Find Academic Supervisors

Benjamin D. WandeltView profile

Research Professor

• Cosmology
• Theoretical Astrophysics
• Data Science
• +3 more

Benjamin D. Wandelt is a Research Professor at Johns Hopkins University with joint appointments in the Department of Physics and Astronomy and the Department of Applied Mathematics and Statistics. As a cosmologist and data scientist, he studies fundamental physics through astronomical observations using AI/ML and statistical inference. His research connects theoretical astrophysics with large-scale astronomical data to explore the cosmological framework. Research Focuses: Cosmological parameter estimation from supernova and CMB data Dark energy constraints through large-scale structure Machine learning applications in astrophysical inference Statistical methods for cosmological data analysis Major Honors: Gruber Prize in Cosmology (2018) Friedrich Wilhelm Bessel Prize Fellow of the American Physical Society Fellow of the International Association of Astrostatisticians

Amlan ChatterjeeView profile

Associate Professor

• High-Performance Computing
• Big Data
• Graph Compression
• +5 more

Dr. Amlan Chatterjee is an Associate Professor in the Department of Computer Science at California State University, Dominguez Hills. His work focuses on high-performance computing, big data analytics, and GPU-based graph compression techniques. He has held academic roles since 2015, including Assistant Professor (2015-2021) and currently serves as Associate Professor. His research explores efficient computation on large datasets using multi-core architectures and GPUs, alongside cloud computing optimization and IoT applications in aviation and health monitoring. Education: Ph.D., Computer Science, University of Oklahoma, 2014 M.S., Computer Science, State University of New York, 2009 B.Tech., Computer Science & Engineering, West Bengal University of Technology, 2007 Research Interests: Dr. Chatterjee's research spans graph compression, social network analysis, cloud resource optimization, and IoT-driven solutions for aviation safety and health monitoring. He has mentored students in projects like GPU-based big data processing and cloud computing efficiency. Awards: Graduate Computer Science Scholarship (University of Oklahoma, 2012-13) Computer Science Advisory Board Scholarship (2012) Phillips Petroleum Scholarship (2010-11) Top Undergraduate Rank (1st/68 students) Academic Contributions: He has served on numerous committees, including the Research Chair for Untenured Faculty (2016-17), IEEE conference session chairs, and accreditation boards. His teaching includes courses on data structures, operating systems, and introductory computer science.

Swen GüntherView profile

Professor

• Process Management
• Innovation Management
• Lean Six Sigma
• +4 more

Prof. Dr. Swen Günther holds the Chair of Process and Innovation Management at HTW Dresden within the Faculty of Business Administration . His academic leadership spans teaching and research in production management, project management, process/quality management, and technology/innovation management. He oversees the Bachelor's and Master's programs in Industrial Engineering and collaborates with international partner universities like Satakunta/VAMK (Finland) and FH Burgenland (Austria). Education & Career: Günther earned his PhD (Dr. rer. pol.) from TU Dresden's Market-Oriented Management department. Prior to academia, he worked at Procter & Gamble in manufacturing and quality management (2008-2015). His research focuses on Lean Six Sigma, TRIZ Reverse, transfer indicators, and digitalization. He leads the BMBF-funded 'Transfer_i' project (2019-2021), developing transfer metrics for academia-industry collaboration. Research Interests: His work emphasizes systematic knowledge/technology transfer, digital transformation in processes, and innovative management methodologies. Recent studies address transfer indicators for universities, cost-benefit analyses of digital projects, and empirical research on management trends. Teaching & Advising: Over 50+ theses supervised (2018-2021) across process optimization, quality management, and innovation transfer. He advises companies on Lean/Six Sigma implementation and organizes industry excursions with firms like T-Systems MMS and König & Bauer. Professional Engagement: Member of German Society for Quality (DGQ) and Society for Organisation (GFO). Regularly publishes in journals like Qualität in der Wissenschaft and Zeitschrift für Organisation .

