جستجوی استاد راهنمای دانشگاهی

Pasquale Bottalicoمشاهده پروفایل

دانشیار

• Vocal Load
• Professional Voice Techniques
• Singer Techniques
• +۳ مورد دیگر

Pasquale Bottalico serves as Associate Professor in the Department of Speech and Hearing Science at the University of Illinois, with dual appointments as Associate Professor at the Center for Latin American and Caribbean Studies and Affiliate Faculty in the School of Music. His unique interdisciplinary profile bridges engineering, music performance, and speech science, reflecting his dual academic training and professional artistry. His educational foundation includes: Bachelor's in Telecommunications Engineering from Univeristà Mediterranea di Reggio Calabria, Italy Concurrent Opera Singing degree from F. Cilea Music Academy, Reggio Calabria Master's in Telecommunications Engineering from Politecnico di Torino, Italy Ph.D. in Metrology specializing in acoustics measurement uncertainty and classroom acoustics Dr. Bottalico's research centers on vocal load quantification and professional voice techniques , with significant contributions to understanding vocal fatigue in teachers and singers. His work spans Speech Intelligibility in educational environments, Room Acoustics for performance and learning spaces, and Musical Acoustics of historical vocal styles. A distinctive thread throughout his research examines how acoustic conditions modulate voice production and perception, increasingly incorporating virtual reality and bone conduction technologies for innovative assessment and intervention approaches. His Colombian vocal health study demonstrates cross-cultural applications of his work. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) The impact of noise and dysphonia on children's speech processing in educational settings, using multimodal assessment including EEG; (2) Virtual reality applications for voice production research and therapeutic intervention; (3) Cross-cultural validation of vocal fatigue metrics and development of biofeedback systems. His work consistently bridges engineering precision with clinical applicability, particularly for professional voice users in challenging acoustic environments. No scientific awards were documented in the available information. While specific advising relationships aren't detailed, his research collaborations span international institutions including Colombian and Italian universities, suggesting graduate mentorship in interdisciplinary projects. No grant information was provided, though his systematic reviews and cross-cultural studies imply externally funded research activities. Though no dedicated laboratory is specified, his virtual reality voice studies and acoustic parameter assessments suggest affiliations with audio engineering facilities and voice clinics, likely through the Speech and Hearing Science department's research infrastructure.

Jan von Delftمشاهده پروفایل

استاد

• Correlated electron systems
• Quantum impurity models
• Quantum criticality
• +۷ مورد دیگر

Jan von Delft is a Professor (chair) at Ludwig-Maximilians-University (LMU) Munich, working in the Faculty of Physics within the Chair of Theoretical Solid State Physics. His research group consists of postdocs, PhD students, and master's students working on various aspects of strongly correlated electron systems, with physical space located at Theresienstr. 37 (Room A420) in Munich. von Delft's research focuses on correlated electron and spin systems, with particular interest in dynamical and transport properties, quantum impurity models, Hund metals, unconventional superconductors, quantum magnets, and quantum criticality. His methodological expertise includes many-body field theory, parquet formalism (FRG), DMFT, and tensor networks (NRG, DMRG, PEPS, XTRG, etc.). His work bridges theoretical concepts with computational approaches to understand complex quantum phenomena in condensed matter systems. He has developed a distinctive emphasis on real-frequency calculations and numerical methods for studying quantum critical phenomena. Analysis of von Delft's recent publications reveals a strong focus on developing and applying advanced computational methods to study strongly correlated electron systems. His group has made significant contributions to numerical renormalization group techniques, tensor network methods, and the parquet formalism for calculating real-frequency correlation functions. His research shows increasing sophistication in handling quantum criticality, particularly in heavy-fermion systems, and exploring unconventional superconductivity mechanisms. Notably, his group has developed specialized computational libraries like KeldyshQFT to make these advanced methods more accessible to the broader physics community. von Delft actively mentors a substantial research group consisting of one postdoc (Markus Scheb), eleven PhD students (Anxiang Ge, Sasha Kovalska, Mathias Pelz, Marc Ritter, Nepomuk Ritz, Changkai Zhang, Markus Frankenbacher, Felipe Picoli, Simone Fodera, Ming Huang), and two master's students (Ester Pages, Gianluca Grosso). His detailed Style Guide for scientific communication demonstrates his commitment to high-quality research presentation. The group appears well-funded with ongoing research activities spanning theoretical development, computational implementation, and physical interpretation of complex quantum phenomena.

