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Murlidharan NairView profile

Professor

• Bioinformatics
• Cancer Genomics
• RNA Splicing Analysis
• +5 more

Dr. Murlidharan Nair is a Professor of Bioinformatics at Indiana University South Bend. He holds a Ph.D. and MSc in Biochemistry from the University of Poona (India). His research focuses on computational analysis of cancer genomics, RNA splicing mechanisms, and machine learning applications in biology. Key areas include cancer transcriptome profiling, nucleosome positioning, and biomarker discovery. He has led multiple grants, including NSF-funded projects on genomic tools and online course development in bioinformatics. Dr. Nair’s teaching spans bioinformatics, genomics, and computer science courses such as Applications of Data Mining and Introduction to Biostatistics (online). His lab develops tools like MAASE for alternative splicing analysis and DNAV for 3D genome visualization. He actively collaborates on projects like the yeast ionome characterization and tumor genome sequencing. Notable contributions include studies on prostate cancer isoform signatures, breast cancer heterogeneity, and neural network models for biological systems. His work bridges computational methods with experimental biology, emphasizing translational applications in cancer research and education.

Daqing YunView profile

Associate Professor

• High-performance Networking
• Parallel and Distributed Computing
• Green Networking
• +5 more

Daqing Yun is an Associate Professor of Computer Science at Harrisburg University of Science and Technology, affiliated with the Computer and Information Sciences (CIS) program. His expertise spans high-performance networking, parallel/distributed computing, green networking, and big data. He teaches courses on software development processes, computer networks, and big data. Education: Ph.D. in Computer Science, New Jersey Institute of Technology (2016) M.Sc. in Computer Software and Theory, Xidian University (China) B.S. in Software Engineering, Xidian University (China) Research Interests: Dr. Yun focuses on optimizing data transfer efficiency in high-performance networks, workflow scheduling in distributed systems, and leveraging machine learning for network performance prediction. His work bridges theoretical models with practical applications in cloud computing and industrial quality control. Research Trends: His recent articles emphasize tri-objective optimization in cloud workflows, cost-time tradeoffs in data transfers, and predictive analytics for big data. His 2024 work on cement clinker quality control demonstrates cross-disciplinary applications of network and data science. Grants and Advising: While no specific grants are listed, his publications suggest involvement in funded research projects. He advises students in big data transfer optimization and network profiling. Labs/Teams: No specific lab affiliations are mentioned, but his collaborative work on transport protocols implies involvement in network research groups.

Adalbert F.X. WilhelmView profile

Associate Professor

• Statistical Learning and Data Science
• Information and Knowledge Management
• Statistical Visualization
• +3 more

Prof. Adalbert F.X. Wilhelm serves as the Interim Dean of the School of Business, Social and Decision Sciences at Constructor University Bremen gGmbH, where he holds the position of Associate Professor of Statistics. His academic career includes visiting professorships at institutions such as the University of Cagliari and George Mason University. With a Ph.D. in Statistics (1993) and a Venia Legendi in Mathematics (2000) from the University of Augsburg, he has contributed significantly to statistical methodology and data science. His research focuses on statistical learning, data mining, and computational statistics, with notable work in high-dimensional data analysis, visualization techniques, and interdisciplinary applications. Wilhelm has led research projects funded by DFG grants and serves as an associate editor for journals like Computational Statistics and Computational Statistics & Data Analysis . His publications span topics such as clustering algorithms, attention mechanisms in psychology, and tumor promotion studies, emphasizing methodological rigor and practical impact. He is an ISI Elected Member and has held leadership roles in the International Association of Statistical Computing (IASC). Education: Ph.D. in Statistics (1993), Venia Legendi in Mathematics (2000), both from the University of Augsburg. Professional Activities: Associate Editor roles, DFG-funded research, and leadership in statistical organizations.