Matthias WolfView profile

Senior Lecturer

• Phylogenetics
• Phycology
• Protistology
• +3 more

Matthias Wolf is an Academic Director at the Department of Bioinformatics, Biocenter, University of Würzburg. He holds a Doctor rerum naturalium (summa cum laude) from Free University of Berlin (2002) and has been a faculty member since 2003, progressing through roles including C1 Assistant Professor (2003–2008), Lecturer (2008–2015), Senior Lecturer (2015–2024), and now Academic Director. His research focuses on phylogenetics, phycology, and RNA secondary structure analysis, particularly using ITS2 databases. He has over 85 peer-reviewed publications and an h-index of 46. Awards include being listed among the top 2% scientists in his field (2020) and recognition for 25 years of service in Berlin and Bavaria (2023). Education highlights include a Diploma in Biology (1999) and PhD studies on molecular systematics of green algae (2002). He has held visiting roles at Research Center Jülich and contributed to expeditions aboard the research vessel METEOR. His grants include DFG funding for ITS2-based phylogenetic algorithms (2007–2011). He serves on editorial boards for BMC Ecology and Evolution and Biology , and is active in societies like GfBS and DBG. Research interests emphasize using ITS2 sequence-structure data for phylogenetic reconstruction, species delineation, and molecular systematics. His work spans algae, protists, and fungi, with a focus on resolving evolutionary relationships and taxonomic ambiguities. Teaching responsibilities include courses in bioinformatics, phylogenetics, and computational tools for biology. Labs/Teams : Chair of Bioinformatics, ITS2 Database Project Grants : DFG MU 2831/1-1 (2007–2011) Advising : Supervised numerous PhD/Master’s students in microbial systematics and bioinformatics

Francesco BaldiniView profile

Senior Lecturer

• Medical Entomology
• Vector Biology
• Malaria Research
• +3 more

Dr. Francesco Baldini is a Senior Lecturer at the University of Glasgow, coordinating the Vector Biology and Disease Group within the School of Biodiversity, One Health and Veterinary Medicine. He holds affiliations with the Ifakara Health Institute and contributes to the VectorsGlasgow initiative. His research focuses on malaria vector biology, with expertise in mosquito ecology, insecticide resistance, and innovative surveillance tools using spectroscopy and AI. He completed a PhD in Medical Entomology across Harvard University, Perugia University, and Imperial College London. Key research areas include developing non-invasive diagnostic methods (mid-infrared/quantum spectroscopy), understanding vector population genetics, and exploring biocontrol strategies. His work bridges field studies in Africa with lab-based molecular analyses. Recent projects emphasize insecticide resistance in Anopheles species, cryptic taxa discovery, and age-grading techniques. Grant support includes Bill and Melinda Gates Foundation funding for malaria vector surveillance, and collaborations with global health institutions. Supervised PhD topics include AI-driven mosquito analysis, tsetse fly trypanosomiasis surveillance, and avian malaria epidemiology. Scientific awards include an AXA ISSF Fellowship (2015–2017) and an Academy of Medical Sciences award (2022–2024). Key publications address genomic studies of Anopheles funestus, quantum cascade laser spectrometry, and Wolbachia symbiont impacts on vector competence.

Dennis MoekeView profile

Lecturer

• Patient Logistics
• Healthcare Logistics
• Data-driven Capacity Planning
• +4 more

Dennis Moeke is a Lecturer in Logistics and Alliances at HAN University of Applied Sciences, leading the Logistics and Alliances Lectorate. He holds a broad professional network spanning logistics, government, and academia, with a focus on healthcare logistics and sustainable urban development. His research addresses societal challenges such as affordable healthcare systems, smart logistics solutions, and livable cities through interdisciplinary collaboration. His expertise includes patient logistics, data-driven capacity planning, and optimization of healthcare processes. Key projects include the Healthy City Lab , exploring sustainable last-mile logistics in cities via two Living Labs (Campus Heijendaal and Buur & Zo), and the Living Labs Sustainable Supply Chain Management in Healthcare . He has secured significant funding, including a NWO grant (Project 439.18.457), to advance interdisciplinary research. Notable contributions include developing the Buur & Zo concept (home care concierge services) and optimizing hospital patient flows using process mining. He collaborates with organizations like Logistics Valley, Health Valley, CWZ Carinova, and Siza. His work emphasizes practical applications, translating academic insights into real-world tools for healthcare and logistics sectors. Publications span topics like home care scheduling optimization, sustainable urban logistics, and pandemic response logistics. He actively promotes the role of logistics in societal well-being through teaching and industry partnerships.

