Daniel Sage is a Lecturer and Scientific Advisor at École polytechnique fédérale de Lausanne (EPFL) , affiliated with the Biomedical Imaging Laboratory (LIB) under the College of Engineering (STI) and School of Life Sciences (SV) . He specializes in bioimage informatics , structured-illumination microscopy , and deep learning applications for biomedical imaging. His work spans algorithm development for single-molecule localization microscopy (SMLM) , fluorescence imaging , and 3D reconstruction . His research group has developed open-source tools like FlexSIM for light inhomogeneity correction, DeepImageJ for integrating deep learning in ImageJ, and Steer'n'Detect for orientation-accurate template detection. His publications focus on correcting multiple-blinking artifacts in PALM, optimal transport metrics for SMLM evaluation, and contextual feature analysis for xenograft cell classification. He mentors PhD students and contributes to interdisciplinary education through courses such as Bioimage Informatics and Fundamentals of Image Analysis , emphasizing practical software solutions and Java programming for bioimage processing. His collaborations include institutions like Howard Hughes Medical Institute and Centre National de la Recherche Scientifique (CNRS) .
Paras N. Prasad is a SUNY Distinguished Professor with joint appointments in Physics, Chemistry, Medicine, and Electrical Engineering at the University at Buffalo. He serves as Executive Director of the Institute for Lasers, Photonics and Biophotonics (ILPB), which he founded in 1999. Dr. Prasad holds the Samuel P. Capen Chair of Chemistry and has pioneered interdisciplinary research at the interface of photonics, nanotechnology, and biomedicine. Education: BSc, Bihar University, India (1964) MSc, Bihar University, India (1966) PhD, University of Pennsylvania (1971) Postdoctoral Fellow, University of Michigan (1971-74) Research Focus: Dr. Prasad's multidisciplinary research spans photonics, nanophotonics, and biophotonics, with emphasis on nonlinear optical processes in nanostructured materials. His work develops photonic technologies for information processing, medical imaging, and cancer therapy through nanoparticle-based drug delivery systems and diagnostic platforms. The ILPB laboratory features state-of-the-art instrumentation for advanced optical research. Publication Trends: Recent articles demonstrate strong focus on nanomedicine applications, particularly cancer theranostics using functional nanoparticles. Key themes include drug delivery systems, chiral photonic materials, bioimaging technologies, and nanoparticle synthesis techniques. The research consistently bridges fundamental materials science with translational medical applications. Honors and Awards: SPIE Gold Medal (2016) IEEE Photonics Society William Streifer Award (2021) American Chemical Society Peter Debye Award (2018) OSA Michael Feld Biophotonics Award (2017) IEEE Pioneer Award in Nanotechnology (2017) Fellow of National Academy of Inventors (2016) Guggenheim Fellowship (1997) Leadership: As ILPB Executive Director, Dr. Prasad leads multidisciplinary teams developing photonic technologies with applications in healthcare, energy, and communications. His research has generated nine spin-off companies, including Nanobiotix currently in advanced cancer therapy trials.
