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Angela SorsbyView profile

Lecturer

• Quantitative methods
• Disproportionality in sentencing
• Probation supervision
• +3 more

Dr. Angela Sorsby is a Lecturer in Criminology at the University of Sheffield's School of Law, appointed in 2014. Her research focuses on quantitative evaluation of criminal justice initiatives, particularly in restorative justice, probation supervision, and police custody practices, with extensive collaborations on Ministry of Justice and Home Office projects. Education: PhD, University of Sheffield BSc (Hons) Psychology, University of Liverpool Dr. Sorsby specializes in quantitative research methods including multilevel modeling and large-scale data analysis applied to criminal justice systems. Her core interests span disproportionality in sentencing, police legitimacy in custody environments, and evidence-based evaluation of probation initiatives. She investigates how training programs affect offender engagement and how restorative justice schemes impact reconviction rates through rigorous statistical frameworks. Her publication record since 2006 demonstrates consistent focus on restorative justice evaluation and police custody practices, increasingly incorporating international dimensions through Romanian collaborations. Methodologically, she maintains strong emphasis on multivariate statistics applied to real-world justice interventions, with recent work examining trauma-informed legal education and detainee dignity standards. Grants: Evaluation of Restorative Justice Schemes (Home Office, £1.3M, 2001-2007) Evaluating Skills for Effective Engagement and Development (SEED) in Romania (European Commission, £51k, 2013-2014) Evaluating Skills for Effective Engagement and Development (SEED) (National Offender Management Service, £180k, 2011-2014) Dr. Sorsby collaborates extensively through the School of Law's Centre for Criminological Research, contributing to major evaluations of police custody practices and probation supervision across England and Romania, with recent work informing National Custody Forum standards.

Evgueni SmirnovView profile

Assistant Professor

• Machine Learning
• Conformal Prediction
• Time Series Forecasting
• +3 more

Evgueni Smirnov is an Assistant Professor in the Artificial Intelligence Department of Advanced Computing Sciences within the Faculty of Science and Engineering . His research focuses on Machine Learning , Conformal Prediction , Time Series Forecasting , and Biomedical Data Analysis . Key research areas include data prediction , classification , instance transfer , and conformal prediction with applications in both computer science and biomedical domains. His work spans predictive modeling , gene expression analysis , and inflammatory response mechanisms in cardiovascular diseases. He has contributed to editorial activities, including co-editing books through ML Research Press , and organized academic events like the Symposium on Conformal and Probabilistic Prediction with Applications . His publications demonstrate expertise in transfer learning , multivariate time-series forecasting , and cross-species biomedical modeling .

Mary RossanoView profile

Associate Professor

• Equine epidemiology
• Equine parasitology
• Gastrointestinal parasites of horses
• +4 more

Mary Rossano is an Associate Professor in the Department of Animal and Food Sciences at the University of Kentucky's Martin-Gatton College of Agriculture, Food and Environment. She has held this position since 2013 with an appointment structure of 80% teaching and 20% research. Dr. Rossano previously served as an Assistant Professor in the same department from 2007-2013 with a 70% teaching, 30% research appointment. Her educational background includes: Ph.D. in Epidemiology/Parasitology from Michigan State University (2003) M.S. in Animal Science/Epidemiology from Michigan State University (1999) B.S. in Animal Science from Michigan State University (1994) Certificate in Horse Management from Michigan State University (1991) Dr. Rossano's primary research focuses on equine epidemiology, particularly surveys and observational studies examining management practices and their effects on equine health, performance, profitability, and environmental impact. Her equine parasitology research centers on gastrointestinal parasites of horses, with special emphasis on Parascaris equorum and non-pharmacological control methods. She also conducts significant research on student learning assessment and factors influencing academic success in animal science education. Analysis of her publication record reveals a strong dual focus in her scholarly work. The first major theme involves equine parasitology and epidemiology, with numerous studies on parasite resistance, control methods, and environmental management of parasites. The second theme centers on educational research within animal sciences, particularly examining student performance factors and assessment methodologies in equine and animal science courses. Her earlier work also includes significant contributions to reproductive toxicology research, particularly examining environmental contaminants and their effects on male fertility. Her notable awards include: Runner up for the Ken Freedman Outstanding Advisor Award (2016) Nomination for the Ken Freedman Outstanding Advisor Award (2015) A Teacher Who Made a Difference Award (2014) Dr. Rossano has served as an advisor to numerous students and has been recognized for her teaching excellence. She has taught multiple courses including Equine Management (both lecture/lab and online versions), Horse Behavior and Handling, Domestic Animal Biology, and Scholarship of Teaching and Learning in Animal and Food Sciences. Her research has been supported by various grants, including NIH-funded studies during her time at Michigan State University. She has also served on editorial boards, notably the Veterinary Parasitology Editorial Advisory Board from 2006-2016, and as a reviewer for multiple scientific journals. Her laboratory work has focused on equine parasitology research, particularly related to Parascaris equorum and strongyle parasites. She has collaborated extensively with researchers across multiple institutions, particularly in Kentucky and Michigan, forming interdisciplinary teams that bridge veterinary medicine, epidemiology, and educational research.

