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Yin Bao is an Assistant Professor in Plant and Soil Sciences and Mechanical Engineering at the University of Delaware since 2023, previously holding the same position at Auburn University's Department of Biosystems Engineering (2019-2023). He holds a BE in Mechanical Engineering from China Agricultural University (2012) and a PhD in Agricultural and Biosystems Engineering from Iowa State University (2018), followed by postdoctoral research there until 2019. His research focuses on automation technology for agriculture and forestry, leveraging robotics, machine learning, and sensing systems to develop tools for precision farming and plant phenotyping. Key areas include unmanned systems (UGVs/UAVs), spectral imaging, and AI-driven predictive models for crop and livestock management. Recent work emphasizes automated inventory systems for forest nurseries, UAV-based vegetation assessment, and machine learning applications in crop yield prediction. His publications span robotic guidance systems, root segmentation in X-ray CT scans, and equine gait analysis using deep learning. Notable projects include the Robotic Assay for Drought (RoAD) system and the 'smart canopy' sorghum initiative. Collaborative efforts involve integrating multifrequency microwave sensing and electronic nose technologies for crop quality analysis.

• Robotics and Controls
• Agricultural Automation
• Precision Farming
• +4 more

Oliver S. Cossairt is an Adjunct Associate Professor at Northwestern University's departments of Computer Science and Electrical and Computer Engineering. He leads the Computational Photography Lab , focusing on computational imaging, optics, and display technologies. His work bridges computer vision, graphics, and optical engineering to design novel imaging systems with applications in medical, astronomical, and scientific domains. Education: Ph.D. Computer Science, Columbia University (2011) M.S. Media Arts and Sciences, MIT Media Lab (2003) B.S. Physics, Evergreen State College (2003) Research Interests: Cossairt develops imaging systems that combine optical innovations with computational methods to enhance performance and functionality. Key areas include computational displays, depth sensing, and high-precision 3D imaging. His work emphasizes practical applications like medical imaging, holography, and non-line-of-sight sensing. Awards: NSF CAREER Award (2015–2020) Best Paper Award at ICCP 2011 NSF Graduate Research Fellowship (2008–2011) Teaching & Funding: Taught courses on computational photography and computer vision. Secured grants from NSF, NIH, and industry partners (e.g., Samsung, Omron) for projects like Coherent Computational Imaging and Snapshot 3D Holographic Microscope . Labs & Teams: Directs the Computational Photography Lab, collaborating with institutions like Argonne National Labs and museums for projects in cultural heritage imaging.

• Computational Imaging
• Computer Vision
• Computer Graphics
• +5 more

Scott Kerlin is a Senior Lecturer in the Department of Electrical Engineering and Computer Science at Oregon State University's College of Engineering. He holds an M.S. and B.S. in Computer Science from the University of North Dakota. Prior to academia, he worked at the Mayo Clinic on medical software systems and IBM as a build master for enterprise products. His career spans roles including network administrator, lab manager, and Undergraduate Director at UND. Dr. Kerlin's research focuses on bridging industry experience with academic curriculum, particularly in computer science education, project-based learning, and cybersecurity. He emphasizes practical applications of theoretical concepts, such as integrating 3D printing and scanning technologies with security systems for small satellites. His work also explores student efficacy in AI courses and scalable software project management methodologies. He has taught at multiple institutions, including the University of Minnesota and Augsburg University, and held roles at Michigan Tech as Senior Security Engineer. His 2024 Engineering+ Outstanding Teaching Award highlights his commitment to pedagogical innovation. Current projects include in-space 3D printing, solar energy systems, and cryptographic solutions for satellite communications. Key areas of contribution include: 3D printing/Scanning: Material characterization, key replication, and aerospace applications Cybersecurity: Intrusion detection, satellite communications security, and chaotic cryptosystems Educational Innovation: Active learning frameworks, PBL implementation, and student performance modeling His interdisciplinary approach connects computer science fundamentals with real-world engineering challenges, emphasizing sustainability and industry relevance in curricula.

