Professor Kim Eun-hee is a faculty member in the Department of Defense Systems Engineering at Sejong University, specializing in advanced radar technologies and signal processing. Her work bridges theoretical research and practical applications in defense systems. Ph.D. in Mechanical Engineering (2004), KAIST M.Sc. in Engineering (1996), KAIST B.Sc. in Precision Engineering (1994), KAIST Her research focuses on radar system design, including airborne active phased array radar, automotive radar, broadband noise radar, and over-the-horizon radar. She explores waveform optimization, MIMO architectures, and signal processing algorithms to enhance radar performance in complex environments. Publications highlight her expertise in MIMO radar configurations, Doppler-insensitive waveforms, and machine learning integration for signal analysis. She leads industry-academic collaborations with organizations like Hanwha Systems and LIG Nex1. She contributes to technical committees, including the Sensor and Signal Processing Division of the Korean Society of Military Science and Technology. Her laboratory (Defense Radar Technology Laboratory) focuses on radar design, signal processing, and sensor integration.
Weiqiang Chen is a Professor of Mechanical and Biomedical Engineering at New York University's Tandon School of Engineering and Director of Research and PhD Programs. He holds a joint appointment at NYU Langone's Perlmutter Cancer Center as a Faculty Member of the Tumor Immunology Research Program. B.S. in Physics (Nanjing University, 2005) M.S. in Electrical Engineering (Shanghai Jiao Tong University, 2008) M.S. in Electrical and Computer Engineering (Purdue University, 2009) Ph.D. in Mechanical Engineering (University of Michigan, 2014) His research focuses on Lab-on-a-Chip , Organ-on-Chip systems, Biomaterials , and Mechanobiology , with applications in cancer biology, stem cell engineering, and immune monitoring. He pioneers microfabrication technologies for real-time observation of cellular interactions, including CAR T-cell immunotherapy efficacy and tumor microenvironment dynamics. Recent grants include NSF funding for leukemia bone marrow niche modeling, NIH Trailblazer Awards for glioblastoma immunotherapy research, and collaborations with the Arthritis Foundation for synovium-on-chip rheumatoid arthritis studies. His work has been supported by over $2M in federal and institutional research funding. National Science Foundation (NSF) grants for leukemia-on-chip and glioblastoma modeling National Institutes of Health (NIH) awards for immunotherapy research American Heart Association fellowships and institutional training programs Chen's scientific awards include the American Heart Association Fellow distinction, multiple Young Investigator Awards from Lab on a Chip and Biomedical Engineering Society, and recognition for his dissertation on nanotopography in stem cell differentiation. He leads the Applied Micro-Bioengineering Laboratory (AMBL) , which develops microphysiological systems for drug testing and personalized medicine. His team has created the first immunocompetent leukemia-on-a-chip for CAR T-cell therapy screening and glioblastoma models that enable patient-specific immunotherapy validation.
Professor Matthias Mann is a world-leading scientist serving as Director of the Proteomics and Signal Transduction department at the Max Planck Institute of Biochemistry in Martinsried, Germany, and Director of the Proteomics department at the Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Denmark. With an h-index exceeding 277 and over 350,000 citations, he is recognized as the highest cited German researcher and one of the most influential scientists globally in proteomics. His educational background includes: Ph.D. in Chemical Engineering from Yale University (1988) Master's Degree in Physics from Georg August University Göttingen (1984) Bachelor's of Arts in Mathematics from Georg August University Göttingen (1982) Professor Mann's research focuses on advancing mass spectrometry-based proteomics to understand biological systems at the protein level. His work spans technological developments in mass spectrometry, bioinformatics and computational analysis, signal transduction and posttranslational modifications, and clinical proteomics applications for disease diagnosis and treatment. The Mann lab has pioneered groundbreaking methods like SILAC for quantitative proteomics and MaxQuant for proteome data analysis. Their vision is to translate proteomics knowledge into clinical practice for predictive, diagnostic, and preventive medicine, with recent work focusing on AI-guided platforms for analyzing proteomes from minimal tissue samples. Analysis of Professor Mann's recent publications reveals a strong trend toward clinical applications of proteomics, particularly in cancer research, metabolic diseases, and neurodegenerative disorders. His work increasingly integrates spatial proteomics, single-cell resolution techniques, and artificial intelligence approaches to uncover disease mechanisms and identify potential biomarkers, with a clear shift from basic technology development toward direct clinical applications and personalized medicine. Professor Mann has received numerous prestigious awards throughout his career: 2025: Elected member of the American National Academy of Sciences 2024: Dr. H.P. Heineken Award for Biochemistry and Biophysics 2023: Otto Warburg Medal 2019: Nominated member of the Bavarian Academy of Sciences 2013: Elected member of Leopoldina German National Academy of Sciences 2012: Körber European Science Award, Louis-Jeantet Foundation Prize for Medicine, Ernst Schering Prize, and Leibniz Prize Professor Mann leads a highly collaborative research team involved in multiple international networks including the Bill & Melinda Gates Foundation, Michael J. Fox Foundation for Parkinson's Research, CLINSPECT-M, and Munich Heart Alliance. His lab has mentored numerous successful researchers, with several former postdocs receiving prestigious ERC Starting Grants. The Mann group has developed innovative clinical proteomics pipelines for analyzing archived tissue specimens and body fluids, aiming to identify protein markers for early detection of diseases such as diabetes and cancer. The Mann lab operates across two major research centers with state-of-the-art mass spectrometry facilities. Their Clinical Knowledge Graph platform integrates multi-omics data with extensive metadata, creating an ecosystem for machine learning applications in proteomics. Current research focuses on developing highly sensitive methods that can profile thousands of proteins from minimal cell samples, enabling the identification of critical disease-related proteins and supporting the development of individualized therapies.
