جست‌وجوی استاد و پژوهشگر

Philip S. Yuمشاهده پروفایل

استاد

• Data Mining
• Big Data
• Privacy-Preserving Data Publishing
• +۹ مورد دیگر

Philip S. Yu is a Distinguished Professor in the Department of Computer Science at the University of Illinois at Chicago and holds the Wexler Chair in Information Technology. Previously, he led the Software Tools and Techniques department at IBM Thomas J. Watson Research Center. Education: B.S. in Electrical Engineering, National Taiwan University M.S. and Ph.D. in Electrical Engineering, Stanford University M.B.A., New York University His research spans data mining , big data , social networks , privacy-preserving data publishing , graph/network mining , recommender systems , and deep learning . He has authored over 970 papers with 74,500+ citations and an H-index of 127. Recent work focuses on heterogeneous graph representation, quantum walks in network analysis, and federated unlearning. Scientific Honors: ACM SIGKDD 2016 Innovation Award IEEE Computer Society 2013 Technical Achievement Award IEEE ICDM 2003 Research Contributions Award IEEE Region 1 Award (1999) UIC Research of the Year (2013) IBM Master Inventor with 300+ patents AI 2000 Most Influential Scholar Honorable Mentions (2024-2025) He served as Editor-in-Chief for ACM Transactions on Knowledge Discovery from Data and IEEE Transactions on Knowledge and Data Engineering , and on steering committees for ACM KDD and IEEE Data Mining. His work bridges theoretical advances in graph neural networks , deep learning , and privacy-preserving systems with applications in healthcare, social media, and enterprise analytics.

Mahdi Khodayarمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۴ مورد دیگر

Mahdi Khodayar is an Assistant Professor of Computer Science at the University of Tulsa . He holds a Ph.D. in Electrical Engineering from Southern Methodist University (2020) and M.Sc./B.S. degrees in Artificial Intelligence and Software Engineering from K.N. Toosi University of Technology (2015, 2013). His research focuses on AI and machine learning applications in power systems, transportation systems, computer vision, and spatiotemporal pattern recognition. B.Sc. in Computer Engineering (2013), K.N. Toosi University of Technology M.Sc. in Artificial Intelligence (2015), K.N. Toosi University of Technology Ph.D. in Electrical Engineering (2020), Southern Methodist University Khodayar’s research bridges deep learning with energy systems , including fault detection in power grids, renewable energy forecasting, and traffic scene understanding. His work leverages graph neural networks , reinforcement learning , and generative models for robust spatiotemporal analysis. Recent publications highlight his focus on graph-based architectures for power systems, hybrid deep reinforcement learning in energy forecasting, and unsupervised domain adaptation in remote sensing. His work integrates physics-informed modeling with probabilistic frameworks . Scientific Awards : NSF ECCS Division Funding (2022) US DOT FHWA Grant (2023) Zelimir Schmidt Award for Early Career Research (2023) Honors Student Award (2015), K.N. Toosi University Khodayar has been funded by the NSF , US Department of Transportation , and the TU Cyber Fellows program . He serves as an associate editor for IEEE Transactions on Transportation Electrification and other journals.

Michael McAlpineمشاهده پروفایل

استاد

• 3D Printing
• Nanotechnology
• Biomedical Engineering
• +۴ مورد دیگر

Michael McAlpine is a Professor in the Mechanical Engineering department at the University of Minnesota . He also holds affiliations with the Biomedical Engineering and Electrical and Computer Engineering departments. His research focuses on 3D printing functional materials & devices , Nanoscale inks , Biomedical devices , Bioelectronics , and Flexible Microsystems . Research Interests : 3D Printing, Biomedical Engineering, Nanotechnology, Flexible Electronics, Microfluidics Labs : ME 361/363 Contact : mcalpine@umn.edu , (612) 626-3303, ME 117 Recent Research Trends include 3D Printed Biomedical Devices , Flexible Electronics , and Bioprinting Applications . His work spans from Spinal Organoid Formation to Programmable Drug Release Capsules . Scientific Award : Circulation Research 2020 Best Manuscript Award