• Computer Science Education
• 3D Printing and Scanning
• Cybersecurity
• +3 more

Thomas Gillespie is a Professor and Co-Chair of the Environmental Science and Engineering (D.Env.) Program at the Department of Geography, University of California, Los Angeles (UCLA). His research integrates Geographic Information Systems (GIS), remote sensing, and biogeography to study tropical dry forests in biodiversity hotspots and develop predictive models for species distribution and conservation. Education: Ph.D. in Geography, UCLA (1998) M.A. in Geography and Planning, California State University, Chico (1994) B.A. in International Affairs, University of Colorado, Boulder (1990) Research Interests: Gillespie’s work focuses on field-based floristic surveys and remote sensing analysis of tropical dry forests across the Pacific, Caribbean, and California. He combines GIS with ecological data to model biodiversity patterns, anthropogenic disturbance impacts, and climate change scenarios. His research spans biogeography, conservation science, and environmental policy. Scientific Awards: NASA Earth and Space Science Fellowship Grants: Gillespie has secured major grants from the National Science Foundation (NSF), Environmental Protection Agency (EPA), National Institutes of Health (NIA, NICHD), and MacArthur Foundation for projects on urban greening, disaster recovery, and tropical forest conservation.

• Geographic Information Systems (GIS)
• Remote Sensing
• Biogeography
• +5 more

Jaime Cardenas serves as an Assistant Professor at The Institute of Optics and holds a joint appointment as Assistant Professor of Physics at the University of Rochester. He joined the faculty in July 2016 after earning his Ph.D. in Optical Science and Engineering from the University of Alabama in Huntsville and gaining industry experience as a process engineer followed by research at the Cornell Nanophotonics Group. His educational background includes: Ph.D. in Optical Science and Engineering, University of Alabama in Huntsville Professor Cardenas' research centers on integrated photonics, nanophotonics, and nonlinear photonics, with current projects targeting photonic packaging, 2D materials integration, nonlinear optical phenomena, and on-chip quantum photonics. His group develops nanostructured photonic devices that manipulate light within chip-scale platforms, enabling applications in precision sensing, communications, and quantum technologies. This work bridges fundamental optical physics with practical engineering solutions for real-world implementation. Analysis of his recent publications reveals dominant themes in chip-scale photonic systems, particularly advancements in silicon nitride and lithium niobate platforms. Key research trajectories include weak-value amplification for ultra-precise optical gyroscopes, adiabatic frequency conversion in microring resonators, photonic packaging innovations via laser fusion splicing, and multispectral imaging sensor development. His work consistently emphasizes translating theoretical concepts into manufacturable integrated photonic devices with applications spanning navigation systems, spectroscopy, and quantum information processing. Professor Cardenas leads the Cardenas Lab, which specializes in creating photonic devices that fit on the tip of a needle. The lab's research portfolio spans from fundamental nonlinear optical phenomena to applied educational initiatives, including hands-on photonic kits designed to train the next generation of integrated photonics engineers. Current projects focus on developing robust, manufacturable photonic systems for industrial and defense applications while maintaining strong connections to quantum photonics research.

• nanophotonics
• integrated photonics
• nonlinear photonics
• +5 more

Dr. Mahendra Bhandari is an Assistant Professor at Texas A&M AgriLife Research and Extension Center in Corpus Christi, affiliated with the Texas A&M College of Agriculture and Life Sciences. He holds a B.S. in Agriculture from Tribhuvan University (2011), an M.S. in Plant, Soil and Environmental Science from West Texas A&M University (2016), and a Ph.D. in Agronomy from Texas A&M University (2020). Affiliations: Texas A&M AgriLife Research, Texas A&M College of Agriculture and Life Sciences Roles: Lead researcher in Digital Agriculture, UAS-based phenotyping, and precision agriculture His research focuses on integrating remote sensing (UAS, satellite, ground sensors), big data analytics, and machine learning to improve crop management and breeding. Key areas include high-throughput phenotyping for cotton, corn, and sorghum; UAS data integration for crop yield prediction; and digital twin frameworks for in-season management. Collaborators include Dr. Juan Landivar-Bowles and Dr. Jinha Jung. Publications emphasize UAS applications in crop monitoring, yield estimation, and disease detection. His work bridges agronomic principles with emerging technologies to enhance agricultural resilience. Key Projects: UAS-based HTP system development Satellite-UAV data fusion for precision irrigation Mechanistic models for cotton yield forecasting Labs/Teams: Leads the Digital Agriculture research team at Texas A&M AgriLife, focusing on UAS innovation and AI-driven agricultural solutions.