Stephen RamseyView profile

Associate Professor

• Computational Systems Biology
• Bioinformatics
• Precision Medicine
• +6 more

Stephen Ramsey, an Associate Professor at Oregon State University, holds dual appointments in the School of Electrical Engineering and Computer Science (College of Engineering) and the Department of Biomedical Sciences (Carlson College of Veterinary Medicine). With a PhD in Physics from the University of Maryland, his postdoctoral training in computational genomics at the University of Washington, and professional experience at the Institute for Systems Biology and Center for Infectious Disease Research, Ramsey bridges computational methods with biomedical applications. Education : Ph.D., Physics, University of Maryland; M.S., Physics, University of Maryland; Sc.B., Mathematical Physics, Brown University Ramsey specializes in computational systems biology , focusing on bioinformatics , biomedical knowledge graphs , and precision medicine . His research integrates machine learning , gene regulatory network modeling , and multi-omics data analysis to address challenges in rare disease diagnostics , drug monitoring , and inflammatory disease mechanisms . Current work includes AI-driven biomedical translation and electrochemical biosensor development for non-invasive diagnostics . Recent publications highlight knowledge graph applications in translational biomedicine , causal network inference in clinical-environmental data integration , and cross-species cancer transcriptomics . His team develops tools like RTX-KG2 and PloverDB to standardize biomedical data sharing and semantic reasoning . Scientific Awards : 2019 Zoetis Award (Carlson College of Veterinary Medicine) 2016 NSF CAREER Award 2016 PhRMA New Investigator Award 2010 NIH K25 Mentored Quantitative Research Award Ramsey advises in computational biology courses (CS 446/546) and contributes to biomedical AI through projects like mediKanren for rare disease diagnostics . His NSF-funded research explores gene expression noise and regulatory network dynamics , while NIH and PhRMA grants support his translational medicine initiatives. He leads the Ramsey Laboratory , which develops graph-based reasoning tools for biomedical data translation and multi-omics integration . The lab's work spans comparative oncology models, electrochemical biosensors , and knowledge graph infrastructure for clinical decision support .

• Computational Neuroscience
• Machine Learning
• Neural Dynamics
• +5 more

Dr. Emili Balaguer-Ballester is an Associate Professor in Computational Neuroscience at Bournemouth University, UK. He co-champions the Interdisciplinary Neuroscience Research Centre and serves as Senior Fellow of the Higher Education Academy. His research spans computational neuroscience, machine learning, and virtual reality applications, with collaborations across Europe (University of Barcelona, Heidelberg University, IDIBAPS, Polyra) and North America (Indiana Purdue University, University of British Columbia). PhD in Physics (Cum Laude) from University of Valencia (2001) MSc in Neuroscience and Biology of Behaviour from University of Seville (2004) Research focuses on cortical network dynamics, mesoscopic auditory cortex modeling, top-down modulation in cognition, and affective computing in VR. His work combines nonlinear time series analysis with neurodynamic modeling to study spontaneous and task-related brain activity states. Recent publications demonstrate expertise in causal inference, neuroevolutionary optimization, and affective state detection using EMG/PPG sensors in VR environments. Collaborators include neuroscience labs (Sanchez-Vives, Durstewitz) and tech companies (Sony London, Emteq). PhD thesis award - Culture Institute 'Juan Gil-Albert', Spain (2001) Senior Fellow Higher Education Academy (2020) Secured major grants including Royal Society funding for cortical network modeling (2022), Human Brain Project ERC support for neuromorphic hardware (2022), and Santander Bank research travel grants (2016). Supervised 14 PhD students through projects involving data streams, VR immersion, and cortical dynamics. Labs include Balaguer Lab (GitHub), Interdisciplinary Neuroscience Research Centre, and collaborations with Human Brain Project. Teaching encompasses doctoral-level neuroscience, MSc data analytics, and undergraduate systems design courses.