Stockton MaxwellView profile

Professor

• Forest ecology
• Dendrochronology
• Paleoclimatology
• +5 more

R. Stockton Maxwell is a Professor of Geospatial Science at Radford University (Virginia). He holds a Master of Forestry (2006) and a Doctorate in Geography (2010) from West Virginia University. His academic journey spans behavioral psychology, forest ecology, and biogeography, with current research focusing on dendrochronology, paleoclimatology, and vegetation dynamics. He directs the Radford University Tree Ring Laboratory and teaches Physical Geography (Geos 130), Introduction to Environmental Studies (Geog 140), and Biogeography (Geos 335). Maxwell's research explores tree-ring analysis applications in climate reconstruction, forest disturbance history, and ecological modeling, with fieldwork extending from the eastern U.S. to Mongolia. His work integrates geospatial techniques to address resource management challenges. He actively mentors students in independent research projects and collaborates on interdisciplinary studies. Recent publications emphasize fire ecology, hydroclimate proxies, and climate-vegetation interactions, reflecting a commitment to advancing climate science through dendrochronological methods. His contributions bridge ecological patterns and human-driven environmental changes, with a focus on long-term ecological continuity.

Giovanni GaliziaView profile

Professor

• Neurobiology
• Olfactory Coding
• Insect Behavior
• +3 more

Professor Giovanni Galizia is a faculty member at the University of Konstanz, holding the position of Professor of Zoology and Neurobiology. He is also a Permanent Fellow at the Wissenschaftskolleg zu Berlin. Born in 1963 in Rome, he studied Biology at the Freie Universität Berlin and Zoology at the University of Cambridge. His research focuses on olfactory coding in insects, particularly honeybees and fruit flies, exploring how neural networks process odor information and assign meaning to odors. Recent work includes investigating how honeybees recognize disease-related odors and use collective behavior to manage hive health. Education: Biology, Freie Universität Berlin Zoology, University of Cambridge Research Interests: Galizia's work delves into understanding the neural mechanisms underlying olfactory perception and coding in insects. Key areas include odorant receptor responses, neural circuitry in the insect brain, and the role of olfaction in behaviors like colony defense and disease detection. His studies also aim to model brain circuits computationally to better comprehend how odors are encoded and interpreted. Key Contributions: Author of Neurosciences: From Molecule to Behavior (2013) Lead researcher on honeybee olfactory coding and neural network modeling Investigating the use of insect olfactory systems for recognizing disease-related odors Professional Engagement: Galizia has presented at numerous events, including the 2022 Colloquium Odor Songs in the Bee Brain and discussions on topics like honeybee dreaming and virus-related research. His work bridges neurobiological studies with broader implications for understanding brain function and sensory processing. Labs/Teams: His research is conducted at the University of Konstanz, with collaborations at the Wissenschaftskolleg zu Berlin, focusing on experimental neurobiology and computational modeling.

Antonio Jesús García LoureiroView profile

Professor

• Semiconductor Device Modeling
• Semiconductor Physics
• Parallel Computing
• +3 more

Antonio Jesús García Loureiro is a Professor at the University of Santiago de Compostela (USC), affiliated with the Department of Electronics and Computing within the Faculty of Physics. He is part of the ARQCOMP research group and the Center for Research in Intelligent Technologies (CITIUS). His primary research focuses on semiconductor device modeling, semiconductor physics, and parallel computing, with significant contributions to solar cell technology and high-performance computing. He holds a PhD from USC (2000) with a thesis on semiconductor device simulation. His work bridges computational modeling, nanoelectronics, and renewable energy systems, emphasizing applications like photovoltaic converters and advanced materials. Research Interests : 3D semiconductor device simulation using finite element methods Optimization of solar cell efficiency (CIGS, tandem structures) Nanoscale transistor performance under process variability Laser power conversion systems for space and terrestrial use Machine learning tools for semiconductor data analysis Labs/Teams : Active in CITIUS and ARQCOMP, leading projects on semiconductor device simulation, parallel computing architectures, and energy-efficient systems. Recent Trends in Publications : Current work emphasizes GaN-based photovoltaic systems for space, high-efficiency tandem solar cells, and quantum transport effects in nanoscale FETs.

