جستجوی استاد راهنمای دانشگاهی

Martin van Ittersumمشاهده پروفایل

استاد

• Agricultural Systems Analysis
• Circular Agriculture
• Climate Change Mitigation
• +۳ مورد دیگر

Prof. Martin van Ittersum is a Professor at the Department of Plant Production Systems at Wageningen University, with a visiting professorship at the Swedish University of Agricultural Sciences. He holds a PhD in Agricultural and Environmental Science from Wageningen University and has led major international projects, including the Global Yield Gap Atlas (GYGA) since 2011. His research focuses on agricultural systems analysis, yield gap reduction, climate change adaptation, and circular food systems. He co-chaired the 1st and 4th International Conferences on Global Food Security and chairs the 5th edition in 2024. He is a member of Wageningen University's Academic Board and has authored over 200 peer-reviewed papers, earning 'Highly-Cited Researcher' status since 2015. His work integrates agronomy, modeling, and policy evaluation to address global food security challenges. Key contributions include advancing phosphorus scarcity solutions, sustainable intensification in Africa, and environmental analyses of circular agriculture. He has supervised numerous MSc and PhD students globally and leads initiatives like the Environmental Analysis of Future Scenarios of Circularity in the North of the Netherlands. His research bridges field-to-global scales, emphasizing systemic approaches to agricultural sustainability.

Wenqi Shiمشاهده پروفایل

استادیار

• Artificial Intelligence in Healthcare
• Precision Medicine
• Translational Medicine
• +۳ مورد دیگر

Dr. Wenqi Shi serves as an Assistant Professor at the Peter O’Donnell Jr. School of Public Health at UT Southwestern Medical Center. Her research focuses on the integration of artificial intelligence with healthcare, particularly advancing algorithms and systems for precision medicine. She specializes in working with multi-modal patient data including EHRs, medical notes, imaging, and genomics, with dedicated applications in pediatric healthcare, cancer, and rare diseases. Her research interests include developing large language models for translational medicine, creating agentic AI and generative models for biomedical discovery, and establishing responsible AI practices to enhance clinical outcomes. Publication trends show extensive work in explainable AI, clinical decision support systems, and multi-modal data integration, with recent emphasis on retrieval-augmented language models and causal inference methodologies. Dr. Shi obtained her Ph.D. from the Georgia Institute of Technology prior to joining UT Southwestern.

Hoda Hassanمشاهده پروفایل

دانشیار

• Computer Networks
• Mobile Ad Hoc Networks (MANETs)
• Artificial Intelligence
• +۱ مورد دیگر

Hoda Hassan is an Associate Professor in the Department of Information Sciences and Technology at George Mason University. Her work bridges theoretical and applied domains in computer networks, Mobile Ad Hoc Networks (MANETs), and the convergence of Artificial Intelligence (AI) and the Internet of Things (IoT). Education : PhD in Computer Engineering from Virginia Tech (2010), MSc and BSc in Computer Science from the American University in Cairo (2005, 1992). Research Interests focus on designing intelligent and secure network systems. She has developed innovative frameworks, including a BLE computer-aided design toolkit for MANETs, which was commercialized by Skymind Malaysia. Her work spans AI integration in IoT, anomaly detection, cloud computing models, and network architecture evolution. Academic Leadership includes pioneering roles in founding The Knowledge Hub (TKH) Universities in Egypt and leading the Computing and Computer Science Program at Coventry University's UK offshore branch (2019–2022). Her research has been supported by a significant 2 million Egyptian Pound grant from ITAC Egypt (2015–2017).

• Microelectronics
• Analog/RF/Mixed-Signal Circuits
• Digital Integrated Circuits
• +۳ مورد دیگر

Dr. Vishnu Unnikrishnan is an Assistant Professor at the Department of Electrical Engineering, Tampere University, within the Faculty of Information Technology and Communication Sciences. His research focuses on energy-efficient high-performance analog/digital/RF integrated circuits and systems in nanometer-scale CMOS technologies. Key areas include time-based data conversion, high-speed serial links, and 5G/6G wireless transceivers. He leads research on analog interfaces using digital/switch components and collaborates with the SoC Hub ecosystem to bridge academic and industrial interests in system-on-chip design. He has secured significant funding, including an EU Marie Curie ITN grant (SMArT) worth €818k and an Academy of Finland Project (2021) of €821k. His work spans over 40 peer-reviewed publications, emphasizing innovations in time-based ADCs, beamforming receivers, and RF system design. Dr. Unnikrishnan actively supervises doctoral and postdoctoral researchers, offers paid master's theses and summer jobs in IC design, and collaborates with industry through the SoC Hub. His research aims to advance cross-technology portable analog interfaces and high-performance mixed-signal systems.

