Prof. Silvia Vignolini is a leading researcher in sustainable and bio-inspired materials. Since January 2023, she has served as Director at the Max Planck Institute of Colloids and Interfaces , where she leads the department of Sustainable and Bio-inspired Materials . Her academic career includes a Lecturer in Physics at University College London (2013-2017) and a Professor of Biomaterials and Sustainability at the University of Cambridge (2020-2022). Education: University of Florence (Physics, PhD) Postdoctoral Research: University of Florence , University of Cambridge Her research bridges chemistry , soft matter physics , optics , and biology , focusing on the self-assembly of natural materials into functional architectures. She pioneered work on cellulose-based photonic materials with applications in displays, pigments, and radiative cooling. The selected articles highlight her work on cellulose nanocrystals , structural coloration , and sustainable fabrication techniques . Key trends include mechanochromic hydroxypropyl cellulose systems, bio-inspired light management, and applications in microalgae growth and bacterial symbiosis. Scientific Awards : Philip Leverhululme Prize (2019) ACS Lectureship in Sustainable Chemistry (2018) Ipazia Prize for Women in Science (2012) PhD Thesis Award (University of Florence, 2009) At the Max Planck Institute, her interdisciplinary research group explores bio-inspired design principles for sustainable materials, combining experimental and computational approaches to create functional materials from natural resources.
Oliver Schmitz is a Professor in the Department of Nuclear Engineering & Engineering Physics at the University of Wisconsin-Madison, where he leads research in plasma edge physics for magnetic confinement fusion and next-generation particle accelerators. His work bridges experimental plasma science, computational modeling, and diagnostic development with applications in both tokamaks and stellarators. Education: PhD (2006), Heinrich-Heine-Universität Diploma (2003), Rheinische Friedrich-Wilhelms-Universität Professor Schmitz's research focuses on 3D plasma edge transport phenomena, plasma-wall interactions, and helicon plasma generation for wakefield accelerators. His group employs advanced computational tools like EMC3-EIRENE for 3D plasma edge modeling and develops active spectroscopic diagnostics to measure plasma parameters through atomic emission analysis. Key themes include resonant magnetic perturbation effects in tokamaks, inherent 3D physics in stellarators, and high-density plasma sustainment for accelerator applications. He actively develops atomic models to interpret spectroscopic data and operates helicon plasma test stands for fundamental process studies. Recent publications reveal strong emphasis on experimental-computational integration for fusion boundary physics, with significant contributions to ITER divertor solutions, stellarator exhaust optimization, and plasma-facing materials. The work shows growing focus on wakefield accelerator diagnostics through helicon plasma sources and advanced spectroscopy, alongside persistent innovation in 3D modeling of plasma-material interfaces. Scientific Awards: 2020 Thomas and Suzanne Werner Chair Professorship 2018 UW Madison Teaching Academy Fellow 2017 ITER Science Fellowship & Vilas Mid-Career Award 2015 DOE Early Career Award & NSF CAREER Award 2011 Torkil Jensen Award (General Atomics) 2007 Günther-Leibfried-Preis (Jülich) Professor Schmitz directs multiple DOE/NSF-funded research programs including his UW Madison laboratory and AWAKE project contributions at CERN. He mentors graduate students through NE 890/990 thesis research courses and has developed nationally recognized K-12 outreach including the "Plasma Show" for elementary schools and "Plasma Academy" for high-school educators developing AP Physics curriculum modules. His leadership extends to university governance through the Kaufman seminar on academic leadership. His research group operates helicon plasma test stands and computational facilities for EMC3-EIRENE simulations, with current efforts focused on high-density plasma sources for accelerators and resilient divertor solutions for stellarators. The group maintains strong international collaborations with ITER, CERN, and major fusion facilities worldwide.