Yao Qinمشاهده پروفایل

استادیار

• Machine Learning
• Adversarial Robustness
• Out-of-Distribution Generalization
• +۵ مورد دیگر

Yao Qin is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara (UCSB), with dual affiliation in the Department of Computer Science. She concurrently serves as Co-Director of the REAL AI Initiative at UCSB and holds a Senior Research Scientist position at Google DeepMind, where she contributes to the Gemini Multimodal project. Her academic credentials include a PhD in Computer Science and Engineering from the University of California, San Diego (advised by Prof. Garrison W. Cottrell) and a BS in Electrical Engineering from Dalian University of Technology. During her doctoral studies, she completed internships with pioneering researchers Geoffrey Hinton and Ian Goodfellow. Dr. Qin's research program centers on machine learning robustness, with emphasis on adversarial robustness, out-of-distribution generalization, and fairness. She develops reliable AI systems specifically for healthcare applications, with diabetes management as a primary focus. Her lab explores critical themes including AI safety in multimodal models and diabetes-specific AI solutions, particularly exercise metabolism modeling and glycemic effect prediction. Recent publications reveal a strong trajectory in robust machine learning with cross-domain applications. Her work consistently bridges theoretical robustness concepts with practical healthcare implementations, particularly in diabetes care. Key publication venues include CVPR, ICML, NeurIPS, and ICLR, with notable contributions to out-of-distribution detection, adversarial transfer learning, and multimodal AI safety. Her distinguished recognition includes: EECS Rising Star at MIT (2021) UCSB Regents' Junior Faculty Fellowship Award Helmsley Charitable Trust award for Type 1 diabetes research UCSB Faculty Research Grant American Diabetes Association Abstract Award (ADA-2025) Dr. Qin actively mentors four PhD students—Mehak Dhaliwal, Andong Hua, Kenan Tang, and Youngseok Yoon—on projects spanning LLMs for diabetes, multimodal robustness, and generative time-series modeling. Her research is funded by the Helmsley Charitable Trust and UCSB, with recent grants supporting exercise-specific AID algorithms for diabetes management. As Co-Director of the REAL AI Initiative, she leads a research ecosystem focused on developing reliable artificial intelligence. Current lab activities include organizing workshops at NeurIPS-2024 (AdvML-Frontiers and AIM-FM) and developing next-generation diabetes management tools through collaborations with medical institutions.

Benyuan Liuمشاهده پروفایل

استاد

• Data and Computer Communication Networks
• Mobile and Wireless Networks
• Internet Technologies & Applications
• +۳ مورد دیگر

Benyuan Liu is a Professor at the Miner School of Computer and Information Sciences within the Kennedy College of Sciences at the University of Massachusetts Lowell . He serves as Director and Graduate Coordinator for Ph.D. programs, with expertise in Data and Computer Communication Networks, Mobile and Wireless Networks, and Internet Technologies & Applications. Education: B.S., University of Science and Technology of China M.S., Yale University Ph.D., University of Massachusetts Amherst His research focuses on Artificial Intelligence in Medical Imaging , Deep Learning for Endoscopy , and Edge Computing Systems . Recent work includes automated lesion detection, 3D reconstruction from sensor data, and predictive models for financial and reproductive health domains. The 15 most recent publications highlight applications of deep learning in medical diagnostics (thyroid nodules, gastric lesions, dental caries), computer vision (attention mechanisms, transformers), and financial technology (market psychology analysis). Technical themes include mmwave radar processing, diffusion models for synthetic data, and multi-scale feature extraction. Benyuan Liu leads the Computer Networking Lab and CHORDS initiative at UMass Center for Digital Health. His work bridges network optimization with healthcare AI , emphasizing real-time systems and portable diagnostics.