László MérőView profile

Professor

• Psychology
• Game Theory
• Cognitive Science
• +4 more

László Mérő is a Professor and lecturer in the Department of Affective Psychology at Eötvös Loránd University's Institute of Psychology. His work focuses on the interplay between psychology, game theory, and complex systems, particularly exploring how humans perceive and rationalize rare events, emotions in decision-making, and the boundaries of rational thought. He has also contributed to artificial intelligence research and the philosophical underpinnings of scientific inquiry. His publications often bridge theoretical and applied domains, addressing topics like monetary behavior, social coordination, and cognitive biases. Mérő’s research interests prominently feature the study of 'miracles' as probabilistic anomalies, the evolution of economic systems, and the limits of rationality in both human cognition and AI. He has written extensively on these themes, including books translated into English such as The Logic of Miracles and Moral Calculations . His work integrates empirical psychology with mathematical models to explain phenomena ranging from emotional impulses to collective social behaviors. No scientific awards are explicitly mentioned in the provided texts. While no advising or grant details are available, his publications suggest a focus on interdisciplinary research at the intersection of psychology, philosophy, and computational sciences. His institutional affiliation includes the Institute of Psychology, where he maintains an office at Izabella u. 46, Budapest, and can be reached via email and listed phone number.

Silvia ToluView profile

Associate Professor

• Neurorobotics
• Bio-inspired Control Systems
• Neuromorphic Engineering
• +3 more

Silvia Tolu is an Associate Professor at the Technical University of Denmark's Department of Electrical and Photonics Engineering, specializing in Neurorobotics. She leads the NeuroRobotics Technology Lab (NRT-LAB), focusing on bio-mimetic control architectures for compliant robotic systems. Her research integrates neuroscience, computer science, and biology to develop solutions for assistive robotics and neurodegenerative disease diagnosis. Her research interests span: Neuro-robotics and neuromorphic engineering Bio-inspired control systems and adaptive motor control Machine learning for robotic applications Human-robot compliant interaction Cerebellar control models Publications primarily focus on neurorobotics, bio-inspired control, and human-robot interaction, with recent advances in learning-based control systems for soft robots and aerial manipulation. Awards include the AEG Elektrofonden Research Grant and funding for human-robot interaction safety research. Current projects include LOCOPD (Lundbeck Foundation), AEROTRAIN (EU Marie Curie ITN), and compliant human-robot interaction systems. She supervises multiple PhD students in neurorobotics and maintains international collaborations across Europe and Asia. Laboratory resources include advanced robotic platforms for musculoskeletal and soft robot control.

• Optimization Algorithms
• Computer Vision
• Machine Learning
• +3 more

Assoc. Prof. Dr. Adnan Acan is a faculty member in the Department of Computer Engineering at Eastern Mediterranean University (EMU). He holds a PhD from Middle East Technical University, specializing in Electrical Engineering. His academic roles include teaching and supervising numerous graduate students in areas such as optimization algorithms, computer vision, and biomedical signal processing. Education: PhD, Electrical Engineering, Middle East Technical University (1992) MS, Electrical Engineering, Middle East Technical University (1985) BS, Electrical Engineering, Middle East Technical University (1983) Research Interests: His research focuses on optimization algorithms, machine learning, pattern recognition, and biomedical applications. Notable areas include metaheuristic algorithms (e.g., particle filters, great deluge), multi-agent systems, and ECG/heartbeat classification. He has contributed to advancements in computational intelligence, evolutionary algorithms, and medical diagnostics. Advising & Students: He has supervised over 30 graduate students, including PhDs such as JAMSHID TAMOUK (2021) and ZAHRA GOLRIZ KHATAMI (2019), and master’s students like MILAD ROSTAMPOUR (2023). His work spans applications in robotics, face recognition, and numerical optimization. Labs & Collaboration: His teaching and research involve courses in artificial intelligence, algorithms, and computer engineering. He actively contributes to academic service, including roles as a session chair and reviewer in conferences. His lab focuses on developing innovative solutions to complex computational and biomedical challenges.