Steven Rogakمشاهده پروفایل

استاد

• Aerosol Science
• Nanoparticle Transport
• Combustion Processes
• +۵ مورد دیگر

Steven Rogak is a Professor in the Department of Mechanical Engineering at the University of British Columbia's Faculty of Applied Science. He holds a P.Eng. license and degrees including a B.A.Sc. in Mechanical Engineering from UBC, and M.Sc. and Ph.D. from Caltech. P.Eng., University of British Columbia B.A.Sc., University of British Columbia M.Sc., Ph.D., California Institute of Technology His research focuses on aerosol science, particularly solid nanoparticles from combustion processes, their climate and health impacts, and mitigation strategies. Key areas include: Soot morphology and transport properties Engine emission reduction via fuel injectors Indoor air filtration systems Membrane-based energy exchangers Atmospheric particulate analysis The 15 most recent articles span experimental and theoretical studies on soot characterization, membrane technologies, and aerosol dynamics, with applications in climate modeling, healthcare ventilation, and sustainable materials. Collaborations include Westport Innovations and interdisciplinary teams. Rogak leads the Aerosol Laboratory at UBC, where he applies fluid mechanics and heat transfer fundamentals to address environmental and health challenges. He emphasizes experimental rigor and welcomes graduate students with expertise in these areas.

Mengliang Zhangمشاهده پروفایل

دانشیار

• Forensic Chemistry
• Food and Agricultural Chemistry
• Metabolomics
• +۱۲ مورد دیگر

Mengliang Zhang is an Associate Professor in the Department of Chemistry and Biochemistry at Ohio University, College of Arts and Sciences. He leads an interdisciplinary research group focused on mass spectrometry and chemometrics, with applications in forensic, food, agricultural, environmental, and material sciences. His lab develops innovative analytical strategies for detecting toxicants, characterizing nanomaterials, and profiling metabolites in botanicals and food systems. Ph.D., Chemistry, Ohio University, 2015 Dr. Zhang’s research integrates instrumentation, chemometrics, and computational tools to address complex analytical challenges. His group works on forensic fiber and ignitable liquid analysis, plant metabolomics, nanomaterial surface chemistry, and environmental toxicant monitoring. His work is highly interdisciplinary, bridging chemistry, data science, and real-world applications in forensics and public health. His recent publications demonstrate a strong trend in advancing ambient ionization mass spectrometry (especially DART-MS), chemometric modeling, and metabolite profiling across diverse matrices—from fire debris to broccoli microgreens. His work increasingly emphasizes automation, quantitation, and database development for botanical phytochemicals. Scientific honors include the MTSU Distinguished Research Award (Early Career), and his students have received prestigious awards such as the Goldwater Scholarship and multiple URECA recognitions. He is actively supported by federal grants from NSF, USDA, DOE, DOJ (NIJ), and FEMA. Dr. Zhang mentors a vibrant research team of graduate and undergraduate students, guiding them in publishing high-impact research and presenting at national conferences like ASMS, Pittcon, and AAFS. He has organized sessions at SciX and served on editorial boards of Journal of Forensic Sciences and Journal of AOAC INTERNATIONAL . His lab recently relocated to Ohio University in August 2024, equipped with advanced instrumentation including UHPLC-QTOF-MS and DART-MS systems.