Tim de LeeuwView profile

Professor

• Organizational Sciences
• Interorganizational Relations
• Innovation Management
• +8 more

Tim de Leeuw is a Full Professor at TIAS School for Business and Society , Tilburg University, with a focus on organizational sciences , specifically interorganizational relations , innovation , and entrepreneurship . He serves as the Academic Director of the Part-time MSc in Business Administration and has developed hybrid educational modules since 2018. Current roles: Full Professor, Academic Director, TIAS Research: Interorganizational collaboration, innovation management, entrepreneurship Teaching: Research methods, innovation, academic writing, multivariate analysis Tim supervises PhD students and bridges academic research with industry practices through workshops. His research has appeared in journals like Research Policy and Journal of Cleaner Production , often addressing innovation in networked organizations and sustainable development. He was involved in an NWO-TOP funded project on entrepreneurship success factors and co-edited a special issue on sustainable innovation. Educated at Eindhoven University of Technology (PhD), Tilburg University (Master's), and Fontys University of Applied Sciences (Bachelor's), he has contributed to student governance as chair of the Fontys student council.

• Psychiatric Comorbidity
• General Factor of Psychopathology
• Intergenerational Transmission of Mental Health
• +5 more

Erik Pettersson is an Associate Professor and Principal Researcher at Karolinska Institutet's Department of Medical Epidemiology and Biostatistics in Stockholm, Sweden. Holding the title of Docent since 2021, he leads significant research initiatives exploring the fundamental structure of mental disorders and their intergenerational transmission patterns. His primary research interests focus on psychiatric comorbidity and the general factor of psychopathology (p-factor), investigating why individuals with one psychiatric diagnosis often develop multiple mental health conditions. Using sophisticated multivariate behavior genetic and quasi-causal methods, Pettersson analyzes data from Swedish population-based health registers and the Swedish Twin Register to understand the underlying mechanisms of mental health disorders across generations. His publication record demonstrates consistent high-impact research in psychiatry and epidemiology, with recent work examining the connections between general psychopathology and clinical outcomes, intergenerational transmission of mental health conditions, and the relationship between mental health problems and physical health outcomes like cardiometabolic complications. His methodological approach frequently employs twin and sibling designs to control for familial confounding factors. Swedish Research Council grant for 'Treatment of general psychopathology' (2024-2026) Swedish Research Council for Health Working Life and Welfare grant for 'Life trajectories in offspring of parents with psychiatric diagnoses' (2024-2026) Swedish Research Council grant for 'Compulsory psychiatric care of children and youth' (2021-2024) Swedish Research Council grant for 'The general factor of psychopathology: Reliability, etiology, and development' (2018-2021) Pettersson actively mentors doctoral students including Mengping Zhou and Zhenxin Liao as primary supervisor and Astrid Moell as co-supervisor. His teaching experience includes directing courses in behavior genetics at Karolinska Institutet and previously at the University of Virginia, demonstrating his commitment to academic training in psychiatric epidemiology and research methodology.

• Economics
• Finance
• Economic Policy
• +3 more

Ünzüle Kurt serves as Associate Professor in the Banking and Finance Department at Canakkale Onsekiz Mart University's Biga Faculty of Applied Sciences since 2020, previously holding Assistant Professor positions at the same institution (2017-2019) and Research Assistant roles at Ardahan University (2010-2016). Her academic journey includes Doctorate (2012-2016), Postgraduate (2010-2012), and Undergraduate (2007-2010) degrees in Economics from Canakkale Onsekiz Mart and Selcuk Universities. Her research spans Environmental Economics, Behavioral Finance, and International Economics with methodological expertise in ARDL bounds testing and VAR modeling. Key investigations include climate change impacts on agriculture, globalization-defense expenditure relationships, urbanization effects on pollution, and financial development-energy consumption linkages. She employs panel data analysis across OECD and developing nations, frequently examining Turkey-specific economic phenomena through empirical econometric frameworks. Her publication portfolio demonstrates evolving research trajectories toward sustainability-focused economic analysis and behavioral finance applications, with recent works emphasizing bibliometric approaches in expectation theory and technological impacts on environmental outcomes. The interdisciplinary nature of her work bridges finance, environmental science, and development economics through rigorous quantitative methodologies. Dr. Kurt actively contributes to academic governance as Thesis Committee Member for graduate programs since 2017 and leads multiple funded projects including Industry 4.0 Maturity Level Research (2021-2022) and Financial Literacy Enhancement initiatives (2021-2022). Her administrative leadership includes former roles as Head of Department (2021-2023) and Vice Dean (2020-2021), alongside current responsibilities as Thrace University Union Coordinator and Research Center Assistant Manager.