Jean-Claude Besse is a Lecturer in the Department of Physics at ETH Zürich, specializing in superconducting circuits and quantum optics. His research focuses on quantum computing, microwave photonics, and artificial atoms. Research Interests: Besse works on the fabrication of superconducting circuits, modular quantum computing processors, and microwave quantum optics using artificial atoms. His work includes single-photon detection, parity measurements, entanglement stabilization, and quantum networking. He has developed technologies like high-fidelity multiplexed readout and tunable ZZ gates. Key Contributions: Besse led breakthroughs in non-destructive single-photon detection, deterministic remote entanglement, and loophole-free Bell inequality violations. His research enables error-corrected quantum communication protocols and scalable microwave quantum systems. Publications Trends: Recent articles emphasize modular quantum architectures, entanglement stabilization, and microwave photon engineering. Topics include cluster state generation, defect mode mitigation, and reinforcement learning for quantum feedback systems. Labs & Teams: Affiliated with the Laboratorium für Festkörperphysik at ETH Zürich, Besse contributes to advancing superconducting quantum technologies and microwave quantum optics.
Kevin C. Zhou is an Assistant Professor in the Department of Biomedical Engineering at the University of Michigan. His research focuses on developing high-performance computational optical imaging systems with unprecedented spatiotemporal throughput, integrating advanced optical instrumentation with machine learning-driven algorithms to analyze big data in biology and medicine. His lab specializes in creating imaging systems capable of capturing high-resolution, high-speed, and high-dimensional datasets. Dr. Zhou holds a Ph.D. in Biomedical Engineering from Duke University (NSF GRFP Fellow) and a B.S. in Biomedical Engineering from Yale University (Barry Goldwater Scholar). Prior to joining U-M, he was a Schmidt Science Fellow and postdoctoral researcher at UC Berkeley. Key research areas include: High-throughput microscopy (gigapixel-scale systems) 3D tomographic imaging Light field and Fourier-based imaging modalities Machine learning for image reconstruction and analysis Biomedical applications in cellular/molecular imaging His recent work has advanced technologies like multi-camera array microscopes (MCAM/MCAS) and Fourier light field mesoscopes, achieving video-rate 3D imaging of freely moving organisms. These innovations enable applications in digital cytopathology, behavioral tracking, and high-content biological studies. Notable awards include the NSF Graduate Research Fellowship and Barry Goldwater Scholarship. His research has been featured in top journals and conferences with a focus on advancing optical imaging hardware and computational pipelines.