• Semiconductor Device Simulation
• Nanoelectronics
• Quantum Transport in Nanostructures
• +3 more

Natalia Seoane Iglesias is a Professor at the University of Santiago de Compostela, affiliated with the Department of Electronics and Computing within the Higher Technical School of Engineering. She holds a PhD from the same institution (2007), focusing on optimizing parallel 3D simulators for studying HEMT device fluctuations under the guidance of Dr. Antonio García Loureiro. Her research expertise spans semiconductor device simulation, nanoelectronics, and quantum transport phenomena in nanostructures. She has pioneered work on advanced transistor architectures (e.g., nanosheet/nanowire FETs), materials like GaN and SiC for space applications, and machine learning-driven optimization tools for semiconductor technologies. Her work bridges computational modeling (Monte Carlo, NEGF methods) with experimental nanofabrication challenges. Recent contributions include developing MLFoMpy for TCAD data analysis, high-efficiency laser power converters using SiC, and benchmarking future transistor nodes below 2nm. Her research group (ARQCOMP) focuses on variability reduction in nanoscale devices and sustainable semiconductor manufacturing. Her publications emphasize statistical variability studies in FinFET/NFET architectures, quantum corrections in 3D simulations, and the application of AI to reduce carbon footprint in nanodevice design. She has co-authored over 100 peer-reviewed articles, with a focus on device physics, materials innovation, and computational tools for nanoelectronics.

Boyang WangView profile

Associate Professor

• Hardware and embedded system security
• Wireless security
• Binary analysis
• +8 more

Dr. Boyang Wang is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Cincinnati, with a secondary appointment in Computer Science. He holds a Ph.D. from the University of Arizona and has conducted research at institutions like Xidian University and the University of Toronto. His research focuses on hardware security, embedded systems, wireless security, and privacy-preserving technologies. He has secured significant NSF funding, including CRII and REU Site grants, and leads projects on side-channel attacks, radio fingerprinting, and smart speaker privacy. Dr. Wang earned his B.S. in Information Security from Xidian University (2007), followed by dual Ph.D.s in Electrical and Computer Engineering (University of Arizona, 2017) and Cryptography (Xidian University, 2014). He has collaborated with industry partners like Bosch Research and Sandia National Lab. His teaching spans courses on cybersecurity, network security, and data privacy. His research interests include hardware security, embedded systems, wireless security, machine learning for security, and applied cryptography. He has published over 50 peer-reviewed papers, with notable works on side-channel attacks using neural networks and defenses against cache-based website fingerprinting. His lab actively mentors undergraduate and graduate students, many of whom have won awards and internships at top institutions like MITRE and Sandia. Key honors include the Best Student Paper Award at IEEE HOST’24, NSF awards, and teaching excellence recognitions. His funded projects include NSF IUCRC CHEST initiatives and collaborations with universities like Northeastern and the University of Nebraska. Dr. Wang also chairs organizing committees for major conferences like IEEE INFOCOM and ICNC.

Abigail ShobenView profile

Associate Professor

• Clinical Trial Design
• Longitudinal Data Analysis
• Cluster Randomized Trials
• +6 more

Dr. Abigail Shoben serves as an Associate Professor in the Department of Biostatistics at The Ohio State University's College of Public Health, where she has been a faculty member since 2010 following completion of her PhD at the University of Washington. Her work uniquely bridges advanced statistical methodology development with high-impact applications in veterinary medicine, public health crises, and health disparity reduction. Her educational credentials include: Ph.D. in Biostatistics, University of Washington (2010) MS in Biostatistics, University of Washington (2008) M.Ed. in Math, Science, and Technology Education, The Ohio State University (2003) Sc.B. in Chemistry, Brown University (2002) Dr. Shoben's research program focuses on advancing statistical methods for complex clinical trial designs, particularly examining the robustness of group sequential approaches in longitudinal studies and adapting random effects models for cluster randomized trials with overlapping participant groups. She simultaneously investigates statistical challenges in serum vitamin D measurement analysis while applying her expertise to diverse domains including tobacco control, cardiovascular disease, and cancer prevention. Her veterinary public health work stands out for its innovative focus on canine orthopedics and agility sports performance metrics. Analysis of her 15 most recent publications (2024-2025) reveals three dominant research strands: 1) Ohio-based opioid epidemic interventions using cluster randomized trials to evaluate naloxone distribution and community programs; 2) Appalachian health disparity initiatives targeting cervical cancer screening access and weight management through HPV self-collection and behavioral interventions; and 3) pioneering veterinary biostatistics research on canine agility performance, injury risk, and orthopedic treatments. Methodologically, her work consistently employs sophisticated longitudinal data analysis and cluster trial designs across these domains. No scientific awards or honors were documented in the provided source materials. While specific grant details and student advising information are not mentioned, Dr. Shoben's extensive collaborative publication record indicates active leadership in multiple research projects and likely mentorship of graduate students within the biostatistics program. Her work demonstrates significant engagement with community-based research teams across Ohio. Dr. Shoben maintains strong interdisciplinary partnerships with The Ohio State University's College of Veterinary Medicine and James Cancer Hospital, while her community-engaged research involves Appalachian health organizations and Ohio public health departments addressing the opioid crisis. This collaborative approach enables translation of statistical innovations into tangible public health solutions.