• Digital Agriculture
• Remote Sensing
• Precision Agriculture
• +3 more

Professor Albert Cheng is a faculty member in the Department of Computer Science at the University of Houston. His research focuses on real-time systems, cyber-physical systems, smart cities, and embedded systems with societal impacts. He has authored over 270 publications and a textbook on real-time systems. Cheng holds roles as an Associate Editor for the IEEE Transactions on Knowledge and Data Engineering and ACM Computing Surveys. His research interests span real-time scheduling, machine learning applications, and systems optimization. Recent work includes vehicular traffic modeling for epidemiological risk reduction, quantum computing response time analysis, and satellite mission planning. Awards include Fulbright Specialist, Distinguished ACM membership, and IEEE Senior Member status. Cheng’s articles demonstrate expertise in real-time scheduling algorithms, cyber-physical systems development, and smart city infrastructure. His contributions bridge theoretical computer science with practical implementations in transportation, healthcare, and aerospace domains. Ongoing efforts include fault-tolerant systems, energy-efficient scheduling, and CPS education initiatives. Awards: Fulbright Specialist, ACM Distinguished Member, IEEE Senior Member, Institute of Physics Fellow Labs/Teams: Hewlett Packard Enterprise Data Science Institute (HPE DSI), Research Computing Data Core (RCDC)

• Real-Time Systems
• Cyber-Physical Systems
• Internet of Things (IoT)
• +3 more

Maiken H. Mikkelsen is the James N. and Elizabeth H. Barton Associate Professor in the Department of Electrical and Computer Engineering at Duke University, with a joint appointment in the Department of Physics . Her research focuses on quantum nanophotonics , plasmonics , and light-matter interactions in nanoscale materials, aiming to advance optoelectronics, quantum science, and biomedical diagnostics. Education B.S. in Physics, University of Copenhagen (2004) Ph.D. in Physics, University of California, Santa Barbara (2009) Postdoctoral Fellowship, University of California, Berkeley Her work explores nanophotonic engineering for quantum optics , spintronics , and ultrafast optoelectronics , with recent studies on nonlinear metasurfaces and plasmonic enhancement of immunoassays for point-of-care diagnostics. Publications highlight 2D semiconductor emission control , ultrafast single-photon sources , and metasurface-based photodetectors . Scientific Awards Maria Goeppert Mayer Award (2017) NSF CAREER Award (2015) Moore Inventor Fellow (2021) ONR/Air Force/Army Young Investigator Awards (2015-2017) Cottrell Scholar (2016) Stansell Family Distinguished Research Award (2021) She advises graduate students in Duke’s Electrical & Computer Engineering and Physics programs and leads the Mikkelsen Lab , which emphasizes ultrafast spectroscopy and quantum material development . The lab has graduated PhD students like Eunso Shin and Hengming Li (2025).

• Quantum Nanophotonics
• Plasmonics
• Spintronics
• +7 more

Hassan Foroosh is a Professor in the Department of Electrical Engineering and Computer Science at the University of Central Florida (UCF), directing the Computational Imaging Laboratory (CIL). He holds a Ph.D. in Computer Science from INRIA-UNSA, France (1996). Prior to UCF, he worked as a Senior Research Scientist at UC Berkeley (2000–2002) and an Assistant Research Professor at the University of Maryland, College Park (1997–2000). Research Interests: His work focuses on Computer Vision, Image Processing, Machine Learning, and Signal Processing. Notable contributions include LiDAR-based perception, adversarial attacks on detectors, medical imaging analysis, and dataset design for action recognition. His research is supported by NASA, NSF, ONR, and industry partners. Publications & Impact: Over 130 peer-reviewed papers, including influential work on super-resolution techniques, transformer networks for 3D object detection, and adversarial machine learning. His recent work explores analytical reasoning in LLMs and multimodal fusion in sports analytics. Awards: Pierro Zamperoni Award (2004), Best ICPR Paper (2004), Sun Microsystems Academic Excellence Award (2004). Labs/Teams: Director of the Computational Imaging Lab (CIL), UCF. Grants: Active funding from NASA, NSF, and industry collaborators.