Lauren Andrews serves as Associate Professor and Marvin and Eva Schlanger Faculty Fellow in the Department of Chemical Engineering at the University of Massachusetts Amherst. Her research integrates synthetic biology and genetic engineering to develop programmable cellular systems for biotechnological applications. Education: Postdoctoral Training: Massachusetts Institute of Technology (Biological Engineering and Broad Institute of MIT and Harvard) PhD: University of Colorado Boulder, Chemical Engineering (2012) MS: University of Colorado Boulder, Chemical Engineering (2009) BS: Cornell University, Chemical Engineering (2006) Dr. Andrews' research focuses on establishing genetic design rules for reprogramming cellular regulation and metabolism. Her lab pioneers synthetic gene networks, genetically-encoded biosensors, and high-throughput methodologies for optimizing genetic designs in both model and non-model bacteria. This work enables precise control of cellular sensing, memory, and environmental responses through multiplexed DNA assembly and next-generation sequencing. Analysis of her 15 most recent publications reveals dominant themes in bacterial biosensor development (particularly for bioremediation), quorum sensing engineering, and programmable genetic circuits for probiotic applications. Her research consistently bridges fundamental genetic circuit design with practical implementations in bacterial consortia and non-model organisms. Scientific Awards: Marvin and Eva Schlanger Faculty Fellowship NSF CAREER Award (2020) for "Programmable synthetic microbial consortia for complex multicellular functions" Her grant portfolio demonstrates significant funding for collaborative research in bacterial communication systems and model-guided design of synthetic ecosystems. The Andrews Lab maintains active partnerships with the MIT-Broad Foundry and Cold Spring Harbor Laboratory, where she co-founded the Synthetic Biology Summer Course. Current projects focus on CRISPR-based regulation in non-model bacteria and algorithmic programming of sequential logic in probiotic strains. The Andrews Lab operates within the Life Science Laboratories at UMass Amherst, utilizing advanced facilities for genetic prototyping and high-throughput screening. Her team develops multiplexed tools for exploring genetic design spaces, with particular emphasis on soil bacteria and Gram-positive pathogens for environmental and therapeutic applications.
Long Cai is a Professor at the California Institute of Technology, affiliated with the Biology and Biological Engineering department. He pioneered the field of spatial genomics and co-developed transformative technologies such as seqFISH and MEMOIR. Research Interests: His work focuses on decoding biological systems through spatial genomics, integrating molecular imaging with computational analysis to uncover cellular organization in tissues. Key areas include developmental biology, neuroscience, kidney regeneration, and cancer biology. Publications: Recent studies highlight applications of spatial transcriptomics in kidney disease, brain nuclear architecture, and multi-omics tissue mapping. His research emphasizes creating high-resolution atlases of cellular dynamics. Scientific Awards: NIH Director’s Pioneer Award (2022) Labs & Collaborations: He leads the Cai Lab, which develops cutting-edge imaging tools in collaboration with the Elowitz Lab and other interdisciplinary teams.
Qing Li is an Associate Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), part of the College of Engineering. He holds a B.E. in Electronics Engineering from Tsinghua University (2006) and a Ph.D. in Electrical and Computer Engineering from Georgia Institute of Technology (2013). Prior to CMU, he worked as a postdoctoral researcher at the National Institute of Standards and Technology (NIST), where he developed quantum frequency conversion and microresonator-based optical systems. His research focuses on light-matter interactions in integrated photonics, emphasizing nonlinear optics and quantum information processing. He has pioneered silicon carbide and aluminum nitride platforms for chip-scale quantum technologies and optical metrology. Dr. Li has been recognized with prestigious awards including the Darpa Young Faculty Award (2019), OSA Paul F. Forman Team Engineering Excellence Award (2020), and Sigma Xi Best Ph.D. Thesis Award (Georgia Tech). His work bridges classical and quantum information systems, with applications in secure communication, atomic systems interrogation, and high-precision frequency synthesis. He actively contributes to the Pittsburgh Quantum Institute (PQI), advancing regional quantum engineering initiatives. His research group’s key projects include developing compact optical frequency synthesizers, soliton microcombs for communication grids, and entangled photon pair sources for quantum networks. Grants and collaborations support his exploration of novel photonic materials and devices, targeting advancements in both fundamental science and applied technologies.
Dr. Richard Fair is the Lord-Chandran Distinguished Professor of Engineering at Duke University, with a career spanning semiconductor physics, digital microfluidics, and lab-on-a-chip systems. His research group collaborates with faculty across Duke, Harvard, and Stanford in bioengineering, genomics, and environmental science to develop applications-driven microfluidic platforms. Ph.D. in Electrical and Computer Engineering, Duke University (1969) B.S.E.E., Duke University (1964) M.S.E.E., Pennsylvania State University (1966) Research interests focus on electrowetting-based microfluidics for biosensing, diagnostics, and synthetic biology applications. Key innovations include adaptive droplet routing , magnetic bead manipulation , and integrated optical sensors for real-time analyte detection in environmental and medical contexts. Recent publications emphasize deep reinforcement learning for biochip automation, fluorescent nucleosome detection , and inorganic ion analysis in aerosols. Collaborations with institutions like Advanced Liquid Logic and NSF-funded projects highlight his interdisciplinary approach. IEEE Third Millennium Medal (2000) Solid State Science and Technology Award (Electrochemical Society, 2003) Gordon E. Moore Medal (2009) Fellow, IEEE and Electrochemical Society Grants include NSF awards with Nan Jokerst and Krish Chakrabarty for adaptive lab-on-a-chip optical control, DARPA funding for genomic engineering platforms, and collaborations with the Desert Research Institute on airborne particle sensing. His lab develops scalable solutions for environmental monitoring, clinical diagnostics, and synthetic biology applications.
