Find Academic Supervisors

Laura TiptonView profile

Assistant Professor

• Microbiome Analysis
• Bacterial-Fungal Interactions
• Statistical Ecology
• +4 more

Laura Tipton is an Assistant Professor in the Department of Mathematics & Statistics at James Madison University (JMU), affiliated with the College of Science and Mathematics. Her research focuses on microbiome dynamics across diverse habitats such as human lungs, aerobiota, invertebrate guts, and fermented foods, emphasizing bacterial-fungal interactions and robust statistical methodologies. She integrates techniques from ecology, machine learning, and graph theory, with side projects in digital humanities, data visualization, and data feminism. Education: PhD in Computational Biology (2016), University of Pittsburgh/Carnegie Mellon University MS in Statistics (2011), George Washington University BA in Biostatistics (2007), University of Virginia Her research interests span microbiome analysis, microbial interactions, and interdisciplinary data science. Recent work includes studies on airborne fungal DNA dynamics, fungal contributions to neonatal lung diseases, and psychobiotic field developments. She emphasizes methodological innovation in microbiome studies and advocates for inclusive data practices. While no formal awards or grants are listed, her work reflects significant contributions to collaborative projects like the Global Spore Sampling Project and Pacific Innovations, Knowledge, and Opportunities (PIKO) Program. Laura’s advising focuses on mentoring students in interdisciplinary projects at the intersection of mathematics, biology, and computational science.

• Decision Analysis
• Consistency
• Fuzzy sets
• +12 more

Michele Fedrizzi is a full professor of Mathematical Methods of Economics and Actuarial and Financial Sciences at the Department of Industrial Engineering, University of Trento. He holds academic affiliations across multiple institutions, including the Faculty of Economics (University of Trento), Faculty of Computer Science (University of Bolzano), Department of Economics and Management, and doctoral programs in Social Sciences and Materials, Mechatronics and Systems Engineering. His research focuses on decision analysis, fuzzy systems, and consensus modeling in group decision-making. Past research included statistical distributions, fuzzy extensions of classical models (e.g., linear regression), and risk equity evaluation. Current interests involve consensus dynamics in group decisions, preference modeling, and the Analytical Hierarchy Process (AHP). Fedrizzi serves as a referee for journals like European Journal of Operational Research, Fuzzy Sets and Systems, and IEEE Transactions on Systems, Man, and Cybernetics. He organized the XXXII AMASES Conference (2008) and the International Workshop on Preferences and Decisions (2009). He was a member of the University of Trento’s Administrative Board (2004–2008) and reviewed PhD theses at institutions like Åbo Akademi University (Finland) and the University of Padova.

Ella HaigView profile

Associate Professor

• Intelligent Systems
• User Modelling and Personalisation
• Data Mining
• +7 more

Ella Haig is an Associate Professor of Artificial Intelligence at the University of Portsmouth, UK, affiliated with the School of Computing within the Faculty of Technology. She is also a member of the Portsmouth AI and Data Science Centre, Future of Law, Innovation and Technology Research Centre, and Centre for Cybercrime and Economic Crime. Her academic journey includes a PhD in Computer Science from Birkbeck College (University of London), an MSc in Learning Technologies from the National College of Ireland, and a Postgraduate Certificate in Learning and Teaching from the University of Portsmouth. Her research focuses on Intelligent Systems, User Modelling, Data Mining, and Decision Support, with notable contributions to emotion recognition, machine learning, and educational data mining. Ella has published over 140 works, including articles on multimodal emotion detection and comparative analyses of AI models like GPT-3 and BERT. She actively contributes to conferences, such as the IEEE World Congress on Computational Intelligence and the International Conference on Educational Data Mining. Ella has secured grants totaling over £235,000 for projects like the KTP Citizens Advice initiative, exploring technology solutions for public services. Her work aligns with UN Sustainable Development Goals, particularly in advancing education and innovation. Notable achievements include a 2023 Best Paper Award for her research on multimodal emotion recognition systems.