Ueli Grossniklaus is an Ordinary Professor at the University of Zurich within the Faculty of Mathematical and Natural Sciences , affiliated with the Department of Plant and Microbiology . His work focuses on plant developmental biology, particularly epigenetic and genetic mechanisms governing reproduction and adaptation. Key Courses: Epigenetics, Plant Biology Workshop, Group Seminars on Current Research Laboratory Techniques: Advanced methods in plant cell mechanics, transcriptomics, and genome editing Research Interests span plant epigenetics, reproductive biology, and the interplay between environmental stress and genetic regulation. He investigates: Mechanistic control of gametogenesis and fertilization Epigenetic contributions to plant adaptation Evolutionary implications of asexual reproduction Biophysical forces in plant cell growth Publication Trends (2025–2018) reveal expertise in: Arabidopsis and fern model systems Epigenetic regulation (DNA methylation, histone dynamics) Apomixis and hybrid seed failure mechanisms Biomechanics of pollen tubes and carnivorous plants Genome editing tools (CRISPR) and long-read sequencing Scientific Collaborations include interdisciplinary projects on: Microfluidic devices for plant cell analysis Gene drive ecology and ethics 3D imaging of plant reproductive structures Advising and Grants focus on mentoring through research internships in developmental biology, genetics, and systems biology. His lab engages in: Epigenetic response to environmental stress Cell wall mechanics in reproduction Computational modeling of plant growth Laboratory Teams integrate plant biologists, bioengineers, and computational scientists to study: Mechanistic gene regulation Evolutionary developmental biology Microrobotics for cellular force measurement
Privatdozent Dr. Andreas Faust is a leading researcher at the European Institute for Molecular Imaging (EIMI) at the University of Münster, where he heads the Chemical Targeting Lab. His work focuses on developing innovative imaging agents for medical diagnostics, particularly in radiopharmaceutical chemistry and molecular imaging. He maintains strong affiliations with the Department of Nuclear Medicine at the University Hospital Münster and participates in the "Cells in Motion" excellence cluster, contributing to cutting-edge research at the intersection of chemistry, medicine, and imaging technology. Dr. Faust completed his chemistry studies at the University of Münster, earning his Diploma in 1999, followed by his doctoral degree (Dr. rer. nat.) in 2003 with research on artificial caffeine receptors. His academic journey continued with positions at the Department of Organic Chemistry and the Department of Nuclear Medicine before becoming head of the chemistry group at EIMI in 2011. Dr. Faust's research centers on organic and medicinal chemistry with specialization in radiopharmaceutical chemistry . His team develops novel tracers for diagnostic molecular imaging using positron emission tomography (PET), single-photon emission computed tomography (SPECT), optical imaging, and photoacoustic imaging. A significant portion of his work focuses on creating specific ligands for the alarmins S100A8/S100A9 and bacteria-specific tracers based on complex carbohydrates or siderophores. His research has important applications in inflammation imaging, infection diagnostics, and cancer theranostics, with emphasis on improving metabolic stability and target specificity of imaging agents. His publication record demonstrates consistent contributions to molecular imaging, with recent work emphasizing bacteria-specific PET tracers, inflammation imaging targeting S100 proteins, and novel optical imaging probes. The research shows a clear trajectory toward developing clinically applicable imaging agents with improved specificity and metabolic stability, particularly in the areas of infection diagnostics and inflammation monitoring. 2017: Best Poster Award at Symposium "Molecular Imaging Agents in Medicine," Groningen 2009: Young Investigator Award at Deutscher Röntgenkongress, Berlin 2005: Best Scientific Poster Award at 4th Annual Meeting of the Society of Molecular Imaging, Köln Dr. Faust leads multiple significant research projects, including as Coordinator of a project on immune cell distribution imaging (2019-2024) and as Principal Investigator for CRC-project A03 "Targeting of S100A8/A9 for imaging of inflammatory disorders" and research on vascular graft infections (both 2021-2024). His Chemical Targeting Lab comprises a multidisciplinary team working at the intersection of chemistry, microbiology, and medical imaging, securing substantial funding from the Innovative Medicines Initiative and DFG Collaborative Research Centre. The Chemical Targeting Lab maintains state-of-the-art facilities for chemical synthesis, radiochemistry, and biological testing. The lab collaborates extensively with microbiologists, clinicians, and imaging specialists to translate basic research into clinical applications. Current research directions include optimizing bacterial imaging probes for clinical diagnostics and developing new inflammation-specific tracers for early disease detection, with particular focus on S100A9-targeted imaging and siderophore-based bacterial detection systems.
Dr. Bob Beitle Jr. is a Professor of Chemical Engineering and Senior Associate Vice Chancellor for Research and Innovation at the University of Arkansas. He joined the department in 1993, earned tenure in 1998, and was promoted to Full Professor in 2006. His research spans biochemical engineering , bioseparation , fermentation , and adaptive technology for the disabled , with significant work on protein purification, catalytic nanoparticles, and sustainable bioprocesses. Education: BS, MS, PhD in Chemical Engineering from the University of Pittsburgh (1987, 1991, 1993) Dr. Beitle's research combines experimental and computational approaches, focusing on peptide-directed nanoparticle synthesis and biocatalysis . His recent publications highlight advancements in MOF-based separations , CO2 capture materials , and viral detection platforms . He has secured grants like the CAREER Award and led projects in industrial partnerships and student development . Scientific contributions include multiple patents in bioseparation and software interfaces. Awards span decades: teaching honors (1988–2007) and mentorship recognition . He serves on the Cell and Molecular Biology Program Advisory Committee and the Executive Committee for the Biochemical Technology Division of ACS . Lab initiatives involve genomic data-driven affinity tail design and membrane-assisted fermentation systems .