Eduardo Rochaمشاهده پروفایل

استاد

• Microbial Evolutionary Genomics
• Genome Organization
• Mobile Genetic Elements
• +۱۳ مورد دیگر

Eduardo Rocha is a Professor and Head of the Microbial Evolutionary Genomics laboratory at the Institut Pasteur, within the Department of Genomes and Genetics. His research integrates bioinformatics, molecular evolution, and genomics to understand bacterial genome organization and dynamics, particularly focusing on mobile genetic elements and their role in adaptation and antibiotic resistance. His research interests include microbial evolutionary genomics, genome organization, horizontal gene transfer, mobile genetic elements (plasmids, phages, integrons), bacterial pathogen evolution, and computational biology. His work lies at the intersection of molecular evolution, population genetics, and molecular epidemiology, with strong translational implications for understanding antimicrobial resistance and infectious disease emergence. The recent publications highlight a consistent focus on mobile genetic elements, genome plasticity, and bacterial adaptation. Key themes include the role of integrons and CRISPR-Cas systems in bacterial immunity, plasmid-mediated spread of antibiotic resistance, phage-plasmid interactions, and the development of bioinformatics tools for microbial genomics. These works frequently appear in high-impact journals such as Science , Nature Microbiology , and PLoS Biology , reflecting significant contributions to the field. Eduardo Rocha leads multiple funded research projects, including ERC-2011-StG EVOMOBILOME, ANR Magisbac, and ANR SHAPE. He has developed and maintains several widely used bioinformatics software tools: IntegronFinder, MacSyFinder, PanACoTA, SatelliteFinder, CapsuleFinder, TXSScan, and others. He mentors a large team of PhD students, postdoctoral researchers, and engineers, and has supervised numerous former students who now hold independent research positions worldwide. Eduardo Rocha has received research funding from major agencies including the European Research Council (ERC) and the French National Research Agency (ANR). His work is central to the LabEx IBEID and the INCEPTION convergence program, where he serves on the steering committee, promoting interdisciplinary research in infectious disease emergence. His laboratory, part of the Genomes and Genetics department, actively contributes to microbial evolutionary genomics through both methodological development and biological discovery. The team participates in networks such as Phages.fr, GDR BIM, and GDR AIEM, reinforcing its collaborative and integrative approach.

• Biomaterials
• Tissue Engineering
• Regenerative Medicine
• +۵ مورد دیگر

João F. Mano is a Full Professor at the Department of Chemistry, University of Aveiro, and Director of the Doctoral Program on Biotechnology. He leads the COMPASS Research Group and serves as Vice-Director at CICECO - Aveiro Institute of Materials. His academic appointments include Invited Professor at University of Lorraine (France), Visiting Professor at KAIST (South Korea), and Adjunct Professor at Ajou University (South Korea). Education: PhD in Chemistry (1996, Technical University of Lisbon); D.Sc. in Tissue Engineering, Regenerative Medicine and Stem Cells (2012, University of Minho) Research Interests focus on Biomaterials for Regenerative Medicine , integrating Nanotechnology , Microtechnology , and Biofabrication . His group develops Bioinspired Materials using polymer chemistry, Decellularized Extracellular Matrix , and 3D Bioprinting to engineer Cell Microenvironments for therapeutic applications. Recent Publications highlight advancements in Human-Derived Hydrogels , Photopolymerizable Scaffolds , Magneto-Responsive Biomaterials , and Programmable Bioinks . Trends show emphasis on Organ-on-a-Chip integration, Smart Living Materials , and Green Bioprinting methodologies. Scientific Awards include: European Research Council Advanced Grants (2015, 2020) Fellow at IUPAC, European Academy of Sciences, and American Institute of Medical and Biological Engineering ERC Proof of Concept Grants Doctor Honoris Causa from University of Lorraine and Utrecht UNESCO Chair on Biomaterials George Winter Award (European Society for Biomaterials) Supervisions & Collaborations encompass 74+ MSc, 26+ PhD students, and 40+ postdocs. He co-founded METATISSUE and CELLULARIS Biomodels , and serves as Editor-in-Chief of Materials Today Bio .