Kyle J. M. BishopView profile

Professor

• Active Matter
• Colloidal Assembly
• Soft Matter Physics
• +3 more

Kyle J. M. Bishop is Professor of Chemical Engineering at Columbia University's Fu Foundation School of Engineering and Applied Science (Columbia Engineering), where he leads research at the intersection of active matter, soft materials, and micro-robotics. Appointed in 2016 after serving as Assistant Professor at Penn State and postdoctoral fellow with George Whitesides at Harvard, his work focuses on non-equilibrium assembly of colloidal systems. Education: BS in Chemical Engineering (highest distinction), University of Virginia PhD, Northwestern University Professor Bishop's research pioneers strategies for directing colloidal assembly outside thermodynamic equilibrium, with emphases on magnetic micro-robot navigation, synchronization phenomena in active matter, and electrochemical control of soft materials. His lab develops fundamental principles for programming collective behavior in synthetic systems, bridging chemical engineering, physics, and robotics to create materials with lifelike functionalities. Recent work explores biomolecular condensates, field-driven transport, and non-equilibrium information processing. Analysis of his 2023-2025 publications reveals a cohesive trajectory toward autonomous control of active systems: magnetic micro-robots navigate complex landscapes through field programming, enzymatic coacervates implement biological feedback loops, and oscillator networks achieve emergent synchronization. These studies span soft matter physics, electrochemistry, and microfluidics, consistently targeting applications in programmable materials and environmental engineering while advancing non-equilibrium thermodynamics. Scientific Awards: 3M Non-tenured Faculty award NSF CAREER award for 'Contact Charge Electrophoresis for Mobile Microfluidics' Professor Bishop secures substantial research funding including his NSF CAREER grant developing contact charge electrophoresis for microfluidic applications. While current students aren't listed in source materials, his lab trains graduate researchers in experimental soft matter physics and micro-robotics. His group collaborates across disciplines to translate fundamental discoveries into technologies for targeted delivery and environmental remediation. The Bishop Lab at Columbia Engineering operates as an interdisciplinary hub where chemical engineers, physicists, and materials scientists develop experimental platforms for manipulating colloids at fluid interfaces, with recent work focusing on magneto-capillary dynamics and field-programmable micro-robot swarms.

Michael RitterView profile

Researcher

• Combinatorial Optimization
• Integer Programming
• Operations Research
• +4 more

Dr. Michael Ritter is a researcher and academic staff member at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology and the Department of Mathematics. His primary role involves advising Master's students in Mathematics programs and coordinating administrative duties for academic affairs. He is part of the Discrete Optimization research group and collaborates with professors like Stefan Weltge and Peter Gritzmann on advanced optimization projects. His research focuses on Combinatorial Optimization, Integer Programming, and real-world applications such as flight schedule design, semiconductor manufacturing optimization, and logistics systems. He has contributed to projects involving automated driving systems, production network resilience, and low-power semiconductor design. Ritter teaches courses on Discrete Optimization and Case Studies in Optimization, balancing theoretical instruction with practical problem-solving. He has co-advised numerous theses on topics ranging from supply chain optimization to timetabling algorithms, demonstrating his commitment to both academic research and student mentorship. His work bridges mathematical theory with industrial applications, addressing challenges in manufacturing, transportation, and electronics through rigorous optimization frameworks. He maintains an active publication record in reputable journals and conferences, reflecting his expertise in interdisciplinary optimization research.

• Biosecurity
• Veterinary Epidemiology
• Statistical Modeling
• +4 more

Dr. Devindri Perera is a Senior Lecturer at Curtin University's School of Electrical Engineering, Computing and Mathematical Sciences (EECMS) within the Faculty of Science and Engineering. He is also affiliated with the Office of the Provost, demonstrating administrative and academic leadership roles. His research focuses on interdisciplinary areas including biosecurity systems, veterinary epidemiology, statistical modeling, and genomics. Dr. Perera's work spans environmental science (biosecurity border management), veterinary medicine (equine health and endocrinology), and computational methods (data clustering, statistical algorithms). His biosecurity research emphasizes risk assessment and spatial-temporal analysis of non-indigenous species, while his veterinary studies investigate equine physiology and disease mechanisms. In genomics, he contributes to identifying genetic markers for neurological disorders like multiple sclerosis. His publications from 2006–2023 reflect a strong focus on statistical methodologies in interdisciplinary contexts, including genome-wide association studies, algorithm validation for genotyping, and applied econometric models. This demonstrates a blend of theoretical rigor and practical problem-solving across diverse domains. Though no specific awards or grants are listed in this profile, his prolific publication record and cross-disciplinary approach highlight sustained academic engagement. His research collaborations span institutions globally, addressing both environmental and biomedical challenges.