Thomas Walter is a Professor at Mines ParisTech and Director of the Centre for Computational Biology (CBIO) , a research group affiliated with the Institut Curie and INSERM . His work focuses on applying Machine Learning and Computer Vision to biomedical image analysis, particularly in high-content screening and computational pathology . He also serves as Deputy Director of the Computational Oncology (U1331) unit and leads the Statistical Learning and Modeling of Biological Systems team. PhD in Medical Image Analysis (2003, Mines ParisTech) Postdoctoral work at EMBL (European Molecular Biology Laboratory) Director of CBIO since 2018 Holder of a PRAIRIE Chair (Paris Artificial Intelligence Research Institute) since 2019 Dr. Walter's research bridges biomedical imaging , machine learning , and cancer genomics . Key areas include: Statistical reconstruction of biological networks Prediction of tumor progression at genomic/transcriptomic levels Development of deep learning methods for cell cycle analysis Integration of multi-omics data for precision oncology Tools for spatial transcriptomics (e.g., autoFISH, RNA2seg) Recent publications highlight his work in spatial transcriptomics , immunotherapy outcome prediction , and deep learning for digital pathology . His team has developed open-source tools like FISH-quant and pyHiM for single-molecule RNA imaging analysis. Scientific Honors: PRAIRIE Chair (2019) for AI research in life sciences Dr. Walter actively contributes to teaching deep learning for image analysis in multiple graduate programs across France, including courses at Mines ParisTech , Université Paris-Saclay , and Institut Curie . His software tools (FISH-quant, pyHiM) and methodological frameworks (e.g., Cut-Detector, PointFISH) have become standard resources in bioimage informatics.
Dustin Scheinost is an Associate Professor at Yale School of Medicine, affiliated with the Department of Radiology & Biomedical Imaging, Yale Child Study Center, Department of Statistics, and Yale Biomedical Imaging Institute. His research focuses on connectomics , machine learning , and neuroinformatics through the Multi-modal Imaging, Neuroinformatics, & Data Science (MINDS) Lab. Radiology & Biomedical Imaging (Primary) Child Study Center (Secondary) Statistics (Secondary) Wu Tsai Institute Yale Stress Center Research Interests include developing novel statistical and machine learning methods for functional connectivity in big neuroscience data, leading the BioImage Suite Web (BISWeb) platform, and advancing early life neuroimaging through the Fetal, Infant, Toddler Neuroimaging Group (FIT’NG). His work is supported by grants from NIMH, NIAA, NIDA, and NHLBI. Selected Scientific Contributions span functional connectivity in laterality preferences, anti-racist AI governance in psychiatry, self-citation trends in neuroscience, and predictive modeling of mood disorders. He collaborates extensively with Todd Constable and others on multimodal neuroimaging studies.
Amir Asif is a Professor at the Lassonde School of Engineering, York University, and concurrently serves as Vice President, Research and Innovation. His academic leadership roles include Dean of the Gina Cody School of Engineering and Computer Science at Concordia University (2014-2020). He specializes in signal processing, communications, and their applications in healthcare, power grids, and distributed systems. Asif holds a PhD from Carnegie Mellon University and a Harvard certification in executive leadership. Education: PhD, Electrical and Computer Engineering, Carnegie Mellon University (1996) MS, Electrical and Computer Engineering, Carnegie Mellon University (1993) BSc, University of Engineering and Technology Lahore (1990) Harvard Certificate in Leadership for Senior Executives (2018) Research Interests: Asif’s work spans signal processing for medical imaging (e.g., ultrasound elastography), smart grid optimization, and cybersecurity in power systems. His recent publications address hydrogen energy systems, EMG-based gesture recognition, and resilient control frameworks against cyberattacks. Grants & Leadership: He leads NSERC-funded projects on federated learning and resilient algorithms. He chairs the Ontario Council of University Research and serves on TRIUMF Innovations and the Richmond Hill Board of Trade. His grants include SSHRC funding for equity initiatives and NSERC support for distributed signal processing. Teaching & Mentorship: Asif has supervised over a dozen graduate students and taught courses like Digital Communications and Statistical Signal Processing Theory. Notable advisees include Arash Mohammadi (PhD, 2014) and Nick Sajadi (PhD, 2017).