Ayşe Nihan AVCIمشاهده پروفایل

استادیار

• Lighting Design
• Health and Well-Being in Interior Spaces
• OLED Lighting Technology
• +۴ مورد دیگر

Dr. Ayşe Nihan AVCI is an Assistant Professor at the Department of Interior Architecture, Faculty of Architecture at Çankaya University. She holds a PhD in Design (2022), Master's in Interior Architecture (2017), and Bachelor's in Interior Architecture (2010) from the same institution. Her research focuses on lighting design's impact on health and well-being, biophilic design principles, and OLED/LED lighting technologies. She has been a full-time faculty member since 2015, progressing from Research Assistant (2015-2022) to Doctoral Researcher (2022-2024) before her current role. Education: PhD in Design, Çankaya University (2017-2022) MSc in Interior Architecture, Çankaya University (2014-2017) BSc in Interior Architecture, Çankaya University (2005-2010) Research Interests: Her work integrates lighting science with human-centric design principles, emphasizing: Salutogenic lighting strategies for health promotion OLED technology's circadian rhythm effects Biophilic daylighting in historical buildings Visual comfort in workplaces Publications: Over 15 peer-reviewed articles (2016–2025) focus on OLED/LED lighting applications, circadian rhythms, and daylighting in heritage buildings. Recent work explores salutogenic design in coffee shop environments and workplace environmental quality. Awards: No specific awards listed, but active in academic service: Member of Aydınlatma Türk Milli Komitesi since 2017 Member of TMMOB İç Mimarlar Odası since 2010 Reviewer for journals including PLANARCH Grants & Projects: Led a university-supported research project (2020–2021) on lighting design's health impacts. Currently teaches courses on lighting design, materials science, and interior design fundamentals.

Mohammad Mohammadi Amiriمشاهده پروفایل

استادیار

• Large Language Models
• Data Valuation
• Federated Learning
• +۵ مورد دیگر

Mohammad Mohammadi Amiri serves as an Assistant Professor in the Department of Computer Science at Rensselaer Polytechnic Institute (RPI), appointed in Fall 2023. His research focuses on advancing artificial intelligence through strategic data utilization, with emphasis on large language models, data valuation, federated learning, and deep learning. Previously, he held postdoctoral appointments at Princeton University and MIT Media Lab, building on his strong educational foundation from Imperial College London, University of Tehran, and Iran University of Science and Technology. Education: Ph.D. in Electrical and Electronic Engineering, Imperial College London (2019) - Best Ph.D. Thesis Award recipient M.Sc. in Electrical and Computer Engineering, University of Tehran (2014) - Ranked 1st among all M.Sc. students B.Sc. in Electrical Engineering, Iran University of Science and Technology (2011) - Ranked 1st among all B.Sc. students Dr. Amiri's research centers on optimizing artificial intelligence systems through innovative data strategies. His work addresses critical challenges in large language models including efficiency, memory usage, alignment, and reasoning capabilities. In data valuation, he develops principled methods to quantify data worth for fair trading platforms. His federated learning research tackles privacy concerns, heterogeneous data distribution, and communication overhead in decentralized environments. The deep learning component explores theoretical foundations to improve model interpretability and robustness. Analysis of his recent publications reveals a strong focus on making AI systems more efficient and accessible, with particular emphasis on large language model optimization, federated learning advancements, and data valuation frameworks. His work bridges theoretical foundations with practical applications in wireless communications and distributed computing environments. Scientific Awards: IEEE Communications Society Young Author Best Paper Award (2022) Best PhD Thesis Award from IEEE Information Theory Chapter of UK and Ireland (2019) Eryl Cadwallader Davies Prize for Outstanding PhD Thesis (2019) EEE Departmental Scholarship at Imperial College London (2015-2019) Ranked 1st among M.Sc. students at University of Tehran (2014) Ranked 1st among B.Sc. students at Iran University of Science and Technology (2011) Dr. Amiri actively mentors graduate students, currently supervising five Ph.D. candidates and one M.Sc. student working on efficient LLM fine-tuning, inference, and storage. His research has attracted significant attention, evidenced by numerous keynote invitations at prestigious institutions including Bell Labs, MIT, King's College London, and various IEEE conferences. He serves on program committees for major conferences including IEEE Globecom and ICC, demonstrating his growing influence in the academic community. His research group operates at the intersection of machine learning and wireless communications, developing innovative solutions for resource-constrained environments while addressing fundamental theoretical challenges in AI systems. Current projects focus on making advanced AI more scalable and accessible through efficiency improvements in model training and inference.