Iona Cheng is a Professor in the Department of Epidemiology and Biostatistics at the University of California, San Francisco (UCSF), where she conducts groundbreaking research in cancer epidemiology. She serves as co-Investigator of the SEER Greater Bay Area Cancer Registry and is Principal Investigator of multiple NIH- and foundation-funded projects examining genetics, lifestyle factors, and neighborhood characteristics in relation to cancer risk. Dr. Cheng has developed an extensive research program focused on racial/ethnic differences in cancer risk and leads population-based cancer surveillance studies that document variations in cancer incidence and mortality patterns across diverse racial and ethnic groups. University of California, Davis, BS, 1990–1994, Physiology Yale University, MPH, 1999–2001, Chronic Disease Epidemiology University of Southern California, PhD, 2001–2005, Epidemiology University of California, San Francisco, Postdoc, 2006–2008, Genetic and Molecular Epidemiology Dr. Cheng's research spans multiple disciplines within cancer epidemiology, with particular emphasis on understanding how environmental exposures, genetic factors, and social determinants interact to influence cancer risk and outcomes across different racial and ethnic populations. Her work frequently examines the impact of air pollution, endocrine-disrupting chemicals, and neighborhood characteristics on cancer development and survival. She has made significant contributions to understanding cancer disparities among Asian American, Native Hawaiian, and Pacific Islander populations, bringing attention to the unique cancer risks and outcomes within these understudied groups. Her research often leverages the Multiethnic Cohort Study, one of the largest prospective studies of cancer incidence and mortality across diverse racial/ethnic populations. Analysis of Dr. Cheng's recent publications reveals a consistent focus on environmental and social determinants of cancer risk across multiple organ sites. Her work demonstrates a sophisticated integration of epidemiological methods with environmental exposure assessment, genetic analysis, and health disparities research. Many of her studies examine the intersection of environmental exposures and racial/ethnic disparities in cancer outcomes, particularly regarding breast cancer, lung cancer, and other malignancies. She has published extensively on the impact of air pollution on cancer risk and survival, as well as the effects of endocrine-disrupting chemicals like bisphenol A, parabens, and phthalates. American Association for Cancer Research Scholar-in-Training Award (2007) National Institutes of Health Loan Repayment Award (2007) National Institutes of Health Loan Repayment Renewal Award (2009) American Association for Cancer Research Faculty Scholar Award (2011) National Institutes of Health Loan Repayment Renewal Award (2011) National Institutes of Health Loan Repayment Renewal Award (2013) American Journal of Epidemiology/Society of Epidemiology Research Top 10 manuscripts (2014) Cancer Prevention Institute of California Mentoring Award (2015) American Society of Human Genetics Top poster As Principal Investigator of multiple NIH-funded projects, Dr. Cheng oversees substantial research grants focused on cancer epidemiology and health disparities. Her work often involves large interdisciplinary collaborations with researchers across multiple institutions, including the Multiethnic Cohort Study which follows over 200,000 participants from diverse racial/ethnic backgrounds. She has demonstrated leadership in mentoring junior researchers, particularly those from underrepresented backgrounds in science, as evidenced by her Cancer Prevention Institute of California Mentoring Award. Her research program integrates data from cancer registries, electronic health records, and geospatial information to provide comprehensive insights into cancer patterns and risk factors. Dr. Cheng's research is closely connected to the UCSF Helen Diller Family Comprehensive Cancer Center and leverages collaborations with Lawrence Berkeley National Laboratory, which provides advanced technological resources for cancer research. Her work benefits from access to extensive cohort data, sophisticated exposure assessment methods, and interdisciplinary expertise in genetics, environmental science, and computational biology available through these institutional partnerships. She frequently collaborates with researchers studying the genetic and environmental determinants of cancer across multiple organ systems, contributing to a more comprehensive understanding of cancer etiology and prevention strategies.