• Stochastic Processes
• Financial Volatility Modeling
• Machine Learning Applications
• +5 more

Aerambamoorthy Thavaneswaran is a Professor in the Department of Statistics at the University of Manitoba , specializing in inference for stochastic processes and dynamic data science applications. His research bridges financial economics, machine learning, and fuzzy logic to develop innovative volatility models and trading strategies. University: University of Manitoba Department: Statistics Email: Aerambamoorthy.Thavaneswaran@umanitoba.ca Research Interests: His work focuses on neuro volatility models, financial network analysis, and fuzzy logic applications in portfolio optimization. Recent projects include hybrid deep learning architectures for cryptocurrency prediction and dynamic covariance modeling. Publications (2023-2025): His articles highlight advancements in volatility forecasting, algorithmic trading strategies, and neuro-fuzzy systems. Key topics include transformer networks for stock markets, adaptive fuzzy adjacency matrices, and Kalman filter integration for cryptocurrency trading.

• Operational Research
• Computational Optimization
• Transportation Logistics
• +3 more

Emmanouil Zachariadis serves as an Associate Professor at the Department of Management Science and Technology (DMST) within the School of Business at Athens University of Economics and Business (AUEB). He specializes in operational research and computational optimization, focusing on transportation logistics, supply chain systems, and environmental impact minimization. Education : BSc in Chemical Engineering from National Technical University of Athens (NTUA) MSc in Computing Science from Imperial College London PhD in Chemical Engineering from NTUA His research integrates mathematical programming with optimization algorithms for operational challenges in transportation and production systems. He has published 26 articles in top-tier journals, accumulating over 1200 Scopus citations by June 2024. Recent scholarly trends emphasize vehicle routing problems with complex constraints (cross-docking, loading, time windows) and optimization methods for logistics sustainability. His work spans production-routing integration, emergency evacuation planning (EVITA project), and hybrid metaheuristics. Scientific Awards : Teaching excellence award for undergraduate course 'Optimization Methods in Management Science', Dept. of Management Science & Technology AUEB (2021-22) Teaching excellence awards for postgraduate course 'Large Scale Optimization', MSc in Business Analytics AUEB (2020-21, 2021-22, 2022-23) He has participated in European and National research projects, applying his expertise in supply chain optimization and sustainability. His teaching portfolio covers quantitative methods, operational research, and supply chain optimization at both undergraduate and postgraduate levels.

Jimmy McGibneyView profile

Lecturer

• Network Security
• Artificial Intelligence
• Cybersecurity
• +5 more

Jimmy McGibney is a Lecturer in the Department of Computing and Mathematics at Waterford Institute of Technology (WIT), now part of South Eastern Technological University (SETU). He holds a Master of Engineering from Dublin City University (1995) and a Bachelor of Engineering (Electronic) from University College Dublin (1992). His research focuses on network security, AI-driven cybersecurity solutions, trustworthiness in service compositions, and resource-constrained environments. External roles include serving as a Researcher at the Telecommunications Software and Systems Group (2000), a Research Assistant at Dublin City University (1996–1997), and a Systems Engineer at Aldiscon (1994–1996). His work emphasizes applied research in intrusion detection systems, network forensics, and trust management frameworks. Key research interests include AI applications in cybersecurity, trust metrics for service compositions, and securing edge computing environments. He has organized workshops on digital forensics and incident response, and his recent work explores AI methodologies for resource-limited systems. McGibney’s publications span over 38 works, including peer-reviewed chapters and conference contributions. Notable areas include network forensic readiness frameworks, deep learning-based intrusion detection, and trust overlays for spam protection. He has contributed to projects funded by industry and academic collaborations, focusing on practical cybersecurity solutions.