• Biomedical Engineering
• Materials Science
• Sensors Technology
• +۷ مورد دیگر

Rahim Rahimi is an Assistant Professor of Materials Engineering at Purdue University, associated with the College of Engineering. His research focuses on advanced materials for biomedical applications, environmental sensing, and flexible electronics. Key interests include developing smart sensors for healthcare, antibacterial coatings for medical implants, and sustainable agricultural monitoring systems. Research emphasizes targeted drug delivery systems via smart capsules, environmental sensor networks for water quality and soil health, and nanotechnology applications in wearable devices. Notable projects include oxygen-generating surgical meshes for wound healing and low-cost wireless sensors for precision agriculture. His work bridges materials science with clinical and environmental challenges, leveraging plasma deposition techniques and nanomaterial functionalization. Recent efforts focus on self-calibrating sensors and integrating machine learning for manufacturing optimization. No scientific awards are explicitly listed in the provided information. His advisory role and grant activities are inferred through his research outputs in materials engineering and biomedical innovation. Rahimi collaborates across disciplines within Purdue's engineering ecosystem, contributing to labs focused on bio-inspired materials and flexible electronics. Future work aims to advance implantable medical devices and scalable sensor technologies for global health applications.

Annemieke Apergis-Schouteمشاهده پروفایل

مدرس

• Obsessive Compulsive Disorder
• Preoccupied Thinking
• Procrastination
• +۷ مورد دیگر

Dr. Annemieke Apergis-Schoute is a Lecturer in Psychology (Teaching and Research) at Queen Mary University of London, affiliated with the School of Biological and Behavioural Sciences and the Centre for Brain and Behaviour. Her research focuses on obsessive-compulsive disorder (OCD), cognitive flexibility, prefrontal mechanisms, and student mental health. She holds a PhD from New York University, where her early work explored threat learning in rats and humans using fMRI. Subsequent roles at the University of Cambridge and UCL expanded her expertise into clinical OCD studies, including deep brain stimulation trials. Her research investigates how prefrontal control deficits and inflexible learning contribute to OCD and related disorders, with a focus on adolescents and young adults. Collaborations include pioneering DBS studies targeting basal ganglia regions to reduce compulsive behaviors. She also explores connections between brain function, interoception, and mental health in daily decision-making contexts. Key publications analyze reversal learning deficits in OCD under serotonergic modulation, neuroimaging markers of cognitive rigidity, and developmental trajectories of compulsivity. Her work bridges basic neuroscience with translational clinical interventions, emphasizing early intervention strategies and cognitive-behavioral approaches.

• Sensors
• Nanotechnology
• Liquid Metals
• +۴ مورد دیگر

Professor Kourosh Kalantar Zadeh is the Head of School of Chemical and Biomolecular Engineering at the University of Sydney. He also holds adjunct professorships at UNSW and RMIT. His research focuses on sensors, nanotechnology, liquid metals, and medical devices. He has over 500 publications and is a member of prestigious editorial boards. **Awards**: Includes AAAS Fellowship (2021), Robert Boyle Prize (2020), Walter Burfitt Prize (2019), and multiple Clarivate Highly Cited recognitions. His work has been featured in over 350 media outlets, including BBC, Time Magazine, and Nature. **Research**: Innovations include ingestible gas-sensing capsules, smart paints, and liquid metal-based catalysis. Supervises 10 PhD students in areas like functional materials and medical devices. **Grants**: Leads ARC Laureate Fellowship projects on liquid metals and NHMRC grants for gut metabolite sensing. Part of the ARC Centre of Excellence in Future Low-Energy Electronics. **Engagement**: Media engagements highlight breakthroughs in sensors, liquid metals, and environmental technologies. Collaborates across disciplines to translate research into practical applications.