Zhiqiang Yu serves as an Associate Professor in the Department of Modern Languages and Comparative Literature at Baruch College's Weissman School of Arts and Sciences, City University of New York. With over two decades of teaching experience, he has established himself as a dedicated educator specializing in Chinese language, cinema, and civilization courses. Education: Ph.D. in Chinese, University of Washington M.A. in Asian Civilization, University of Iowa B.A. in Chinese Literature, Fudan University (Shanghai) Professor Yu's research focuses on innovative approaches to Chinese language pedagogy, with particular interest in applying economic principles and artificial intelligence to language teaching. His work bridges traditional linguistic scholarship with modern educational technology, examining how efficiency, resource allocation, and technological advancements can enhance language learning outcomes. His research spans Chinese linguistics, dialectology, cinema studies, and cultural elements in language teaching. His publication record reveals a consistent trajectory toward optimizing language instruction through systematic analysis. Recent work increasingly focuses on AI applications in language education and the economic framework of pedagogical efficiency. His scholarship demonstrates a progression from traditional linguistic analysis toward innovative teaching methodologies that incorporate modern technological and theoretical frameworks. Scientific Awards: Award of Excellent Academic Research Reviewer from Journal of International Chinese Education (2016) Graduate Teaching Fellowship from University of Washington (1993) Graduate Teaching Fellowship from University of Iowa (1989) Graduate Research Fellowship from University of Iowa (1988) Student Excellency Award from Fudan University (1984) Professor Yu has served extensively on departmental committees including as Department Assessment Coordinator and Secretary of the Asian and Asian-American Studies Committee. He has organized numerous academic events featuring prominent Chinese cultural figures and has contributed to developing Chinese language curriculum resources including online placement tests. His professional service extends to editorial work for CUNY publications and Chinese language training for the New York Police Academy. He maintains active involvement with multiple professional organizations including the American Name Society, American Oriental Society, American Society of Geolinguistics, Association for Asian Studies, and Chinese Language Teachers Association, frequently presenting at international conferences on Chinese language pedagogy.
Simon Mak is an Assistant Professor of Statistical Science at Duke University and a Faculty Network Member of the Duke Institute for Brain Sciences. His educational background includes: Ph.D. in Statistics, Georgia Institute of Technology (2018) M.S. in Statistics, Georgia Institute of Technology (2018) B.S. in Statistics, Simon Fraser University (2013) Dr. Mak's research focuses on advanced statistical methodologies for complex scientific problems. His expertise spans statistical modeling , Bayesian inference , Gaussian process emulation , and uncertainty quantification . He applies these methods to nuclear physics (heavy-ion collisions), engineering (engine control systems), and music information retrieval, emphasizing scalability and interpretability in scientific computing. Analysis of his 2023-2025 publications reveals dominant trends in scalable Gaussian process methods for massive datasets and multi-fidelity simulations, particularly applied to high-energy physics and engineering systems. He has pioneered innovations in Bayesian optimization for expensive simulators and developed novel frameworks for online change-point detection in streaming data, demonstrating exceptional cross-disciplinary impact. Dr. Mak leads multiple significant research initiatives: Collaborative Research: Cost-Efficient and Confident Sampling for Modern Scientific Discovery (2023-2026) Science-Integrated Predictive modeLing (SCINPL) for scalable scientific computing (2022-2025) The X-SCAPE collaboration for statistically advanced nuclear collision modeling (2020-2025) These projects fund his development of statistical frameworks for scientific discovery in complex systems. He actively contributes to the JETSCAPE collaboration, developing multi-stage frameworks for studying jet quenching in heavy-ion collisions, and applies statistical methods through the Duke Institute for Brain Sciences to advance neuroscience research.
Aaron M. Dollar is the Frederick W. Beinecke Professor of Mechanical Engineering at Yale University, affiliated with the Yale Grab Lab. His research focuses on robotics, mechatronics, robotic grasping, and prosthetics, emphasizing adaptive mechanisms and human-robot interaction. He holds a PhD from Harvard University (2008) and degrees from UMass Amherst. Key research areas include dexterous manipulation, underactuated mechanisms, and assistive devices. His work bridges theory and practical applications, with contributions to prosthetic hands, robotic hands, and modular robotics systems. Recipient of prestigious awards: TR35 Innovator (2010), NSF CAREER Award (2010), DARPA Young Faculty Award (2013), and Air Force Young Investigator Award (2011). Developed the Yale MyoAdapt Hand, a single-actuator prosthetic with high functionality. Pioneered methods in real-to-sim transfer, modular lattice printing, and energy-aware robotic exploration. His lab, the Yale Grab Lab, explores robotics, prosthetics, and human motion analysis. Recent projects include autonomous calibration systems (ARC-Calib) and low-cost robotic hardware (RB5 Explorer).