Stefano Morettiمشاهده پروفایل

استاد

• High Energy Physics
• Particle Phenomenology
• Collider Physics
• +۵ مورد دیگر

Professor Stefano Moretti holds a Professorship at the University of Southampton's Department of Physics & Astronomy and is a Full Professor at Uppsala University's Theoretical Particle Physics group. He is a member of the Southampton High Energy Physics (SHEP) group and the Southampton Theory Astrophysics and Gravity (STAG) Research Centre. His research focuses on particle phenomenology, particularly collider physics, with over 550 publications and 34,000 citations. He is also a Visiting Staff at RAL PPD and part of the CMS experiment at CERN. Education: PhD from the University of Torino, followed by postdoctoral roles at the University of Cambridge, Rutherford Appleton Laboratory (RAL), and the University of Oxford. He joined Southampton in 2003 via an STFC Advanced Fellowship. Research Interests : Standard Model (QCD/EW interactions), Supersymmetry, Non-minimal Higgs Models, Monte Carlo Event Generators, and Higher Order Corrections. He authored textbooks on Supersymmetry and SM Phenomenology. Awards : 2024 Lilly and Sven Thuréus Prize (Sweden), 2018 Honorary Doctorate from Uppsala University, and 2025 Breakthrough Prize in Fundamental Physics (shared with LHC experiments). Teaching : Coordinates the UG module PHYS2006 (Classical Mechanics) and teaches the PG Phenomenology course within the NExT PhD School. Grants/Projects : Lead researcher on multiple STFC, Royal Society, and EU-funded projects. Active in Horizon Europe evaluations and UK REF2021 panel work. Labs/Teams : Director of the NExT Institute, member of SHEP and STAG, collaborates with CMS at CERN, and advises on policy for science assessment frameworks.

Shelley Xuelian Mengمشاهده پروفایل

دانشیار

• Remote Sensing
• Coastal Dynamics
• Wetland Restoration
• +۵ مورد دیگر

Introduction Dr. Shelley Xuelian Meng is an Associate Professor in the Department of Geography and Anthropology at Louisiana State University (LSU), part of the College of Humanities & Social Sciences. Her research focuses on leveraging remote sensing technologies (e.g., UAVs, LiDAR, multispectral imaging) to study coastal dynamics, wetland restoration, vegetation health, and precision agriculture. Education Ph.D. in Geography and GIScience, Texas State University (2010) M.S. in GIS and Cartography, Chinese Academy of Sciences (2003) B.E. in Information Engineering, Wuhan University (2000) Research Interests Meng’s work emphasizes the application of advanced geospatial technologies to address environmental challenges. Key areas include: Coastal wetland die-off and restoration using multi-scale remote sensing LIDAR and UAV-based terrain and vegetation mapping Object-oriented classification algorithms for environmental monitoring GIS integration for precision agriculture and disaster management Awards & Recognition 2023 Tipton Team Award (for Roseau cane die-off research) 2014 Best Paper Award in Remote Sensing CPGIS Young Scholar (2012) Grants & Projects Notable funded projects include: USDA-funded Roseau cane die-off studies ($1.6M+ across multiple years) Development of LiDAR and thermal sensing tools for coastal research Acquisition of terrestrial LiDAR equipment for multidisciplinary studies Labs & Affiliations Meng directs the Technology Intensive Geospatial and Remote Sensing (TIGeRS) Lab , which houses advanced equipment including drones, LiDAR scanners, and multispectral sensors. The lab collaborates with the LSU Coastal Studies Institute and other institutions.