Sean Lubnerمشاهده پروفایل

استادیار

• Energy Storage
• Thermal Engineering
• Materials Science
• +۵ مورد دیگر

Sean Lubner is Core Faculty at the Boston University Institute for Global Sustainability (IGS) and Assistant Professor in Mechanical Engineering within the College of Engineering. He holds a PhD from UC Berkeley and BS degrees in Mechanical Engineering and Applied Physics from Carnegie Mellon University. His research focuses on energy transport and storage systems, including thermal energy storage, battery diagnostics, and CO₂ capture technologies. Education: PhD in Mechanical Engineering, UC Berkeley (NSF Fellow) BS in Mechanical Engineering & Applied Physics, Carnegie Mellon University Research Interests: Lubner specializes in grid-scale thermal energy storage, non-invasive sensors for harsh environments, and decarbonization strategies. His work integrates machine learning with materials science to develop advanced energy systems. He collaborates with industry on patents involving battery safety, photonic surfaces, and phase change materials. Article Trends: Recent publications emphasize high-temperature materials, battery failure prediction via thermal signatures, and femtosecond laser processing for photonic surfaces. His work bridges nanoscale phenomena with macro-scale energy systems, leveraging interdisciplinary methods. Awards: Lubner was an NSF Graduate Research Fellow during his PhD. Advising & Grants: While no advisees are listed, his research is supported by industry partnerships and grants focusing on energy storage innovation. He leads the Lubner Group, which develops novel sensing and storage technologies. Labs/Teams: The Lubner Group at BU focuses on sustainable energy solutions, combining experimental and computational approaches to address climate challenges.

Jeff Searlمشاهده پروفایل

استاد

• Speech Production
• Head and Neck Cancer Rehabilitation
• Voice Assessment
• +۳ مورد دیگر

Jeff Searl is a Professor in the Department of Communicative Sciences and Disorders at Michigan State University (MSU), within the College of Communication Arts and Sciences. Previously, he held faculty roles at the University of Kansas Medical Center’s Hearing and Speech Department and the Otolaryngology – Head & Neck Surgery Department. He earned his Ph.D. from the University of Kansas. His research focuses on understanding how chemoradiation and surgery for head and neck cancers affect speech and voice production. The goal is to develop clinical practices that preserve or rehabilitate communication for patients post-treatment. His methods include physiological, acoustic, and auditory-perceptual measurements. Key emphases include optimizing communication while balancing speech intelligibility, physical/cognitive effort, and associated fatigue. Recent work addresses pandemic impacts on laryngectomy patients, clinician practices during crises, and vocal effort measurement across cultures. His lab investigates articulatory pressures, tracheoesophageal speech dynamics, and dysphagia treatment innovations. Though no specific awards are listed, his contributions to voice rehabilitation and clinical methodologies are significant. Dr. Searl advises on telemedicine applications for Parkinson’s voice therapy, group therapy feasibility, and alaryngeal communication modalities. His lab at MSU collaborates on interdisciplinary projects involving speech-language pathologists, engineers, and oncologists to advance communication restoration technologies.