Ben Seiyon Lee is an Assistant Professor in the Department of Statistics at George Mason University's College of Science. His work bridges computational statistics, climate modeling, and environmental risk assessment. Education: PhD in Statistics, Pennsylvania State University (2020) Lee specializes in computational methods for high-dimensional spatiotemporal data and uncertainty quantification in climate models. His research explores climate change impacts on extreme hydrological events, wildfire emissions, and medical decision-making. Recent publications focus on Bayesian spatiotemporal frameworks for extreme precipitation analysis, zero-inflated spatial models, and multisector uncertainty quantification. His work addresses challenges in flood risk assessment, agricultural yield projections, and healthcare compliance metrics.
Ralph Jimenez is an Adjunct Professor of Chemistry and Institute Fellow at JILA, University of Colorado Boulder. He holds a Ph.D. from the University of Chicago (1996) and completed postdoctoral work at the University of California, San Diego (1997-1998), followed by research at The Scripps Research Institute (1998-2003). His research focuses on quantum spectroscopy and photophysics of fluorescent proteins, leveraging quantum optics to enhance spectroscopic sensitivity and developing genetically encoded biomarkers with improved photophysical properties. Key achievements include fluorescence-lifetime-based methods to engineer brighter fluorescent proteins and machine-learning approaches to improve photostability. His awards include the Arthur S. Flemming Award (2017) and U.S. Department of Commerce Gold Medal (2017). His group's work integrates quantum engineering with biophysical studies, targeting real-world applications in molecular imaging and materials science. The Jimenez Group operates labs at JILA (B117, B119, B121) and collaborates on projects involving entangled photons, two-photon absorption, and ultrafast spectroscopy. Research themes include quantum-enhanced spectroscopy for complex systems and overcoming limitations in fluorescent protein imaging through physical chemistry strategies. His lab develops novel instrumentation, including microfluidic sorting systems and tabletop X-ray spectroscopy platforms, to advance biomarker engineering and environmental monitoring.
Joachim Weickert is a Professor of Mathematics and Computer Science at Saarland University where he heads the Mathematical Image Analysis Group since 2001. He received his diploma and Ph.D. in mathematics from the University of Kaiserslautern (1991, 1996), and a habilitation degree in computer science from the University of Mannheim (2001). Prior to his current position, he worked as a research assistant at the University of Kaiserslautern, as a post-doctoral researcher at the universities of Utrecht and Copenhagen, and as an assistant professor at the University of Mannheim. His research focuses on image processing, computer vision, and scientific computing, with special emphasis on techniques based on partial differential equations, variational principles, wavelets, morphological and nonlocal methods, as well as neuroexplicit approaches. He has developed mathematical models and efficient numerical algorithms for image restoration, enhancement, segmentation, compression, optic flow computation, stereo reconstruction, shape from shading, and signal processing methods for tensor fields. These ideas have been successfully applied in industry, biomedical image analysis, and other fields. Analysis of his recent publications reveals a strong trend toward combining traditional PDE-based methods with modern deep learning approaches, particularly in the areas of image inpainting and compression. His work increasingly explores the connections between numerical algorithms for partial differential equations and neural network architectures, demonstrating how mathematical foundations can inform cutting-edge AI techniques while maintaining strong theoretical guarantees. Gottfried Wilhelm Leibniz Prize (2010), considered the most important research award in Germany ERC Advanced Grant (2017) for "Inpainting-based Compression of Visual Data" Elected member of Academia Europaea - The Academy of Europe Jan Koenderink Prize for Fundamental Contributions in Computer Vision (2014) Multiple DAGM Prizes and Best Paper Awards throughout his career AAIA Fellow (2021) and Highly Ranked Scholar (2024) distinctions Professor Weickert has supervised over 250 bachelor's and master's theses and initiated the Master Programme in Visual Computing at Saarland University, the first of its kind in Germany taught in English. He has established numerous interdisciplinary collaborations with colleagues from medicine, bioinformatics, pharmacy, physics, mechatronics, and mechanical engineering. As Principal Investigator for Visual Computing within the Multimodal Computing and Interaction Cluster of Excellence, and former dean of the Faculty of Mathematics and Computer Science (2008-2010), he has played a significant leadership role in advancing visual computing research and education. He heads the Mathematical Image Analysis Group, which has been at the forefront of developing mathematical methods for image analysis. The group maintains strong connections with both theoretical mathematics and practical applications, bridging the gap between fundamental research and real-world implementation across various domains including medical imaging, industrial inspection, and multimedia processing.