ALDO FRANCO DRAGONIView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +3 more

Prof. Aldo Franco Dragoni is an Associate Professor at the Department of Information Engineering, Polytechnic University of Marche (UNIVPM). He specializes in artificial intelligence applications for healthcare, cybersecurity, and smart systems. His research spans machine learning, computer vision, and multi-agent systems, with notable projects like CLAUDIA (Alzheimer's diagnosis via 3D MRI) and Cloud-YLung (lung cancer histology classification). He leads initiatives in medical imaging analysis, violence detection, and IoT-based systems. Research interests include AI-driven medical diagnostics, cyber-physical systems, and BDI agent architectures for ambient assisted living (e.g., Virtual Carer project). His work integrates cloud computing, neural networks, and multi-agent reasoning for healthcare solutions. Publications focus on AI applications in medical imaging, surveillance, and smart environments. He contributes to academic publications and conference proceedings, co-authoring papers on topics like deep learning for violence detection, face recognition systems, and blockchain in multi-agent negotiations.

• Artificial Intelligence in Industry
• Machine Learning
• Forecasting
• +4 more

Symone Gomes Soares Alcalá is a Professor at the Federal University of Goiás (Brazil) and a former postdoctoral researcher at the IIT Connected Industry Chair (Madrid, Spain). She holds a Ph.D. in Electrical and Computer Engineering from the University of Coimbra (Portugal) and a B.Sc. in Computer Engineering from PUC-GO (Brazil). Her research focuses on applying Artificial Intelligence, Machine Learning, and Vision Systems to industrial contexts, including predictive maintenance, additive manufacturing, and supply chain optimization. Education : Ph.D. in Electrical and Computer Engineering, University of Coimbra (2015) B.Sc. in Computer Engineering, Pontifical Catholic University of Goiás (2009) Research Interests : Symone’s work integrates computational intelligence with industrial processes. Key areas include: AI-driven defect detection in additive manufacturing Machine learning for demand forecasting and inventory management Low-Code platforms for digital transformation Optimization of distributed production systems Predictive maintenance algorithms Her methodologies often involve ensemble learning, neural networks, and vision systems. Publications : Her articles span journals like IEEE Transactions on Industrial Informatics and Production Engineering , focusing on applications like defect detection, supply chain design, and adaptive learning systems. Recent work emphasizes AI in manufacturing and industrial IoT integration. Awards : Recipient of the CAPES Elsevier 2024 Award for impactful research in Exact Sciences in Brazil’s Central-West region. Grants & Collaboration : Her research has been supported by collaborations with institutions like the Portuguese Institute of Systems and Robotics (ISR-Coimbra) and industry partnerships. Projects include developing digital twin systems and optimizing additive manufacturing supply chains. Labs & Teams : She leads interdisciplinary teams at the Federal University of Goiás, focusing on AI applications in industry and collaborative R&D with the IIT’s Connected Industry group.