Ruth MüllerView profile

Professor

• Entomology
• Climate Change
• Vector-Borne Diseases
• +3 more

Ruth Müller is a Professor of Entomology at the Institute of Tropical Medicine in Antwerp, Belgium, leading the Department of Biomedical Sciences. She is the Unit Head in Entomology and oversees the Institute’s insectarium, established in 2019 with a €1 million grant. Her research focuses on the interplay between biodiversity, climate change, and human health, particularly regarding mosquito-borne diseases. Key projects include studying vector control strategies, climate impacts on disease transmission, and collaborations with institutions like Nepal’s National Health Research Institute. Education and Early Career: Müller’s early work involved Arctic studies on UV radiation and ocean warming’s environmental risks. She has authored over 57 ISI-listed publications, 12 non-ISI documents, 9 book chapters, and a German-language book on biodiversity and climate change. Research Interests: She investigates eco-bio-social approaches to vector control, climate change’s effects on disease vectors, and interdisciplinary solutions for tropical diseases. Her work spans Europe, Africa, South America, and Asia, with a focus on malaria and dengue vectors. Recent Articles: Müller’s recent studies address topics like predatory macroinvertebrate interactions with malaria vectors, public perceptions of climate change in Nepal, and gene drive technology in mosquitoes. These reflect her dual focus on ecological and public health dimensions. Grants and Labs: The insectarium houses species like tiger mosquitoes, malaria vectors, and sandflies, enabling interdisciplinary research on tropical diseases linked to climate change. Major grants include the Flemish Government’s support for vector control projects and the European Centre for Disease Prevention and Control’s funding for VECTORNET3. Future Work: Ongoing projects include light polarization’s impact on mosquito swarms and climate change’s biodiversity-health interface, emphasizing translational research for global health solutions.

• Statistical Education
• Environmental Modeling
• Science Communication
• +2 more

Dr. Rachel King is an Associate Professor in the School of Mathematics, Physics and Computing at the University of Southern Queensland. Her applied research spans statistical applications in environmental science, public health, and agricultural risk management. She develops spatial modeling frameworks for ecological conservation and designs UV exposure assessment methodologies for skin cancer prevention. Her research group focuses on creating statistical tools for environmental decision-making, including wildlife corridor design, drought forecasting systems, and climate risk models for agriculture. Current projects investigate human-wildlife conflict mitigation and optimize bushfire preparedness strategies. Publication analysis shows strong emphasis on interdisciplinary collaboration, blending advanced statistics with practical environmental applications. Recent methodological innovations include INLA-SPDE spatial models and electronic UV monitoring systems. She leads community engagement initiatives on disaster preparedness and mentors graduate students in statistical applications for environmental science.

Claudia KlüppelbergView profile

Professor

• Applied Probability
• Mathematical Statistics
• Financial Risk Management
• +3 more

Claudia Klüppelberg is a Professor and Chair of Mathematical Statistics at the Center for Mathematical Sciences, Technische Universität München (TUM). Her academic journey includes positions at ETH Zurich, University of Mainz, and TUM since 1997. She holds a Carl von Linde Senior Fellowship at TUM-IAS, focusing on Risk Analysis and Stochastic Modeling. Her research bridges applied probability, statistics, and their applications in finance and insurance, emphasizing extreme value theory, risk processes, and stochastic networks. She has received prestigious awards such as the New Frontiers in Risk Management Award (2007) and Cross of Merit (2001). Her work addresses real-world challenges in financial risk management, including systemic risk in networks and operational risk modeling. Her recent publications explore causal analysis of extreme risks in networks, max-linear models, and Bayesian networks for extreme events. She contributes to academic leadership as an editorial board member and advisor, promoting interdisciplinary stochastic sciences.