• Computer Vision
• Image Processing
• Machine Learning
• +3 more

Prof. Kwang W. Oh is a tenured Professor at the Department of Electrical Engineering and Department of Biomedical Engineering within the School of Engineering and Applied Sciences at University at Buffalo (SUNY at Buffalo) . He serves as the Director of Graduate Studies in Electrical Engineering and Director of SMALL (Sensors and MicroActuators Learning Lab) . His academic journey includes PhD and MS in Electrical and Computer Engineering from University of Cincinnati (2001, 1997) and BS in Physics from Chonbuk National University (1995). Prof. Oh's research expertise lies at the intersection of microfluidics , BioMEMS , and lab-on-a-chip technologies. His lab has pioneered vacuum-driven microfluidic devices , PDMS-based systems , droplet manipulation , and chemical-free fabrication techniques . His work enables point-of-care diagnostics , single cell analysis , and wearable medical sensors , with significant contributions to sample-to-answer nanosystems and world-to-chip interfacing . The scientific awards section highlights his excellence in teaching and research: SUNY Chancellor's Award for Excellence in Teaching (2020) Meyerson Award for Undergraduate Teaching (2019) Qualcomm Faculty Award (2019) Senior Teacher of the Year (2017) Royal Society of Chemistry's Emerging Investigators (2013) Samsung Electronics' CEO Honor (2003) His lab has produced numerous PhD and MS students including Dr. Anyang Wang (2020), Dr. Nikhila Nyayapathi (2020), Mr. Liam Christie (2021), and Dr. Domin Koh (2019). As a conference chair , he has organized symposia at NanoTech (2012-2026) and served as editorial board member for Sensors , Micromachines , and Biomedical Engineering Letters .

• Microfluidics
• BioMEMS
• Lab-on-a-Chip Technology
• +11 more

Uwe Bergmann is the Martin L. Perl Endowed Professor in Ultrafast X-Ray Science at the University of Wisconsin-Madison's Department of Physics. His research leverages advanced X-ray techniques to study nonlinear phenomena, real-time chemical reactions, and structural changes in both biological and material systems, with a focus on photosynthesis and ancient cultural heritage. PhD in Physics from Stony Brook University Former affiliations: National Synchrotron Light Source, European Synchrotron Radiation Facility, Lawrence Berkeley National Laboratory, Stanford Synchrotron Radiation Lightsource, Linac Coherent Light Source, Stanford PULSE Institute His work spans ultrafast X-ray spectroscopy, synchrotron methods, and the development of novel instruments like the X-FAST tabletop spectrometer. Research themes include: Photosynthetic water oxidation mechanisms using femtosecond X-ray crystallography Electronic and structural dynamics in 2D materials and metalloenzymes Imaging ancient fossils and manuscripts with X-ray techniques Advancing X-ray laser and synchrotron instrumentation Recent publications highlight attosecond X-ray pulses, catalysis under extreme conditions, and structural intermediates in photosystem II. His work intersects physics, chemistry, and paleobiology. Scientific recognition includes the Martin L. Perl Endowed Professorship. He leads the Bergmann Research Group, mentoring graduate students and postdocs in ultrafast X-ray science.

• Ultrafast X-ray Science
• Synchrotron Radiation
• X-ray Free-Electron Lasers
• +5 more

Lindsay McHenry is Professor and Department Chair of Geosciences at the University of Wisconsin-Milwaukee. She holds a Ph.D. from Rutgers University, an M.S. from Dartmouth College, and a B.S. from Dartmouth College. Her research focuses on using volcanic ash composition to correlate archaeological sites in East Africa and identifying terrestrial analogues for Martian surface minerals. Her research interests include tephrostratigraphy for human evolution studies, Mars geology analogs, sulfate mineral formation processes, and paleolimnology of saline-alkaline systems. Recent publications demonstrate strong focus on Martian analog studies using terrestrial environments (Iceland, East African lakes), mineral mapping with remote sensing/ML techniques, and paleolake reconstruction. Work increasingly incorporates drone technology and machine learning for planetary exploration applications.