Brad Sutton is a Professor of Bioengineering at the University of Illinois Urbana-Champaign and Technical Director of the Biomedical Imaging Center at Beckman Institute. He holds affiliate roles in the Neuroscience Program, Department of Electrical and Computer Engineering, and is a Health Innovation Professor at the Carle Illinois College of Medicine. His roles also include fellowship positions with the National Center for Supercomputing Applications and the CZ Biohub Chicago. Education: Ph.D. in Biomedical Engineering from the University of Michigan (2003). Research Interests: Focus on advanced MRI techniques for structural and functional brain imaging, including diffusion-weighted imaging, dynamic imaging, and neuromuscular coupling studies. His work emphasizes multi-scale bioimaging to understand brain function across interventions, aging, and disease. Publications: Over 180 peer-reviewed articles in 2025-2024 highlight innovations in MRI technology and applications in neuroscience, including breakthroughs in laminar fMRI specificity, myelin development modeling, and Alzheimer’s biomarker studies. Recent work extends to clinical applications like aortic imaging automation and mixed reality training tools. Awards: AIMBE and ISMRM Fellowships (2017/2024), Abel Bliss Scholar (2014-), and over 9 patents in imaging techniques. Labs & Teams: Leads the Magnetic Resonance Functional Imaging Lab. Collaborates with interdisciplinary teams across engineering, medicine, and computational science to advance imaging technologies and their clinical translation.
Gary A. Baker is an Associate Professor in the Department of Chemistry at the University of Missouri (Columbia), part of the College of Arts and Science. He holds a BS from SUNY Oswego (1995) and a PhD from SUNY Buffalo (2001). His research focuses on sustainable nanoscience, deep eutectic solvents, and nanomaterials for environmental and biomedical applications. Notable honors include the PECASE (2008), Cottrell Scholar Award (2015), and MU Graduate Faculty Mentor Award (2024). Research interests include light-driven nanochemistry, nanoparticle-based bioimaging, and waste valorization aligned with UN Sustainable Development Goals. His lab develops eco-friendly materials for water purification, sensors, and drug delivery. Collaborative work includes the Women in Training for Science (WITS) outreach program. Over 340 publications span topics like ionic liquid applications, nanoparticle synthesis, and environmental remediation. Key recent work involves programmable nanoclays, eutectogels, and piezoelectric ionic liquid studies. Awards highlight mentorship and innovation in nanoscience and sustainable chemistry.
Dr. Youngchan Kim is a Lecturer in Quantum Biology at the University of Surrey , serving as Director of the Quantum Biology Doctoral Training Centre (QB-DTC). He is affiliated with multiple departments including the School of Biosciences, Advanced Technology Institute, and Quantum Sciences Group. PhD in Physics (2011), Korea Advanced Institute of Science and Technology MSc in Physics (2008), KAIST BSc in Physics (2006), Chung-Ang University Graduate Certificate in Learning and Teaching (2022), Advance HE His research focuses on quantum phenomena in biological systems at physiological temperatures, particularly using femtosecond optical spectroscopy and genetically engineered fluorescent proteins to explore evolutionary adaptations and develop quantum-bio-inspired technologies like room-temperature single-photon sources. The 15 most recent publications span quantum biology, biophotonics, and optical spectroscopy, with particular emphasis on quantum coherence in biological systems , terahertz birefringence , fluorescent protein dynamics , and biomedical imaging innovations . These works demonstrate his interdisciplinary approach bridging physics, biology, and medical applications. As QB-DTC Director, he leads transdisciplinary initiatives fostering collaboration between quantum physics and biosciences. His technical expertise includes time-correlated single-photon counting , common-path interferometry , and ultrafast fluorescence depolarization techniques.