Duygu Bayram KaraView profile

Associate Professor

• Machine Learning
• Signal Processing
• Electrical Machines and Energy Conversion
• +3 more

Duygu Bayram Kara is an active Associate Professor in the Department of Electrical Engineering at Istanbul Technical University's Faculty of Electrical and Electronics Engineering, where she has been a faculty member since 2016 after serving as a Research Assistant (2007-2015). Her career includes a brief industry role at Baytek Construction (2015-2016), but she remains a core academic staff member with office EEF 7311 and contact number +90-212-285-6956. She maintains active profiles on Scopus, Web of Science, Google Scholar, and ResearchGate with an ORCID (0000-0001-8184-8510). Education: PhD in Electrical Engineering from Istanbul Technical University (2009-2015) MSc in Electrical Engineering (with thesis) from Istanbul Technical University (2006-2009) BSc in Electrical Engineering from Istanbul Technical University (2001-2006) Research Interests: Her work integrates Machine Learning and Signal Processing with Electrical Machines and Energy Conversion to address critical challenges in electric motor reliability. She pioneers Kalman filter-based data fusion for aging monitoring and fault detection in motors, while simultaneously applying deep neural networks to characterize polymer nanocomposite films for electrical/optical applications. This dual focus bridges theoretical signal processing with practical energy systems and material science. Publication Trends: Her 23 Scopus-indexed outputs (2010-2025) demonstrate consistent innovation in motor diagnostics using wavelet transforms and neural networks, evolving toward sophisticated data fusion techniques. Recent work (2022-2025) heavily emphasizes deep learning for nanocomposite material analysis and Kalman filter applications in aging monitoring, with her 2020 nanocomposite conductivity paper accumulating 29 Scopus citations. The research shows increasing interdisciplinary collaboration and real-world validation in automotive and energy systems. Scientific Awards: No specific prizes, fellowships, or medals are documented in the provided materials. Professional recognition includes IEEE Senior Membership (2020-present) and standard IEEE Membership (2014-present), reflecting industry standing. Advising and Grants: She currently supervises one thesis in progress. As Principal Investigator, she secured two significant projects: Integrated Condition Assessment Using Kalman Filter-Based Data Fusion with Sensor Data from Different Environments and Recurrence Analysis-Assisted Aging Monitoring (TÜBİTAK, March 2024-May 2026) for advanced motor reliability Design and Development of Low Power Permanent Magnet Synchronous Motors in accordance with IE4 class (BAP, March 2018-October 2020) focusing on energy-efficient motor design Labs and Teams: Based at ITU's Ayazaga Campus, she operates within the Department of Electrical Engineering's research ecosystem, leveraging international collaborations (evidenced by global co-author networks) for projects involving electric motor diagnostics and nanocomposite analysis. Her work requires specialized facilities for motor testing, sensor data acquisition, and computational modeling, though specific lab names aren't disclosed in the text.

• Modeling (multivariate methods, reactor modeling, experimental design)
• Catalytic reactors (exhaust gas purification, automotive catalysis)
• Internal combustion engines
• +6 more

Jonas Sjöblom is an Associate Professor at Chalmers University of Technology, affiliated with the Transport, Energy and Environment division. His research focuses on connecting modeling techniques, catalytic reactor design, internal combustion engines, and emission control to create environmentally friendly vehicles and improve air quality. Modeling: Multivariate methods, reactor modeling, experimental design Emissions: Engine, brake, and tire particulate matter Air Quality: Control instruments and policy implications Projects: Involved in 40 initiatives, including hydrogen propulsion, emission regulations, and virtual calibration systems His recent work includes computational modeling of catalytic systems, characterization of alternative fuel emissions, and applications of machine learning in trip prediction. Collaborations span Chalmers departments, Gothenburg University, and industry partners like AFA Försäkring and Energimyndigheten.