Dongmei Chenمشاهده پروفایل

استاد

• Geomatics
• Environmental Science
• GIS Applications
• +۴ مورد دیگر

Dr. Dongmei Chen is a Professor in the Department of Geography and Planning at Queen's University, affiliated with the Faculty of Arts and Science. She holds cross appointments in the School of Environmental Studies and the Beaty Water Research Centre. Her research focuses on understanding human-environment interactions through GIS and remote sensing, with specialties in land use modeling, climate change impacts, and spatial data analysis. Education: PhD in Geography (2001, San Diego State University/UCSB); M.Sc. in GIS/Remote Sensing (Chinese Academy of Sciences); B.Sc. in Geography (Peking University). Pre-Queen's career included work as a GIS product specialist at ESRI. Research interests include geomatics, environmental science, and applying machine learning to remote sensing challenges. Recent work addresses flood susceptibility modeling, urban sprawl analysis, and spatial-temporal disease risk. Her interdisciplinary approach bridges geospatial technologies with environmental and social science. Active in research centers like LaGISA, she explores topics like air pollution monitoring and spatial data privacy. Grants and advising are integral to her role, though specific details are not detailed here. Collaborations span global contexts, including Brazil, Thailand, and China.

Sisi Zhouمشاهده پروفایل

پژوهشگر

• Quantum Metrology
• Quantum Error Correction
• Quantum Learning
• +۲ مورد دیگر

Sisi Zhou is a Research Faculty member at the Perimeter Institute for Theoretical Physics, specializing in quantum information science. Her work focuses on quantum metrology, quantum error correction, and quantum learning, with a particular emphasis on advancing methodologies for noisy quantum systems. Her research explores theoretical frameworks to enhance precision in quantum measurements, optimize error-correcting codes, and apply machine learning techniques to photonic platforms. Recent contributions include studies on non-Markovian metrology, Gaussian measurement limitations, and entanglement-enabled protocols for bosonic channels. Zhou has delivered seminars at institutions such as the Banff International Research Station and the University of Calgary, addressing topics like quantum metrological limits in noisy environments and error mitigation strategies for near-term quantum processors.

Salem S. Gharbiaمشاهده پروفایل

استاد

• Climate Resilience
• Environmental Monitoring
• Environmental Modeling
• +۳ مورد دیگر

Dr. Salem S. Gharbia is the Head of the Department of Environmental Science and a Principal Investigator at Atlantic Technological University (ATU). He leads the Centre for Environmental Research Innovation and Sustainability (CERIS) and co-founded the Centre for Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE). His research focuses on climate resilience, environmental monitoring, and modeling, with expertise in Geographic Information Systems (GIS), wireless sensor networks, and climate change impacts. Dr. Gharbia coordinates major EU projects like Horizon 2020 SCORE and has secured over €14M in research funding. He holds a PhD in Environmental Engineering from Trinity College Dublin, where he received the prestigious Ussher Award. His work spans collaborations with the Irish EPA, Horizon Europe, and the Marine Institute, addressing coastal flooding, microplastic detection, and sustainable agriculture. Education: PhD in Environmental Engineering, Trinity College Dublin. Research interests include climate adaptation strategies, urban resilience, and innovative sensor technologies for environmental monitoring. His projects emphasize interdisciplinary approaches to address global challenges such as rising sea levels, extreme rainfall, and coastal erosion. Awards: Trinity College Ussher Award. Grants: Over €14M secured over five years for projects like EmpowerUS, Pro-climate, and WaterFutures. Advising: Accepting PhD students in environmental science and engineering. Labs: CERIS and MISHE, focusing on climate modeling and environmental systems.

• Mechanical Engineering
• Vibration Analysis
• Rotordynamics
• +۳ مورد دیگر

Sampo Laine is a Visiting Professor at the Department of Energy and Mechanical Engineering at Aalto University, with affiliations in Mechatronics. His expertise focuses on vibration analysis, rotordynamics, and powertrain systems, contributing to the UN Sustainable Development Goals related to Industry, Innovation, and Infrastructure (SDG 9). He holds a Doctor of Science (Tech) in Mechanical Engineering (2025), a Master of Engineering (2021), and a Bachelor of Engineering (2020), all from Aalto University. His research explores lateral and torsional vibrations in rotating machinery, electromagnetic influences on torsional systems, and vibration mitigation through active control strategies. Notable contributions include the OpenTorsion Python library for torsional vibration analysis and studies on semi-active foundation stiffness control in rotor systems. His work bridges mechanical design, digital twin technology, and collaborative engineering practices. Laine’s publications span topics such as wire rope isolators, aerostatic measurement systems, and dynamic modeling of coupled electromechanical systems. His research emphasizes practical applications in industrial machinery, automotive powertrains, and manufacturing processes. Collaborations have addressed challenges in winder dynamics, paperboard quality assessment, and roll geometry optimization. No scientific awards are explicitly listed in the provided materials. His advising and grants focus on doctoral research in mechanical systems, with a recent doctoral thesis titled Lateral and torsional vibrations in variable speed rotating machinery (2025). He is affiliated with Aalto’s Mechatronics and Energy Engineering research groups, contributing to interdisciplinary projects in vibration analysis and automated design methodologies.