John Capobianco, PhD, is a Professor in the Department of Chemistry and Biochemistry at Concordia University and holds the Honorary Concordia University Research Chair in Nanoscience. His research focuses on lanthanide-doped nanoparticles, upconversion luminescence, and biomedical applications. PhD, University of Geneva Key research areas include: Nanomaterials synthesis and spectroscopy Upconversion for biomedical imaging Drug delivery systems Photodynamic therapy for cancer treatment Optical thermometry and sensing Recent publications highlight advancements in: X-ray detection via photochromic nanoparticles Lipid-coated nanoparticles for lung permeation Cooperative energy transfer in Yb3+/Eu3+ complexes Biocompatible nanomaterials for secure information storage Pr3+-doped radiosensitizers for glioblastoma therapy Scientific recognitions: Honorary Concordia University Research Chair in Nanoscience Teaching includes undergraduate and graduate courses in inorganic chemistry and spectroscopy. His work bridges fundamental material science with applied biomedical engineering, emphasizing optical properties and therapeutic applications of lanthanide-based nanomaterials.
Professor Graham Sander is a Professor of Hydrology at Loughborough University, affiliated with the School of Civil and Building Engineering. His research focuses on mathematical modeling of soil erosion, unsaturated soil flow, contaminant transport dynamics, and nonlinear diffusion-convection equations. He leads the NERC-funded project on multi-dimensional soil erosion and chemical transport, collaborating with Lancaster University’s Department of Environmental Science. His academic qualifications include a BSc (Hons) and PhD. Recent research emphasizes integrating particle size-selective models to predict sediment and contaminant delivery to water bodies, supported by lab and field experiments. He has also pioneered pseudospectral methods for infiltration modeling and explored flood risk management through nature-based solutions like leaky barriers. Key contributions include advancing understanding of rainfall-driven erosion dynamics, including splash effects and rock fragment coverage impacts. His work spans experimental hydrology, numerical simulation, and interdisciplinary approaches to environmental challenges. He co-edits hydrology journals and advocates for rigorous scientific communication in the field. Grants: NERC-funded soil erosion project, Australian Research Council project on unsaturated soil flow. Labs/Teams: Collaborator with Lancaster University’s Environmental Science Department.
Tim Cohen is an Associate Professor of Physics at the University of Oregon, with affiliations at CERN and EPFL's Lausanne Theory Physics Laboratory. He is based at the Institute for Fundamental Science within the Department of Physics at the University of Oregon's College of Arts and Sciences. His research focuses on theoretical particle physics, particularly exploring phenomena beyond the Standard Model. Dr. Cohen's research interests center on particle physics beyond the Standard Model, with specific expertise in Large Hadron Collider phenomenology, effective field theory, electroweak naturalness, and dark matter. His work bridges theoretical frameworks with experimental possibilities at major particle physics facilities. His research program encompasses both theoretical developments in quantum field theory and practical applications to collider physics and cosmology. Analysis of his recent publications reveals a strong focus on effective field theory applications, de Sitter space physics, and dark sector phenomenology. His work demonstrates sophisticated mathematical approaches to problems in quantum field theory while maintaining connections to observable phenomena at particle colliders and in cosmological settings. He frequently collaborates with researchers across institutions including CERN, EPFL, and various US universities. Dr. Cohen serves as a senior researcher with active roles at multiple institutions, contributing to major collaborative efforts such as the Snowmass community planning process for particle physics. His work appears in leading journals including Journal of High Energy Physics, Physical Review D, and Physics Letters B, demonstrating consistent productivity and impact in the field. His research group operates within the Institute for Fundamental Science at the University of Oregon, with additional connections to theoretical physics groups at CERN and EPFL. This international collaboration network enables him to work at the intersection of theoretical developments and experimental frontiers in particle physics.