Samuel Chengمشاهده پروفایل

دانشیار

• Information Theory
• Signal and Image Processing
• Remote Sensing
• +۴ مورد دیگر

Dr. Samuel Cheng is an Associate Professor at the Gallogly College of Engineering , University of Oklahoma , specializing in Electrical and Computer Engineering . He holds a Ph.D. in Electrical Engineering from Texas A&M University (2004), preceded by M.S. and M.Phil. degrees from the University of Hawaii and Hong Kong University of Science and Technology. Education: B.S. (University of Hong Kong, 1995), M.Phil. (HKUST, 1997), M.S. (University of Hawaii, 2000), Ph.D. (Texas A&M, 2004) Professional Experience: Senior Research Engineer at Advanced Digital Imaging Research (2004-2005), prior internships at Microsoft Asia and Panasonic Technologies His research focuses on Information Theory , Signal and Image Processing , and Pattern Recognition , with applications in remote sensing, urbanization analysis, and disaster monitoring. His publications span topics including urban impervious surface mapping , nighttime light analysis , and machine learning for environmental data . His work often integrates multi-source datasets (e.g., Landsat, LiDAR, social media) for spatiotemporal modeling. Technical Expertise: Spectral unmixing, machine learning, thermal remote sensing, GIS integration Key Applications: Power outage detection, vegetation-crime correlation, PM2.5 estimation, smart meter data fusion Dr. Cheng holds three US patents in digital watermarking and is affiliated with IEEE, Sigma Xi, and AAAS. His recent articles demonstrate a trend toward leveraging AI for remote sensing challenges and analyzing urbanization impacts on ecosystems.

Wade Smithمشاهده پروفایل

مدرس ارشد

• Dynamics, vibration and vibration control
• Signal processing
• Modelling and simulation
• +۷ مورد دیگر

Dr. Wade Smith is a Senior Lecturer within the School of Mechanical and Manufacturing Engineering at the University of New South Wales. He is an active member of the WAVES research group (Wear, Aeroacoustics and Vibration in Engineering Systems) and conducts his research in the Tribology and Machine Condition Monitoring laboratory. His primary research interests include vibration-based diagnostics of rotating machinery, prognostics of rotating machinery, gear wear monitoring and prediction, simulation and modeling of rotating machines for diagnostic applications, and signal processing of machine vibration signatures using cyclostationarity. His work has significant applications in industrial machinery health monitoring and predictive maintenance systems. Dr. Smith's recent publications demonstrate a consistent focus on advanced diagnostic techniques for rotating machinery, with particular emphasis on gear systems and bearings. His research integrates traditional mechanical engineering principles with modern signal processing and machine learning approaches to develop more effective condition monitoring solutions. He actively supervises PhD and Masters students on projects related to gear diagnostics, wear monitoring, and vibration analysis. His current research projects include gear diagnostics in planetary gearboxes using internal sensors, gear wear monitoring and prediction, sliding contact-induced vibration studies, and transmission-error-based gear diagnostics. Dr. Smith's laboratory is equipped with specialized facilities including gearbox test rigs (both planetary and parallel configurations), a rolling element bearing test rig, an engine test rig, friction rig, tribometer, high-quality microscope, and extensive instrumentation for vibration analysis. His research has attracted collaborations with institutions including Queensland University of Technology, SpectraQuest (USA), Weir Minerals, University of Technology Sydney, RWTH Aachen University (Germany), and Safran.