Mostafa Mohammadiمشاهده پروفایل

استادیار

• Neurorehabilitation Robotics
• Human-Computer Interaction
• Telerehabilitation Technologies
• +۵ مورد دیگر

Mostafa Mohammadi is an Assistant Professor at the Department of Health Science and Technology, Aalborg University, affiliated with the Faculty of Medicine and Center for Rehabilitation Robotics. His research focuses on neurorehabilitation robotics, human-computer interaction, and telerehabilitation technologies for individuals with disabilities. Ph.D. in Biomedical Engineering (Aalborg University, 2018-2022) M.Sc. in Biomedical Engineering (Polytechnic University of Milan, 2015-2017) B.Sc. in Mechanical Engineering (Sharif University of Technology, 2011-2015) His work spans exoskeleton design, assistive robotics, and innovative interfaces like tongue-computer interfacing. Recent projects include the eMotivo digital health solution funded by Innovation Fund Denmark and intelligent tendon-driven exoskeletons for severe disabilities. Research outputs (33 total) emphasize adaptive robotics, motor impairment solutions, and wearable technologies. Collaborations span robotics, biomedical engineering, and clinical disciplines. Teaching includes courses in rehabilitation robotics, human-computer interaction, and digital systems for biomedical engineering. Scientific activities align with UN Sustainable Development Goals for quality education and reduced inequalities. Notable contributions include advancements in myoelectric interfaces and neurorehabilitation technologies.

Swati Biswasمشاهده پروفایل

استاد

• Biostatistics
• Statistical Genetics
• Genetic Epidemiology
• +۳ مورد دیگر

Dr. Swati Biswas is a Professor and Associate Department Head in the Department of Mathematical Sciences at the University of Texas at Dallas (UTD). She holds a Ph.D. in Biostatistics from The Ohio State University (2003) and has held academic positions at UTD since 2012, including roles at the University of North Texas Health Science Center prior to that. Her research focuses on biostatistical methods for genetic epidemiology, cancer genetics, and risk prediction modeling, with a particular emphasis on Bayesian approaches. Education: B.Sc. (1994), M.Sc. (1996) in Statistics from the University of Delhi, followed by a Ph.D. in Biostatistics from The Ohio State University (2003). She completed a postdoctoral fellowship at MD Anderson Cancer Center (2004–2005). Research interests include statistical genetics, rare haplotype analysis, Bayesian clinical trials, and personalized risk prediction models for diseases like breast cancer and substance use disorders. She has developed tools such as CBCRisk for contralateral breast cancer prediction and Bayesian hierarchical models for pathway analysis. Her publications span over 40 peer-reviewed articles, focusing on methodological advancements in genetic association studies and clinical risk modeling. Notable awards include the 2016 Young Researcher Award from the International Indian Statistical Association and the 2011 President’s Award for Educational Excellence from UNT HSC. Dr. Biswas has secured grants totaling over $10M, including NIH funding for projects like multifrequency ultrasound imaging for breast cancer monitoring and Bayesian meta-analysis of cancer risk. She mentors doctoral students and has advised nine completed dissertations, with several current students.

• Cyber-Physical Systems
• Internet of Things (IoT) Security
• Computer Architecture
• +۵ مورد دیگر

Hokeun Kim is an Assistant Professor in the School of Computing and Augmented Intelligence (SCAI) at Arizona State University (ASU), part of the Ira A. Fulton Schools of Engineering. He previously held positions at Hanyang University (2021-2023) and worked in industry roles at Google, LinkedIn, and HP Labs. His research focuses on cyber-physical systems, IoT security, and computer architecture, with a particular emphasis on safety and security aspects of time-sensitive systems. Education: Ph.D. in EECS, University of California, Berkeley (2017) M.S. in EECS, Seoul National University (2012) B.S. in Computer Science and Engineering, Seoul National University (2010) Research Interests: Kim’s work spans secure IoT frameworks, real-time embedded systems, and edge computing. He develops tools like the Secure Swarm Toolkit (SST) and Lingua Franca, addressing challenges in distributed system security, interoperability, and performance. Key Contributions: Authored over 30 peer-reviewed publications in top venues like IEEE Transactions, ACM Conferences, and DATE. Received the ACM/IEEE Best Paper Award (IoTDI 2017) and IEEE Micro Top Picks Honorable Mention (2017). Active in organizing conferences (e.g., DATE, FDL) and serves on technical committees for top journals/conferences. Teaching: Courses include Computer Architecture I/II, Real-Time Embedded Systems, and IoT design at both undergraduate and graduate levels.