Christa SearleView profile

Assistant Professor

• Sustainability
• Logistics
• Operational Research
• +3 more

Christa Searle is an Assistant Professor in Business Analytics at Heriot-Watt University's School of Social Sciences and Edinburgh Business School. She joined in 2021 and serves as Programme Director for the MSc Business Analytics and Consultancy. Her research focuses on sustainability, logistics, and human behavior, employing operational research, agent-based simulation, and data analytics. She holds an extraordinary senior lecturer position at Stellenbosch University, where she earned her PhD in Industrial Engineering (2019). Her work addresses challenges like hydrogen refuelling infrastructure design, supply chain optimization, and modeling complex systems such as tuberculosis spread in informal settlements. Key projects include the ATHENA framework for hydrogen infrastructure analysis and Agent-Based Modeling of forced migration and consumer behavior. Christa has been recognized with awards including the Tom Rozwadowski Medal (2022) and Fellow of the Higher Education Academy (FHEA, 2023). She actively participates in conferences and workshops, such as the 53rd Annual Conference of the Operations Research Society of South Africa (2024) and the Sustainable Road Freight Workshop (2023). She contributes to research groups like the Centre for Logistics & Sustainability and the FeMe Network. Her teaching emphasizes authentic, industry-engaged assessments and spans business and data analytics. Current research collaborations explore decarbonizing freight transport and SDG-aligned solutions, reflecting her commitment to practical sustainability outcomes.

Christian MuiseView profile

Assistant Professor

• Artificial Intelligence
• Automated Planning
• Machine Learning
• +6 more

Christian Muise is an Assistant Professor at Queen's University's School of Computing, part of the Faculty of Arts and Science. He holds a PhD (2014) in Artificial Intelligence from the University of Toronto, where he was advised by Sheila McIlraith and J. Christopher Beck. His research focuses on automated planning under uncertainty, combining planning with learning for applications like goal-oriented dialogue systems and multi-agent coordination. He previously held postdoctoral roles at the University of Melbourne's Agentlab and MIT's CSAIL, and was a Research Staff Member at the MIT-IBM Watson AI Lab. Education: PhD in Artificial Intelligence, University of Toronto (2014) MSc in Computer Science, University of Toronto (2009) BSc in Computer Science, Carleton University (2007) Research Interests: His work bridges automated planning and machine learning, emphasizing robustness in uncertain environments. Key areas include non-deterministic planning, model acquisition with large language models (LLMs), and human-aware planning. He explores applications in healthcare (e.g., treatment response prediction), robotics (autonomous navigation), and dialogue systems for safety-critical domains. Current projects include developing explainable planning systems and mitigating bias in AI decision-making. Awards: Scotiabank Scholar (Scotiabank Centre for Customer Analytics) Advising & Labs: Leads the Mu Lab, supervising PhD and Master's students in topics like model acquisition, dialogue systems, and planning bias. Active in open-source tools (e.g., L2P, MACQ library) to democratize planning research. Collaborates on projects like PRP Rebooted and FixMyPlan to advance FOND planning and LLM integration. Labs/Teams: Mu Lab at Queen’s University, focusing on planning under uncertainty, AI safety, and neuro-symbolic systems.

• Political Economy
• Economic Growth
• Innovation Economics
• +3 more

Rainer Andergassen is an Associate Professor in the Department of Economic Sciences at the University of Bologna. His research focuses on political economy, economic growth, innovation dynamics, and tourism economics. He holds a formal affiliation with the University of Bologna's Department of Economic Sciences and maintains an ORCID profile. His work bridges theoretical economic modeling with applied policy analysis, particularly in areas of innovation diffusion, structural change, and tourism destination management. Education details are not explicitly provided in the text, but his academic trajectory aligns with typical senior faculty roles. Research interests include intergenerational mobility, technological convergence, and public policy design for tourism sectors. His recent publications (2012-2021) explore topics like innovation networks, disaster mitigation economics, and fraudulent behavior in competitive markets. Dr. Andergassen's academic contributions span 20+ years with articles addressing: (1) innovation's role in economic growth through structural transformation, (2) strategic tourism destination management frameworks, and (3) behavioral economic factors influencing managerial fraud. His work frequently integrates mathematical modeling with real-world policy implications. No formal awards or grants are listed, though his extensive publication record indicates sustained research activity. He is available for consultations at his office (Piazza Scaravilli 2, Bologna) on Wednesdays at 11:30am.