Noah Molotchمشاهده پروفایل

استاد

• Snow Hydrology
• Surface Water Hydrology
• Remote Sensing
• +۵ مورد دیگر

Noah Molotch is a Professor of Geography at the University of Colorado Boulder, where he serves as Director of the Mountain Hydrology Group and is a Fellow of INSTAAR (Institute of Arctic and Alpine Research). His research and teaching focus on hydrologic processes in mountainous regions with expertise in snow hydrology, remote sensing, and ecohydrology. Molotch earned his Ph.D. from The University of Arizona in 2004. His research utilizes ground-based observations, remote sensing, and computational modeling to understand hydrological processes, particularly snow distribution and water-carbon-nitrogen fluxes in mountain ecosystems. His work has significant implications for sustainable resource management and environmental policy. His recent publications show a strong focus on snow water equivalent estimation, snowmelt timing impacts on forest productivity, and the development of advanced remote sensing techniques for monitoring mountain hydrology. His research increasingly addresses climate change impacts on water resources, with particular attention to the Western United States. Fellow of INSTAAR Art+Science fellowship in partnership with artist Hannah Taylor Molotch advises numerous graduate students and leads significant research projects including those funded by NASA and NSF. His Mountain Hydrology Group operates field sites across the Western U.S., including Storm Peak Laboratory and Niwot Ridge Long Term Ecological Research Program. The group produces near-real-time snow water equivalent estimates and contributes to the Snow Today website at the National Snow and Ice Data Center.

Regina Raganمشاهده پروفایل

استاد

• Nanomaterials
• Self-Assembly
• Surface-Enhanced Raman Scattering (SERS)
• +۴ مورد دیگر

Regina Ragan is a Professor in the Department of Materials Science and Engineering at the Samueli School of Engineering, University of California, Irvine. Her research focuses on nanomaterials, self-assembly, and surface-enhanced Raman scattering (SERS) for applications in optical communication, energy systems, and biomedical diagnostics. Education: Ph.D. in Applied Physics, California Institute of Technology, 2002 M.S. in Applied Physics, California Institute of Technology, 1998 B.S. in Materials Science and Engineering, University of California, Los Angeles, 1996 Her work integrates scanning probe microscopy and first-principles calculations to study thermodynamic driving forces in self-assembly and structure-function relationships. Recent publications highlight applications in antimicrobial susceptibility testing, environmental monitoring, and plasmonic device fabrication. The Ragan group develops low-cost diagnostic tools using SERS for telemedicine applications. Current lab members include graduate students and postdoctoral researchers working on nanoscale systems from atomic to mesoscale. Scientific Awards: NSF CAREER Award for fundamental studies of biological/inorganic interfaces Research Trends: Recent articles show a focus on SERS-based diagnostics, plasmonic nanoantennas, machine learning-assisted spectral analysis, and scalable synthesis of 3D graphene architectures. Subfields span quantum plasmonics, stress-activated materials, and biofilm monitoring.

Eduardo Mercado IIIمشاهده پروفایل

استاد

• Bioacoustics
• Cognitive Psychology
• Marine Ecology
• +۵ مورد دیگر

Eduardo Mercado III is a Professor in the Department of Psychology at the University at Buffalo, College of Arts and Sciences. His research focuses on bioacoustics, cognitive psychology, and marine ecology, particularly the vocal behavior of humpback whales and its implications for understanding human impact on marine ecosystems. He is also known for his work in perceptual learning, autism spectrum disorder, and comparative cognition. Scientific Awards Guggenheim Fellowship Harvard Radcliffe Institute Fellowship Research Trends His recent publications emphasize bioacoustic analysis of humpback whale songs, including their spectral entropy, cyclical variations, and adaptive adjustments to anthropogenic noise. Additional work explores perceptual learning mechanisms in autism, neural network modeling for acoustic classification, and cognitive processes in canines and rodents. Projects Mercado’s “Singers as Sentinels” project combines acoustic analysis of humpback whale songs with public awareness initiatives about ocean noise pollution. The project will produce a book, Why Whales Sing and Dolphins Don’t , and a web-based interface for public engagement.