Barbara Smith is an Associate Professor at Arizona State University’s School of Biological and Health Systems Engineering. She joined ASU in January 2015 and leads the Smith Laboratory, focusing on photoacoustic imaging technologies and multiomic biomarker discovery for women’s health and mental illness applications. Her work bridges biomedical engineering and clinical diagnostics, with recent publications and patents advancing early-stage detection and point-of-care analysis. Postdoctoral Research Fellow, Harvard University Ph.D. in Biomedical Engineering, Colorado State University B.Sc. in Industrial Engineering, Michigan State University The Smith Laboratory specializes in developing novel photoacoustic and ultrasound imaging systems to study single-cell behavior and neural networks, aiming to improve cancer diagnosis and monitoring of mental health conditions. Collaborations with clinics have enabled patient sample analysis for multiomic biomarker identification. Scientific Awards: Centennial Professorship Award Arizona Biomedical Research Consortium Early Stage Investigator Award Women and Philanthropy Award National Science Foundation ICorps Award Her lab has submitted seven patents, and she has taught courses in bioengineering product design and directed research for advanced degree candidates. Barbara Smith’s research aligns with expertise in bioimaging, neuroimaging, and biotechnology.
Professor Brant Gibson is a Deputy Dean of Research and Innovation and holds the rank of Professor in the School of Science at RMIT University. His research focuses on quantum technologies, particularly diamond-based systems including nitrogen-vacancy (NV) centers, fluorescent nanoprobes, and hybrid materials for sensing applications. He leads projects in quantum magnetometry, photonics, and biomedical imaging, with an emphasis on translating lab-based innovations into practical devices for fields like medical diagnostics and environmental monitoring. Brant’s work spans condensed matter physics, nanotechnology, and optical engineering, with notable contributions to diamond-doped optical fibers, quantum sensor development, and the application of nanodiamonds in biophotonics. His research integrates experimental physics with computational modeling to optimize material properties and sensor performance. He is actively involved in student supervision, offering guidance for Masters and PhD candidates in quantum engineering, materials science, and interdisciplinary applications. Current projects include quantum tensor gradiometry for navigation, bioimaging with near-infrared emitters, and silk-diamond composites for wound monitoring. Brant’s academic contributions are further reflected in over 150 peer-reviewed publications and collaborations across academia and industry. His work bridges fundamental research with real-world applications, emphasizing Australia’s role in global quantum technology advancements.
Jennifer Chen is an Associate Professor in the Department of Chemistry at York University's Faculty of Science. She leads a research group focused on designing nanomaterials for optical sensing, biomedical diagnostics, and solar energy conversion , with an emphasis on plasmonic nanostructures and hybrid materials. Research spans analytical, inorganic, and physical chemistry Eligible supervisor for Physics and Astronomy graduate students Key funding: CFI, NSERC, Ontario Research Fund Her work bridges fundamental studies of materials interfaces with applications in healthcare and sustainability. Recent publications explore charge transfer mechanisms and DNA-nanoparticle interactions for biosensing. 2022: J. Mater. Chem. A on Mn-doped quantum dots 2020: Analyst and ACS Appl. Nano Mater. on DNA-based sensing 2018: JPCC on interfacial charge dynamics 2013: JACS on plasmonic microRNA detection Major awards include the Canadian Society for Chemistry Fred Beamish Award (2019), Nano Ontario Early-Career Award (2018), and Top 40 Under 40 Analytical Scientist (2018). Her group has trained 15+ graduate students, including PhD graduates Brian and Anthony.
Kejun Huang is an Assistant Professor in the Department of Computer and Information Science and Engineering at the University of Florida's Herbert Wertheim College of Engineering. His primary research area is Machine Learning, with additional interests in algorithms, computer vision, and data science. He received his Ph.D. in Electrical Engineering from the University of Minnesota in 2016. His research focuses on machine learning, signal processing, optimization, and statistics. Recent work tackles unsupervised learning challenges and AI-powered medical research through NIH-funded projects. Dr. Huang's publications demonstrate consistent focus on optimization techniques for tensor decomposition, dictionary learning identifiability, and nonnegative matrix factorization. Key themes include algorithmic efficiency and theoretical guarantees in machine learning models.