James H. HarrisonView profile

Professor

• Clinical Chemistry
• Pathology Informatics
• Biomedical Informatics
• +5 more

James H. Harrison is a Professor of Pathology at the Department of Pathology, University of Virginia . His work spans Clinical Chemistry , Pathology Informatics , and Biomedical Informatics , with a focus on leveraging Machine Learning and Data Mining to improve clinical laboratory workflows and electronic health record (EHR) analysis. Education: Undergraduate: Furman University, Greenville, SC Medical School: Medical University of South Carolina (MD, PhD in Pharmacology), Charleston, SC Residency: Yale University (Anatomic and Clinical Pathology), New Haven, CT Harrison’s research emphasizes Biorepository Management standards through the College of American Pathologists Biorepository Accreditation Program and Medical Education Curriculum Development for pathology residents. His publications highlight trends in Artificial Intelligence applications for diagnostics, Longitudinal EHR Analysis , and Quality Assurance in Laboratory Medicine . He also explores Temporal Data Mining for event detection in complex clinical scenarios.

Gang TaoView profile

Professor

• Control Systems
• Adaptive Control
• Fault-Tolerant Control
• +5 more

Gang Tao is a Professor in the Department of Electrical and Computer Engineering at the University of Virginia, where he has worked for over 30 years in adaptive control theory and applications. He holds a Ph.D. in Electrical Engineering from the University of Southern California and serves as an IEEE Fellow. His research focuses on adaptive control of complex systems with actuator/sensor nonlinearities, stability analysis, and control of systems with uncertain faults. Education : B.S. (1982) University of Science and Technology of China; M.S. degrees (1984-1989) and Ph.D. (1989) from University of Southern California. Research Interests : His work spans adaptive control , fault-tolerant systems , robotics , and intelligent learning , addressing challenges in multivariable systems, structural damage compensation, and resilient control for high-speed trains, aircraft, and renewable energy systems. Publication Trends : Recent articles emphasize Koopman operator-based optimal control for multi-robot systems, adaptive backstepping techniques, and fault accommodation in aerospace and transportation applications. His work integrates machine learning with classical control theory for dynamic mutation handling. Scientific Recognition : IEEE Fellow Extensive editorial roles in leading journals Conference organization and plenary speaking Teaching Contributions : He has taught foundational courses including Adaptive Control, Linear Control Systems, and advanced topics in robotics and optimal control. His educational materials reflect deep technical expertise and pedagogical innovation.

• Biostatistics
• Public Health
• Clinical Research
• +3 more

Alexandra L. Hanlon is a Professor of Practice in the Department of Statistics at Temple University’s College of Science. She holds roles as Director of the Center for Biostatistics and Health Data Science (CBHDS) and Co-Director of the iTHRIV Biostatistics, Epidemiology, and Research Design (BERD) Methods Core. Her academic journey includes a PhD in Statistics from Temple University (1998), an MS in Mathematical Statistics from the University of California, Irvine (1991), and a BS in Mathematics from Rochester Institute of Technology (1985). Dr. Hanlon’s research focuses on biostatistical methods applied to healthcare outcomes, including sleep health, cardiovascular disease, and clinical trial design. Her work bridges statistical theory with practical applications in chronic disease management, gerontology, and public health disparities. Notable contributions include studies on sleep apnea’s impact on cognitive decline and interventions to improve clinical trial retention. Her publications span topics like sleep patterns and hypertension, statistical methodologies, and health disparities. Over 50 peer-reviewed articles reflect her interdisciplinary approach. She has secured over $3.5 million in grants from NIH, PCORI, and others, emphasizing translational research and patient-centered outcomes. Awards: ASA Fellow (2019), ASA Statistical Consulting Award (2014), and multiple research grants. Grants: Over 40 projects, including NIH-funded studies on sleep apnea (R01AG054435), pediatric feeding behaviors (R01NR015226), and cancer disparities (R01-CA196131). Dr. Hanlon’s leadership roles include past-chair of the ASA Council of Chapters and reviewer for high-impact journals. Her work impacts policy through contributions to patient safety initiatives and medication management programs.