David Juncker is a Professor and Department Chair of the Department of Biomedical Engineering at McGill University. He serves as a Principal Investigator at the McGill University & Genome Quebec Innovation Centre and holds associate memberships in the Department of Neurology and Neurosurgery, Department of Electrical and Computer Engineering, Division of Experimental Medicine, Department of Surgery, and Goodman Cancer Research Centre. His research focuses on micro- and nano-bioengineering technologies for bioanalysis, precision medicine, and organs-on-chips. Key areas include microfluidics, lab-on-a-chip devices, biomedical sensors, medical diagnostics, biomaterials, tissue engineering, and cancer biomarker discovery. His lab develops scalable antibody microarrays, self-powered diagnostic platforms, microfluidic probes for brain tissue perfusion, and nanogradients for neuronal navigation, with applications in cancer diagnostics, global health, and neuroscience. Recent publications (2023-2025) reveal strong emphasis on extracellular vesicle analysis, single-cell proteomics, 3D-printed microfluidic/organ-on-a-chip systems, and capillary-driven circuits. Key trends include low-cost point-of-care diagnostics, advanced circulating tumor cell isolation methods, and biomimetic synthetic vesicles for drug delivery, demonstrating translational potential in early disease detection. Dr. Juncker leads a highly interdisciplinary team comprising undergraduate and graduate students, post-doctoral fellows, and staff from diverse scientific, engineering, and cultural backgrounds. His lab actively recruits Canadian/permanent resident graduate students for projects on single extracellular vesicle and protein detection in cancer and infectious diseases, leveraging microfluidics and wearables for biomarker discovery. The Juncker Lab operates from the McGill University & Genome Quebec Innovation Centre (740 Dr. Penfield Avenue, Room 6206). It maintains a collaborative, multicultural environment focused on developing transformative micro- and nano-bioengineering technologies with significant potential impact on human health diagnostics and treatment.
Dr. Borivoje Dakic is an Associate Professor at the University of Vienna , affiliated with the Faculty of Physics and the Quantum Optics, Quantum Nanophysics and Quantum Information department. His research spans foundational and applied aspects of quantum theory. Operational reconstruction of quantum formalism Quantum interference as a resource for communication Tomography of large-scale quantum systems Macroscopic quantum phenomena His work includes scalable verification techniques for quantum devices and collaborations with experimental teams like Philip Walther’s and Markus Aspelmeyer’s groups. He received the Marko Jarić Prize (2025) for his contributions. Recent projects focus on diagnostics of quantum devices (FWF BeyondC SFB), information-theoretic foundations of quantum interference (FWF P36994), and local operations in quantum field theory (Cluster of Excellence QuantA). His research on quantum coherence in networks and macroscopic entanglement challenges traditional assumptions about quantum-classical boundaries. Publications emphasize resource-efficient tomography, device-independent verification, and foundational frameworks for quantum statistics and field theory. Teaching: Quantum Information (2025W), Theory in Quantum Optics (2025S), VCQ Summerschool Labs: Dakić Group at University of Vienna
Suliana Manley is a Full Professor at the École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the School of Basic Sciences and the Laboratory of Experimental Biophysics . She also holds teaching and research roles in EPFL's School of Life Sciences and Swiss Plasma Center , focusing on interdisciplinary biophysical studies. Education : PhD in Physics (2004), Harvard University Bachelor's in Physics & Mathematics (1997), Rice University Manley's research centers on super-resolution fluorescence imaging , single-molecule tracking , and quantitative biophysics . Key themes include: Understanding protein assembly dynamics at cellular membranes Elucidating viral assembly mechanisms (e.g., HIV-Gag) Developing 3D imaging algorithms and high-density data reconstruction tools like PALMsiever and FALCON Quantifying nanoscale organization in systems like telomeres and centrioles Her work bridges optical physics , computational image analysis , and cellular biology , with notable Nature and PNAS publications. Collaborations span bioengineering , genetics , and medical research . Scientific Awards : Featured in Nature Methods Research Highlights (3x) Very Important Paper and Cover Article (ChemBioChem, 2012) Postdoctoral Fellow, NIH and MIT Advising & Collaborations : Current PhD students in biophysics, cellular biology, and bioengineering Former students: Anna Archetti, Aleksandr Benke, Andrea Callegari, and others Co-founder of tools for high-density super-resolution microscopy and live-cell imaging Labs & Teams : Leads the Laboratory of Experimental Biophysics at EPFL, integrating physics-based methods into biological questions. The lab focuses on quantitative imaging , computational modeling , and software development for nanoscale analysis.
