ORC) Grants from NVIDIA and projects like Beam-shaping for laser-based manufacturing underscore his innovation in smart lasers . Active in the Smart Lasers and Special Fibres research group, he continues advancing interdisciplinary laser technologies.
Professor David McGloin is a Personal Chair and Head of School at the School of Natural and Computing Sciences, University of Aberdeen, a position he has held since September 2022. He is actively involved in research, teaching, and leadership, supervising PhD students and developing new courses in optics. His academic journey includes faculty roles at the University of Dundee and the University of Technology Sydney, where he served as Director of Research Programs in the Faculty of Engineering and IT. MSci (Hons) in Laser Physics and Optoelectronics, University of St. Andrews (1997) PhD in Physics, University of St. Andrews (2001) David McGloin's research centers on optics, particularly optical trapping, beam shaping, and their applications in biomedical and environmental sciences, including aerosol analysis and biophotonics. He also explores THz beam shaping and microfluidics. His work bridges physics, engineering, and life sciences, with a strong emphasis on experimental and computational photonics. His recent publications reveal a consistent focus on optical manipulation techniques, especially using Bessel beams and holographic methods, with applications in aerosol dynamics, single-pixel imaging, and biomedical force measurements. The trend shows increasing interdisciplinary collaboration, integrating optics with immunology, environmental science, and advanced manufacturing. Royal Society University Research Fellowship (2003) McGloin has supervised numerous PhD and postgraduate students and has led major research initiatives across institutions. His leadership roles include Head of Physics and Associate Dean for Research at Dundee, and Director of Research Programs at UTS. He has secured significant research funding, though specific grants are not detailed in the text. He is currently accepting PhD students in physics, particularly in experimental or computational optics and photonics. He is a member of professional bodies including the Institute of Physics (MInstP), Senior Member of Optica, and Chartered Physicist (CPhys). His research group focuses on developing novel optical tools for scientific and industrial applications, with strong ties to interdisciplinary teams in biophysics and environmental monitoring.
Indian Institute of Technology Hyderabad (IITH)India
Renu John is a Professor in the Department of Biomedical Engineering at Indian Institute of Technology Hyderabad . He earned his Ph.D. in Physics (Optics) from IIT Delhi in 2006 and has held postdoctoral positions at Duke University and University of Illinois . He leads the Medical Optics and Sensors Laboratory (MOS) and co-founded the Center for Healthcare Entrepreneurship (CfHE) , focusing on affordable healthcare solutions for India. Research Interests : Biomedical Imaging, Optical Coherence Tomography (OCT), Digital Holography, AI/ML in Diagnostics, Microfluidic Biosensors, 3D Bioprinting, Nanoparticle-based Imaging, Optical Elastography. Awards : Best Paper & Poster Awards at international conferences (2018-2019), Samsung Innovation Award (2018) for smartphone-based oral cancer detection. Grants : Lead investigator for an ICMR Center of Excellence (15.2 Cr funding) in Medical Devices and Diagnostics. Students : Mentored over 20 researchers, including current and alumni Ph.D. candidates working on OCT, microfluidics, AI-driven imaging, and biosensor development. Labs & Innovations : The MOS Lab develops cutting-edge technologies like lensless microscopes, FF-OCT systems, and dual-modality biosensors. His team has filed 18 patents and published 117 international journal articles, with projects spanning from in vivo magnetomotive imaging to organ-on-chip platforms for disease modeling.
Assoc. Professor Jun Tong is affiliated with the School of Electrical, Computer and Telecommunications Engineering at the University of Wollongong. He holds a PhD from City University of Hong Kong and specializes in signal processing for communication systems and instrumentation, focusing on robust, low-complexity algorithms for high-dimensional signals and imperfect models. His research enhances spectrum/energy efficiency in challenging environments. Research Interests: Signal processing applications in communication systems, MIMO and 5G/6G technologies, optical systems, machine learning for signal processing, and sensor networks. He has published extensively in top-tier journals like IEEE Transactions and conferences such as ICC and MWP. Teaching & Supervision: Teaches Digital Signal Processing, Engineering Electromagnetics, and Digital Hardware. Supervises PhD/Master’s projects on topics like 6G wireless communication, MIMO systems, and light-field imaging. Current students are researching areas such as ODDM modulation and sub-THz communications. Funding & Grants: Secured grants including the Advancement and Equity Grants Scheme for Research (AEGiS) for multi-modal defect detection in manufacturing. Previously led projects on UOW-UESTC collaborations. Service & Leadership: Member of the IEEE. Actively involved in academic leadership and curriculum development within his school.
Iacopo Mochi is a Group Leader for Advanced Lithography and Metrology and beamline scientist at the Paul Scherrer Institute (PSI), specifically working at the Laboratory for X-ray Nanoscience and Technologies within the PSI Center for Photon Science. He has extensive experience in EUV lithography, X-ray optics, and semiconductor metrology, with a career spanning multiple prestigious research institutions including Lawrence Berkeley National Laboratory and imec. Dr. Mochi received his physics degree from the University of Florence and earned a PhD in Methods and Technologies for Environmental Monitoring. His career path has included significant contributions to LIDAR systems, astrophysical instrumentation, and ultimately EUV technologies for semiconductor manufacturing. At PSI since 2016, he has established himself as a leading researcher in advanced lithography techniques. His primary research focuses on the development of EUV instrumentation for semiconductor metrology, particularly the XIL-II metrology end station - a lensless microscope dedicated to EUV photomask inspection. His work spans nano-imaging, interferometry techniques in the X-Ray spectrum, and the characterization of advanced materials for semiconductor manufacturing. Dr. Mochi has made significant contributions to the field through the development of RESCAN, an actinic pattern inspection platform based on coherent diffraction imaging. Analysis of his publication record reveals a strong trajectory of innovation in EUV lithography, with recent work pushing resolution limits to 5 nm, developing novel metrology techniques, and applying machine learning approaches to improve image reconstruction and defect detection. His research directly addresses critical challenges in semiconductor manufacturing as the industry moves toward smaller technology nodes. Dr. Mochi's scientific contributions include groundbreaking work on EUV pellicles for mask protection, characterization of absorber and phase defects on EUV reticles, and advancements in interference lithography techniques. His collaborative research demonstrates strong partnerships with industry and academic institutions worldwide. As the beamline scientist for the XIL-II beamline, Dr. Mochi coordinates and supervises experiments that support cutting-edge research in semiconductor manufacturing and nanotechnology. His leadership extends to mentoring junior researchers and contributing to the development of next-generation scientists in the field of advanced lithography.