Yi David Juمشاهده پروفایل

پژوهشگر ارشد

• Nanotechnology
• mRNA Therapeutics
• Lipid Nanoparticle Formulation
• +۴ مورد دیگر

Dr. Yi David Ju is a Senior Research Fellow at RMIT University's School of Science and an ARC DECRA Fellow at La Trobe University's School of Cancer Medicine. He leads the Nanomedicine and Gene Therapeutics Laboratory at the Olivia Newton-John Cancer Research Institute (ONJCRI) and holds Honorary Fellowships at the University of Melbourne's Department of Microbiology & Immunology and Chemical Engineering. PhD from University of Melbourne (2017, Frank Caruso) 2017–2021 : Research Fellow at University of Melbourne 2021 : Vice-Chancellor’s Postdoctoral Fellow at RMIT 2023 : Visiting Researcher at University of Manchester's Nanomedicine Lab His research focuses on Bio-Nano Interactions , particularly Nanoparticle-Immune System dynamics, Lipid Nanoparticle Engineering for mRNA Delivery , and Poly(ethylene glycol) Alternatives . Key contributions include stealth nanoparticles for prolonged circulation, anti-PEG antibody dynamics in vaccine development, and patient-specific targeting models for chronic lymphocytic leukemia . Recent publications analyze hybrid immuno-PET-MRI probes for inflammation monitoring, zwitterionic PEG nanoparticles for reduced immunogenicity, and RAFT polymer-based LNPs for enhanced gene delivery . His work also explores supramolecular DNA-polyphenol assemblies and metal-phenolic coatings for controlled drug release . Scientific Awards ： 2023 ACIS ECR Lectureship Finalist, 2023 ACS Nano Impact Award 2022&2023 RMIT Enabling Capability Platform Funding 2021 CBNS Most Significant Publication Award 2020 CBNS Career Development Award 2019 Outstanding Postdoctoral Researcher Award 2019 Nanoscale Advances Oral Prize 2017 Reviewer Excellence Award for Chemistry of Materials 2014 Best Tutor Award Professional Roles ： Associate Editor, Journal of Materials Science Committee Member, Royal Australian Chemical Institute (Victorian Branch) Active Member, Australasian Colloid and Interface Society

• Machine Learning-Informed Medicines Optimization
• Computational Pharmaceutics-Informed Drug Delivery
• Digitalisation of Pharmacy Practice
• +۲ مورد دیگر

Dr. Harriet Bennett-Lenane is a Lecturer in Clinical Pharmaceutics at the School of Pharmacy, University College Cork (UCC). She holds a BSc(Pharm) from Trinity College Dublin (2017), an MPharm from the Royal College of Surgeons in Ireland (2018), and a PhD in Pharmaceutics from UCC (2022), supported by an Irish Research Council Postgraduate Scholarship. Her research focuses on machine learning applications in drug formulation, computational pharmaceutics, and digital pharmacy practice. She has industry experience in Quality Assurance and Regulatory Affairs roles at Eli Lilly, MSD, and Clinigen. Research Interests include optimizing medicines using AI, improving drug delivery systems, and enhancing pharmacy services for vulnerable patients. Her work bridges academia and industry, emphasizing translational research. Notable Awards: Gold Medal for Pharmaceutics (Trinity College Dublin, 2017), Irish Research Council Postgraduate Scholarship (2018), and Entrance Exhibition Scholar (Trinity College Dublin, 2014). Teaching: Focuses on integrating research-led, active learning approaches in Clinical Pharmacy and Pharmaceutics.