• Business Process Management
• Artificial Intelligence
• Computer Science
• +1 more

Fabiana Fournier is an active researcher at IBM Research, Haifa, Israel , focusing on business process management, artificial intelligence, and event-driven systems. Her work bridges theoretical advancements with practical applications in explainable AI, causal process modeling, and blockchain technologies. Key Research Themes: Explainability in business processes, causal dependency discovery, LLM-driven process analysis, and temporal aspects in smart contracts Recent Trends: Publications center on benchmark creation for causal reasoning, monetizing financial sentiment analysis, and unification of process models

Pierre Yves SchobbensView profile

Professor

• Software Product Lines
• Software Verification
• Formal Methods
• +5 more

Pierre Yves Schobbens is a Professor of Computer Science at the Université Catholique de Louvain, specializing in software product lines verification, formal methods, and agent-oriented programming. He holds leadership roles including President of the Precise research center and the international affairs commission of the Faculty of Computer Science. His research focuses on software reliability, energy-aware systems, and real-time systems. Education: Bachelor in Philosophy (1982) Master in Applied Mathematics and Economics (1983) Master in Computer Engineering (1984) Doctorate in Computer Science (1993) Research Interests: Software Product Line Verification Model Checking Formal Methods for Real-Time Systems Energy Efficiency in Neural Architectures Agent-Oriented Programming Key Contributions: Development of featured transition systems for variability analysis Advances in mutation testing for timed systems Tools like ProVeLines for software product line verification Awards: Most influential paper award (IEEE RE 2016) Best paper (SAFECOMP 2012) 2024 VAMOS Ten-Year Most Influential Paper Award Grants & Projects: Lead on SQUAL.AI (AI-driven software quality) ERNEST (energy-efficient IoT scheduling) CFV (Center for Software Verification) He collaborates extensively with institutions like the Ecole Normale Supérieure and the University of Birmingham, and has supervised over 90 research works.

Richard ScamellView profile

Professor

• Database Management Systems
• Research Methodology
• Impact of Information Systems on Organizational Dynamics
• +3 more

Richard Scamell is a Professor and Associate Dean for Student Affairs in the Decision and Information Sciences Department at the C. T. Bauer College of Business, University of Houston. He has been at the University since 1972, contributing over five decades to academia. Scamell holds a Ph.D., MBA, and B.A. in Statistics and Operations Research from the University of Texas at Austin. His teaching focuses on Database Management Systems, Decision Support Systems, and MIS Research Methods. He has advised over 60 doctoral students, chairing 16 committees, and received multiple Excellence in Teaching awards. His research spans database systems, information systems impact on organizations, and groupware acceptance, with publications in MIS Quarterly , Management Science , and IEEE Transactions . He co-authored Data Modeling and Database Design (Cengage Learning, 2015). Scamell serves as the NCAA Faculty Athletics Representative and has held interim roles in university administration. His work emphasizes human-centered IT design and organizational dynamics. Research Interests : Database Management Systems, Human-Computer Interface, Information Systems Impact, Research Methodology. Key Contributions : Pioneering studies in groupware adoption, SQL vs. QBE usability, and long-term academic service. His research bridges technology and organizational behavior, emphasizing practical applications in education and industry.

David ValeriuView profile

Professor

• Electromagnetic Compatibility
• Biomedical Instrumentation
• Electromagnetic Field Measurements
• +3 more

Prof. David Valeriu is a Professor at the Department of Electric Engineering, Technical University of Iasi. His research focuses on electromagnetic compatibility, biomedical instrumentation, and environmental monitoring of electromagnetic fields. He leads projects investigating the health effects of electromagnetic fields on humans, including effects on bioelectric signals and induced currents in the body. His work also involves developing advanced measurement systems and materials for electromagnetic shielding. Key research areas include: Electromagnetic field measurements in hospitals, power substations, and residential areas Biomedical signal processing (ECG, PPG, brain activity) Development of low-cost embedded platforms for medical applications Electromagnetic interference mitigation in medical devices and imaging systems His recent studies address: Long-term magnetic field surveys in laboratories and hospitals Exposure assessment of mobile phone and power line emissions Omni-directional shielding materials for high-frequency radiation Integration of biosignal monitoring systems with ambient assisted living Prof. Valeriu has contributed to over 50 peer-reviewed publications, with a focus on electromagnetic field characterization and biomedical engineering applications. His work frequently explores the intersection between environmental safety and medical technology.