Jered Haun is an Associate Professor at the Samueli School of Engineering , University of California, Irvine , with joint appointments in Biomedical Engineering , Chemical and Biomolecular Engineering , and Materials Science and Engineering . Based in 3107 Natural Sciences II , his research focuses on developing nanoengineering and molecular medicine technologies to improve disease diagnosis and treatment. Email: jered.haun@uci.edu Phone: (949) 824-1243 Research Interests include: Nanomaterial Probes for molecular profiling and disease detection Microfabricated Platforms for cell analysis and tissue processing Targeted Delivery Carriers that interact with unique disease molecules Technologies employed in his lab encompass: Fluorescence imaging and MRI enhancements Bioorthogonal chemistry and nanosensor development Micro-NMR for tumor analysis Quantum dot-based detection systems Awards include: NIH National Cancer Institute's Innovative Molecular Analysis Technologies Funding The Haun Laboratory actively recruits graduate and undergraduate students for projects related to nanoengineering, molecular medicine, and microfluidic device development.
Professor Hala Zreiqat AM is a leading biomedical engineer at The University of Sydney , serving as the Director of the ARC Training Centre for Innovative BioEngineering . A Fellow of all major Australian academies (AAS, ATSE, FAHMS, FRSN), she develops 3D printed bioceramics for bone regeneration while championing diversity through initiatives like the IDEAL Society and BIOTech Futures mentorship program. Her work bridges academia, clinical practice, and industry in musculoskeletal research . Research Focus: Her lab creates synthetic bone scaffolds that mimic natural bone architecture, strength, and porosity, enabling non-rejected bone regeneration via patient-matched implants. Key applications include orthopaedic, dental, and maxillofacial repair , with over $18M in competitive funding and multiple patents. Current projects explore AI-driven scaffold performance prediction and anti-senescence strategies for aging-related bone loss. Scientific Trends: Recent publications highlight 3D printed nanovoxelated ceramics , antisenescence biomaterials , and multifunctional theranostic platforms . Her team integrates machine learning for scaffold design, atom probe tomography for interface analysis, and two-photon imaging for cellular monitoring in 3D environments. 2021-2022 Fulbright Senior Scholar 2018 NSW Premier's Woman of the Year 2019 Eureka Prize for Innovative Use of Technology Fellow of Australian Academy of Science (2021) Over $18M in research funding Teaching & Leadership: She designed core courses like Tissue Engineering and Nanomaterials in Medicine , mentoring 158 students in 2020 alone. As Chair of CAAR (2020-2023), she strengthens Australia-Arab collaborations. Her lab trains early-career researchers , with alumni now in academia and industry.
George T.-C. Chiu is a Professor in the School of Mechanical Engineering at Purdue University, with courtesy appointments in Electrical and Computer Engineering and Psychological Sciences. He holds a 50% appointment as Assistant Dean for Global Engineering Programs and Partnerships. Previously, he served as a Program Director at the NSF, managing the Control Systems Program and National Robotics Initiative. His research focuses on mechatronics, dynamical systems, and control, with applications in printing, robotics, and human-machine interaction. Education: PhD (1994), University of California, Berkeley MS (1990), University of California, Berkeley BS (1985), National Taiwan University Research Interests: Functional printing technologies for biomedical and environmental sensors Robotics and human-robot interaction Control systems for manufacturing and dynamic systems Energy-efficient sensor design His work bridges mechanical engineering, materials science, and control theory, addressing challenges in precision manufacturing and sustainable technology. Awards: Fellow, ASME (2021) Fellow, Society for Imaging Science and Technology Grants & Projects: USDA-funded projects on food safety sensors and sustainable agriculture NSF initiatives in robotics and additive manufacturing Collaborative research with industry partners like HP and the Army Labs & Outreach: Founded the Purdue FIRST Programs, mentoring K-12 students in robotics. Co-developed experiential courses for student mentors, fostering leadership and project management skills.