Sören Laueمشاهده پروفایل

استاد

• Machine Learning
• Optimization Algorithms
• GPU Computing
• +۳ مورد دیگر

Prof. Dr. Sören Laue is a Professor of Machine Learning at the University of Hamburg's Department of Informatics. His research focuses on optimization algorithms, machine learning frameworks, and high-performance computing. He leads the Machine Learning research group and developed the GENO optimization framework and the Matrix Calculus toolset. His work emphasizes GPU acceleration, tensor operations, and scalable solutions for classical machine learning problems. Projects: GENO solver (Python-based optimization), Matrix Calculus (derivative computation), and SQL-based tensor operations. Key Research Themes: Optimization frameworks, GPU computing, neural network scalability, and algorithm design. Selected recent publications highlight contributions to tensor calculus benchmarks, GPU-optimized machine learning pipelines, and novel optimization methods. His work bridges theoretical foundations and practical software tools for the machine learning community.

Justin Leidwangerمشاهده پروفایل

دانشیار

• Maritime Archaeology
• Mediterranean Archaeology
• Roman and Late Antique Archaeology
• +۵ مورد دیگر

Justin Leidwanger is an Associate Professor of Classics at Stanford University with a courtesy appointment in Oceans at the Doerr School of Sustainability, specializing in Mediterranean maritime archaeology through fieldwork in southeast Sicily and southwest Turkey. His educational background includes: Ph.D. in Art and Archaeology of the Mediterranean World from the University of Pennsylvania (2011) M.A. in Nautical Archaeology and Anthropology from Texas A&M University B.A. in History & Classical Studies from Loyola University Chicago Leidwanger's research centers on Mediterranean mobilities, maritime communities, and exchange systems from the Roman period through late antiquity, using shipwrecks and port sites to analyze socioeconomic dynamics. His work integrates ceramic analysis, port network studies, and digital heritage methods to explore ancient technologies of distribution and long-term maritime interactions. Recent publications reveal consistent focus on Roman/late antique maritime economies with growing emphasis on digital documentation (3D modeling, GIS) and contemporary relevance through migration studies. Key trends include transport amphorae standardization, underwater survey methodologies, and the intersection of ancient maritime heritage with modern migration patterns in the central Mediterranean. Leidwanger actively advises students in classical archaeology while leading major field projects including the Marzamemi 'church wreck' investigation (2013-2019) and ongoing 'U Mari research in Sicily. His work combines underwater survey, community-based archaeology, and heritage activism addressing both ancient tuna fishing traditions (mattanza) and contemporary migration routes. He directs the Maritime Archaeology and Digital Heritage Lab (MEDLab) at Stanford's Archaeology Center, which supports advanced digital modeling (photogrammetry, laser scanning, network analysis) and ceramic analysis (petrography, pXRF, computational morphometrics) for field research and museum collaborations.

Chia Leeمشاهده پروفایل

استاد

• Microbiology
• Immunology
• Bacterial Pathogenesis
• +۳ مورد دیگر

Chia Lee, Ph.D., is a Professor in the Department of Microbiology and Immunology at the University of Arkansas for Medical Sciences (UAMS) College of Medicine. Their research focuses on understanding the molecular mechanisms of Staphylococcus aureus pathogenesis, particularly the regulation of virulence factors such as capsule and α-toxin. They completed their Ph.D. and postdoctoral training at Kansas State University. Key research interests include bacterial virulence regulation, antibiotic resistance, biofilm formation, and the transition from carriage to invasive disease. Their lab employs structural biology, mutagenesis, and proteomics to study regulatory networks like ClpC, SigB, and small RNAs. Recent work involves developing rat models for studying implant-associated biofilm infections. Publications highlight advances in understanding capsule regulation via SarZ, MgrA, and RbsR, as well as α-toxin regulation and biofilm matrix composition. Collaborators include M. G. Lei, R. K. Gupta, and D. D. Gudeta. Research has implications for developing novel therapeutics against staphylococcal infections. Lab activities emphasize translational research bridging basic science and clinical applications, with a focus on elucidating how regulatory pathways control virulence expression during infection. Current projects address in vivo regulatory dynamics and disease transition mechanisms.