• Volcanic Ash Correlation
• Archaeological Stratigraphy
• Mars Geology Analogues
• +2 more

Frederick R. Haselton is a Professor of Biomedical Engineering, Chemistry, and Ophthalmology and Visual Sciences at Vanderbilt University’s School of Engineering. His research focuses on developing low-cost, accessible diagnostic technologies for global health challenges, particularly in resource-constrained settings. He leads the Haselton Lab, a multidisciplinary team advancing innovations like Adaptive PCR, coffee ring-based diagnostics, and quantum dot imaging systems. Education : Ph.D. in Bioengineering from the University of Pennsylvania; B.A. in Mathematics from Haverford College. Research Interests : Dr. Haselton’s work spans molecular diagnostics, nanotechnology, and global health. Key projects include: Adaptive PCR: A revolutionary PCR method using synthetic L-DNA for temperature-independent cycling, enabling point-of-care diagnostics. Coffee Ring Diagnostics: Leveraging evaporation phenomena to create simple malaria and tuberculosis tests requiring no electricity. Quantum Dot Imaging: Developing multispectral tools for retinal and cardiovascular disease monitoring. Global Health Collaborations: Leading LIGHT (Laboratories for Innovation in Global Health Technologies), a cross-disciplinary initiative addressing diagnostic needs in low-resource environments. Grants & Funding : Haselton has secured major grants from NIH, Bill & Melinda Gates Foundation, and others for projects like tuberculosis detection via magnetic bead systems and mobile-connected diagnostic tests. Labs & Teams : The Haselton Lab collaborates with faculty across engineering, medicine, and chemistry. Current personnel include postdocs, graduate students, and undergraduates working on projects ranging from HIV viral load monitoring to SARS-CoV-2 diagnostics.

• Global Health Technologies
• Molecular Diagnostics
• Nano Science and Technology
• +3 more

Bohan Chen is a Postdoctoral Scholar Research Associate in the Department of Computing and Mathematical Sciences. Their work focuses on advancing graph-based machine learning techniques and their applications in environmental science, remote sensing, and AI-driven analysis. Research interests include graph neural networks, active learning strategies, hyperspectral image analysis, and knowledge graph integration. Notable contributions include the development of the GLL layer for neural networks, the CUSP permafrost dataset, and hybrid models for multispectral image processing. Key research trends span theoretical advancements in graph-based learning and practical applications such as environmental monitoring, SAR data analysis, and pandemic modeling. Their work bridges computational methodologies with real-world environmental and societal challenges. Advising and grants: No student advisees listed. Contributions include foundational research without explicit grant mentions in provided text. Labs/teams: No specific lab or team affiliations mentioned in the text.

• Machine Learning
• Computer Vision
• Data Science
• +3 more

Ioanna Kakoulli is a Professor in the Department of Materials Science and Engineering at the University of California, Los Angeles (UCLA), affiliated with the Henry Samueli School of Engineering and Applied Science. She leads the Molecular & Nano Archaeology Lab, focusing on interdisciplinary research at the intersection of materials science and cultural heritage preservation. Her work spans archaeological materials characterization, forensic imaging techniques, and conservation science. Education: D.Phil. (PhD) in Archaeological Science from the University of Oxford (1999). Key research interests include ancient pigment technologies, materials diagenesis, and the analysis of Hellenistic/Roman painting. She pioneered studies on Egyptian blue pigments and cross-cultural material exchanges via trade routes like the Silk Road. Awards include membership on the CAARI Board of Trustees, Visiting Fellowship at ICCROM, and multiple research awards from the A.G. Leventis Foundation and Overseas Research Scheme. Her lab collaborates with international institutions (e.g., Homeland Security Investigations) on looted antiquities and integrates cutting-edge imaging technologies (multispectral/hyperspectral) for non-destructive analysis. Guides students like Xuanyi Wu (SCSMM award winner), Aileen Shin, Lindsey Perry, and others in the Archaeomaterials Group. Research highlights include revealing asbestos use in Byzantine murals and identifying arsenic exposure in pre-Columbian Chilean mummies. Active in developing sustainable preservation strategies for rock-cut tombs and globigerina limestone monuments.

• Archaeological Materials Science
• Forensic Analytical Imaging
• Art Conservation
• +4 more