JIANG Xingyu is Chair Professor and Head of the Department of Biomedical Engineering at the Southern University of Science and Technology (SUSTech) . Since 2018 he has led a multidisciplinary team developing advanced micro- and nano-scale tools for analytical chemistry, microfluidics and nanomedicine. Education Postdoctoral Research, Harvard University (2004–2005) Ph.D. in Chemistry, Harvard University (2004) B.S. in Chemistry, University of Chicago (1999) Research Interests Professor Jiang’s research integrates analytical chemistry , microfluidics , biomedical engineering and nanomedicine . His laboratory designs microfluidic chips for point-of-care diagnostics, engineers gold nanoclusters and nanoparticles for antimicrobial and anticancer therapy, and develops soft flexible bio-electronics for neural interfaces and wearable health monitoring. Across 400+ publications, recent work demonstrates a clear trend toward translational nanomedicine : point-of-care viral variant detection, nanoantibiotic strategies against multidrug-resistant bacteria, CRISPR delivery systems for cancer therapy, and conformal electronic tattoos for human-machine interfaces. Scientific Awards & Honours Fellow, American Institute for Medical and Biological Engineering (2020) Fellow, Royal Society of Chemistry (2016) Tencent Science Exploration Award (2019) Chief Scientist, National Key R&D Program (2019–) National Science Fund for Distinguished Young Scholars (2010) Young Investigator Award, Human Frontier Science Program (2007) Research Funding & Teams He currently directs the Nanoscience Laboratory at SUSTech, hosts National Key R&D Program projects as Chief Scientist, and serves on editorial boards of Advanced Healthcare Materials , Lab on a Chip , Nanoscale Horizons , Nanoscale and Nanoscale Advances . The group is actively recruiting post-docs, research professors and technicians across chemistry, materials, biology and medical engineering disciplines.
Omer Bayraktar is a Group Leader at the Wellcome Sanger Institute , leading research in the Cellular Genomics Programme. His work focuses on decoding human brain cellular diversity using spatial transcriptomics , imaging , and functional screening to study neural complexity in health and disease. Bayraktar's educational background includes a PhD from HHMI under Chris Doe, investigating neural diversity development in Drosophila , followed by postdoctoral work at University of California, San Francisco and University of Cambridge as a Life Sciences Research Foundation Fellow. He developed a spatial transcriptomic pipeline during his postdoc to analyze astrocyte heterogeneity in the cerebral cortex. His research explores neural cell type mapping , glial-neuronal interactions , and cellular pathways in neurodevelopmental disorders . Recent publications emphasize 3D tissue mapping , multi-omic integration , and computational tools like Cell2fate and WebAtlas. His work bridges neurogenetics and computational biology to advance understanding of human tissue ecosystems. Bayraktar's lab collaborates with the Human Cell Atlas initiative and develops technologies such as automated histology pipelines and highly-multiplexed smFISH for molecular cell typing. His team also investigates glia-based therapies and astrocyte functional heterogeneity in neurodevelopmental contexts. Key scientific contributions include: Discovering astrocyte layer patterns independent of neuronal laminae Developing cell2location for spatial cell mapping Characterizing Drosophila neural stem cell models with human relevance Notable awards include the Life Sciences Research Foundation Fellowship during his postdoctoral training. His current group includes a PhD student , Senior Data Scientists , and Bioinformaticians .
Dr. Benjamin C.K. Tee is an Associate Professor at the National University of Singapore (NUS), affiliated with the College of Engineering and the Department of Materials Science and Engineering. He leads the Sensors.AI Labs, focusing on transforming materials science, mechanics, and biology into cutting-edge technologies for robotics and healthcare in the AI era. His research explores novel materials and fabrication techniques to develop flexible, stretchable electronic sensors. These innovations enable applications in human-machine interfaces, biomedical devices, and AI-driven robotic systems. Key areas include self-healing materials, large-scale tactile sensing, and wireless health monitoring. His work has garnered international acclaim, including the James Dyson Foundation Prize (International Winner, 2021), MIT TR35 Innovator (2015), and recognition as a World Economic Forum Young Scientist (2019). His inventions have been commercialized through co-founded startups Privi Medical (acquired in 2021) and Hannah Life Technologies. Scientific Awards: National Research Foundation Fellowship (2017) MIT TR35 Innovator (Global) (2015) World Economic Forum Young Scientist (2019) James Dyson Foundation Prize - International Winner (2021) IES Prestigious Engineering Award (2020) Stanford University Top 2% Scientists (2021)