Zidong WangView profile

Professor

• Intelligent Data Analysis
• Statistical Signal Processing
• Dynamic Systems & Control
• +4 more

Professor Zidong Wang is a renowned academic in the field of dynamic systems and computing at Brunel University London. He holds the rank of Professor in the Department of Computer Science within the College of Engineering, Design and Physical Sciences. His research focuses on intelligent data analysis, statistical signal processing, and dynamic systems & control, with notable contributions to networked control systems, cyber-physical systems, and machine learning. He has been recognized as a Highly Cited Researcher in Computer Science and Engineering, and is an IEEE Fellow and member of prestigious academies such as Academia Europaea. Professor Wang’s editorial roles include Editor-in-Chief positions for the International Journal of Systems Science , Neurocomputing , and Systems Science and Control Engineering , alongside associate editorships for multiple high-impact journals. His work is funded by major organizations including the EU, Royal Society, and EPSRC. His research interests span advanced control theory, signal processing, and interdisciplinary applications in engineering systems. Notable achievements include pioneering work on state estimation, security in cyber-physical systems, and anomaly detection using novel transformer architectures. Professor Wang has supervised numerous PhD students, contributing to advancements in fields like smart grids, microarray image processing, and genetic regulatory networks. His academic leadership and prolific publication record (over 1,050 publications) underscore his global impact in systems science and computing.

Salim AhmedView profile

Assistant Professor

• Safety and Risk Engineering
• Process Systems
• Process Control
• +3 more

Salim Ahmed is an Assistant Professor in the Department of Chemical Engineering at Memorial University of Newfoundland's Faculty of Engineering and Applied Science since February 2012. He holds a B.Sc. and M.Sc. in Chemical Engineering from Bangladesh University of Engineering and Technology (BUET) and a Ph.D. in Process Control from the University of Alberta. Prior roles include a postdoctoral fellowship at the University of Alberta (2006-2008), an Assistant Professorship at Qatar University (2008-2012), and a Lecturer position at BUET (1997-2000). His research focuses on safety and risk engineering, process systems, and model-based process control. Notable projects include an IgniteR&D grant-funded risk-based alarm system for process industries and early warning systems design. His expertise spans system identification, continuous-time models, model validation, and valve stiction analysis. Teaching responsibilities include undergraduate and graduate courses in Process Engineering and Oil and Gas Engineering. Awards include the 2010 Best Student Research Award (Energy and Environment category) at the Qatar Foundation Annual Research Forum. Research outputs include over 30 peer-reviewed articles, conference papers, and book chapters, emphasizing fault detection, data-driven modeling, and risk assessment in process systems. He has developed tools like StepID for step-response identification and AlarmSoft for alarm management.

Yuba GautamView profile

Associate Professor

• Public Health
• Cardiovascular Disease Prevention
• Global Health
• +3 more

Yuba Gautam is a Collegiate Associate Professor in the Department of Population Health Sciences at the Virginia-Maryland College of Veterinary Medicine, Virginia Tech. His expertise spans cardiovascular disease prevention, global health, and the application of technology in health education. He holds a PhD in Health Education from Southern Illinois University (2012) and an MS in Community Health from Minnesota State University (2007). His research focuses on cardiovascular risk factors in children, dietary patterns in athletes, and leveraging learning management systems (LMS) in public health education. He has published extensively on topics like LMS adoption using the Theory of Planned Behavior, obesity prevention interventions, and the impact of physical activity on academic performance. Prof. Gautam has held academic positions at Northern Michigan University (2013–2022) and has experience as an adjunct faculty member. He is a Master Certified Health Education Specialist (MCHES) since 2017 and previously held CHES certification. His work integrates technology solutions with public health challenges, emphasizing evidence-based strategies for global health issues.

Nourridine SieweView profile

Assistant Professor

• Mathematical Biology
• Disease Dynamics
• Computational Biology
• +4 more

Nourridine Siewe is an Assistant Professor at the Rochester Institute of Technology (RIT) in the School of Mathematics and Statistics under the College of Science . He specializes in mathematical biology, focusing on modeling diseases like obesity-induced Type 2 Diabetes Mellitus (T2DM), cancer, malaria, and infectious diseases. PhD in Mathematics from Howard University Postdoctoral Research Fellow at the University of British Columbia Postdoctoral Fellow at the National Institute for Mathematical and Biological Synthesis (NIMBioS) His research integrates mathematical modeling, differential equations, and computational analysis to address global health challenges. Recent work includes modeling glucose-insulin dynamics in T2DM and evaluating anti-T2DM drug efficacy. His methodologies have potential applications in cancer, hepatitis B, and chronic wound healing. The 15 most recent articles highlight his focus on mathematical modeling for infectious diseases, metabolic disorders, and ecological systems. These include studies on desert locust dynamics, diabetic wound treatments, and cancer immunotherapy optimization. 2025 NIGMS SuRE–First Award for research linking obesity to T2DM He mentors undergraduate and graduate students at RIT, teaching courses in multivariable calculus and research methodologies. His models are critical for virtual patient simulations and drug evaluation frameworks.