• Data Science
• Concept-Drift Management
• Database Systems
• +۱۲ مورد دیگر

Tania Cerquitelli is a Full Professor in the Department of Control and Computer Science (DAUIN) at Politecnico di Torino, where she leads research in data science, concept-drift management, and inclusive AI technologies. She is a member of SmartData@PoliTO, the GEDI Observatory for Gender Equality, and serves in leadership roles related to social affairs and community policies at the university level. She also acts as a scientific advisor for the partnership with Accenture. Her research interests span Data Science , Concept-Drift Management , Database Systems , Conversational Data Science , and Industry 4.0 . She applies AI and machine learning to industrial, societal, and ethical challenges, particularly in promoting inclusive communication and gender equality in research. The most recent publications highlight her work in explainable AI, concept drift detection, multimodal diagnostics, and AI for social good. Her research integrates machine learning, natural language processing, and computer vision to address real-world problems in manufacturing, healthcare, agriculture, and education. She is an Associate Editor for several prestigious journals including Expert Systems with Applications , Computer Networks , Future Generation Computer Systems , and Knowledge and Information Systems . She has served on the program committees of major conferences such as ECML PKDD, EDBT/ICDT, and ACM KDD, and has been a reviewer and selection committee member for ETH Zurich and EMPA. She actively supervises PhD students and teaches a wide range of courses including Data Science and Database Technologies, Business Intelligence for Big Data, and Gender and Diversity in Research. She is involved in multiple national and international research projects such as E-MIMIC, WEBFARE, and EnABLES, focusing on inclusive AI, smart data, and industrial applications. Her lab affiliations include the DBDM - Database and Data Mining Group (DAUIN) and the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory , where she contributes to advancing data science methodologies and their societal impact.

Mathangi Gopalakrishnanمشاهده پروفایل

دانشیار

• Pharmacometrics
• Precision Therapeutics
• Predictive Analytics
• +۹ مورد دیگر

Mathangi Gopalakrishnan, PhD, MPharm, is an Associate Professor in the Department of Practice, Science, and Health Outcomes Research at the University of Maryland School of Pharmacy. She is actively engaged in research, mentoring, and academic scholarship, with a focus on quantitative clinical pharmacology and data-driven therapeutic optimization. Education: PhD, Statistics, University of Maryland, Baltimore County MS, Statistics, University of Maryland, Baltimore County MPharm, Birla Institute of Technology & Science, Pilani, Rajasthan, India BPharmacy (Honors), Birla Institute of Technology & Science, Pilani, Rajasthan, India Her research interests center on pharmacometrics, precision therapeutics, predictive analytics, real-world data, and drug development . She integrates principles of clinical pharmacology, advanced frequentist and Bayesian statistical methods, and artificial intelligence/machine learning to enhance patient outcomes, particularly among vulnerable populations. Her lab's work includes designing prospective clinical pharmacokinetic trials for anti-epileptics and antimicrobials in patients on continuous renal replacement therapy, leveraging real-world data from electronic health records to optimize dosing in neonatal opioid withdrawal syndrome and pediatric anticoagulation, and developing models for disease progression in conditions like schizophrenia and binge-eating disorders. The trends in her recent publications reflect a consistent focus on model-informed precision dosing, real-world evidence generation, pharmacokinetic-pharmacodynamic (PK/PD) modeling in special populations, and methodological innovation in clinical trial design . Her work spans diverse therapeutic areas including critical care, neonatology, psychiatry, and maternal health, demonstrating a broad impact of quantitative pharmacology. Dr. Gopalakrishnan is accepting applications for postdoctoral positions in pharmacometrics at the Center for Translational Medicine, indicating active research funding and team leadership. Her collaborations extend to academic medical institutions nationwide, underscoring her role in multi-center research initiatives. She is involved in collaborative research with academic medical institutions across the country and has presented her work at major conferences including the Joint Statistical Meetings (JSM) and the American Conference on Pharmacometrics (ACoP).