Thomas Lippmannمشاهده پروفایل

استاد

• Coastal Engineering
• Physical Oceanography
• Sediment Transport
• +۷ مورد دیگر

Thomas Lippmann is a Professor and Director of the Center of Ocean Engineering within the Department of Earth Sciences at the University of New Hampshire (UNH), part of the College of Engineering and Physical Sciences. He holds dual affiliations with the Ocean Engineering program and retains a research associate position at Scripps Institution of Oceanography’s Integrated Oceanography Division. His career includes roles as a Research Oceanographer at Scripps (1995–1999), Research Scientist at Ohio State University (1999–2008), and a Postdoctoral scholar at the Naval Postgraduate School (1992–1995). Dr. Lippmann earned a BA in Mathematics and Biology from Linfield College (1985), followed by an MS (1989) and PhD (1992) in Bio Oceanography from Oregon State University. His research focuses on shallow water oceanography, hydrography, and bathymetric evolution in coastal waters, combining experimental fieldwork, theoretical analysis, and numerical modeling. Key areas include nearshore processes, inlet dynamics, sediment transport pathways, and effects of sea level rise on estuaries. He has conducted 14 field experiments and accumulated over 18 months of fieldwork experience. His teaching portfolio includes advanced courses such as Beaches and Coasts , Ocean Measurements Lab , and Spectral Analysis of Geophysical Data , reflecting his expertise in nearshore hydrodynamics and coastal engineering. He also advises doctoral research and oversees special programs like Advanced Research Experience . Advising and grants: While no specific grant details are provided, his extensive fieldwork and collaborative projects suggest significant grant-funded research. His academic leadership includes directing UNH’s Ocean Engineering Center and organizing interdisciplinary programs like CLOSES-GAP. No scientific awards are explicitly mentioned in the texts. Labs and teams: Active in the Integrated Oceanography Division (SIO) and the Byrd Polar Research Center. Collaborates with institutions like Ohio State University, Naval Postgraduate School, and the University of New Hampshire’s Center for Coastal and Ocean Mapping. His work integrates with the Great Bay Estuary’s tidal energy test site and remote sensing projects.

• Medical Image Reconstruction
• Computed Tomography
• Positron Emission Tomography
• +۶ مورد دیگر

Professor Jerome Liang is a distinguished faculty member at Stony Brook University's Renaissance School of Medicine, holding professorships in Radiology, Biomedical Engineering, Electrical and Computer Engineering, and Computer Science. He serves as Co-Director of Radiology Research and has established himself as a leading expert in medical imaging reconstruction techniques. Dr. Liang's educational background includes a Ph.D. in Physics from City University of New York, postdoctoral training at Duke University, and fellowship at Albert Einstein College of Medicine. His undergraduate degree in Modern Physics was obtained from Lanzhou University in China. His primary research interests focus on advanced medical imaging techniques, particularly low-dose computed tomography image reconstruction, quantitative SPECT reconstruction, high-resolution PET imaging, tissue segmentation from multi-spectral images, computer-aided diagnosis systems, and virtual colonoscopy development. His work bridges engineering principles with clinical applications to improve diagnostic imaging capabilities while reducing radiation exposure. Analysis of his recent publications reveals a strong focus on machine learning applications in medical imaging, particularly in polyp classification, dual-energy CT spectral analysis, and virtual endoscopy. His research consistently aims to enhance diagnostic accuracy while optimizing radiation dose and improving visualization techniques for various medical conditions. 1981 China-US Physics Examination and Application Program (CUSPEA) Winner (Top 25 among 250,000 candidates) 1990 NIH First Investigator Award 1996 American Heart Association Established Investigator Award 1996 Radiological Society of North America Certificate of Merit Award 2002 SUNY Chancellor's Entrepreneur Award 2007 IEEE Society Fellow 2011-2013 SBU, BNL and CSHL Certificates of Excellence in Research and Invention 2013 Stony Brook School of Medicine Award for Excellence in Translational Research Dr. Liang has secured significant research funding including NIH/NCI R01 grants for "Advanced Virtual Colonoscopy for Early Cancer Screening" and "Radiogenomics of Colorectal Polyps." He currently leads active protocols including IRB 93995-MODCR005 focused on integrating virtual and optical colonoscopies with pathological analysis. His laboratory (IRIS - Imaging Research and Informatics) continues to advance medical imaging technology while mentoring the next generation of researchers in this critical field.