• Research Integrity
• Scientific Misconduct
• Meta-Research
• +3 more

Daniele Fanelli is an Assistant Professor in the School of Social Sciences at Heriot-Watt University, United Kingdom. He holds a PhD and is currently a Fellow at the London School of Economics and Political Science (26 Apr 2023 – 1 May 2026). His work contributes to UN Sustainable Development Goals, though specific goals are not detailed here. In terms of education, he has received several competitive fellowships including the Marie Curie Intra-European fellowship (2008) and Leverhulme Early-Career Fellowship (2010). His research focuses on meta-research, scientific integrity, and publication practices, with a particular interest in quantifying knowledge, assessing retractions’ epistemic impact, and analyzing predictors of misconduct. He has also explored the hierarchy of sciences and the unintended consequences of academic metrics. His scientific achievements include receiving the LSE Excellence in Education Award (2021). Recent activities highlight his engagement in talks about reproducibility, research integrity, and metascience, including an invited talk in 2025 titled 'Research integrity in context'.

• Chaos control
• Modelling of nonlinear dynamic systems
• Modelling of biological systems
• +3 more

Yağmur Denizhan is a full-time Professor at Boğaziçi University. Their research focuses on chaos control, nonlinear dynamic systems modeling, and biological systems analysis. Key interests include renal sympathetic nerve activity modeling, stochastic processes, and optimization algorithms. Research highlights include long-term mathematical models of renal function and arterial pressure dynamics, as well as advancements in Particle Swarm Optimization (PSO) algorithms. Their work bridges chaos theory, computational methods, and biomedical engineering. Notable contributions include studies on targeting methodologies in chaotic systems and interdisciplinary explorations of semiotics combined with thermodynamics. Recent publications (2010-2013) emphasize real-time object recognition systems and evolutionary modeling frameworks. No scientific awards or grants are listed in the provided information. No student advisees are explicitly mentioned.

Claudia AndreiniView profile

Associate Professor

• Metalloproteins
• Bioinformatics
• Biological Databases
• +3 more

Claudia Andreini is an Associate Professor at the University of Florence, affiliated with the Magnetic Resonance Center and the Department of Chemistry. Her research focuses on computational biology, particularly metalloproteins and bioinformatics. She pioneered the use of bioinformatics to study metalloproteins and developed the MetalPDB database. She collaborates internationally and has presented at major conferences. Education: PhD in Chemistry (2006), University of Florence; Laurea in Chemistry (2002, cum laude), University of Florence. Research interests include metalloprotein structure-function relationships, metal-coordination databases, and predictive computational tools. Her work integrates structural bioinformatics, machine learning, and database mining to analyze metal sites in proteins. Recent publications highlight advancements in zinc-binding site prediction, metal-induced structural variability, and applications of deep learning in metalloprotein analysis. She has contributed to drug design studies involving ruthenium complexes and antibacterial agents. No scientific awards or grants are explicitly listed in the provided texts. She leads the MetalPDB project and collaborates on structural biology initiatives.

• Information Systems Engineering
• Logic and Computation
• Smart Grids
• +3 more

Prof. Sandford Bessler is affiliated with the Technische Universität Wien's Faculty of Informatics, specifically within the Compilers and Languages department. His research focuses 75% on Information Systems Engineering and 25% on Logic and Computation. He teaches courses such as Bachelor Thesis for Informatics and Business Informatics . His work emphasizes smart grids, electric vehicle management, scheduling algorithms, and distributed systems. Research interests include optimizing energy networks, resilience in power grids, and integrating renewable energy systems. He has contributed to projects like ARTE (2012–2017) , exploring disruption-tolerant vehicle-infrastructure communication. Supervised theses include Electric vehicles recharge scheduling with time windows and A service overlay network for telematic applications . Key projects involve improving grid resilience through demand-side management and collaborative frameworks. He collaborates with industry and academia on smart grid technologies and electric vehicle infrastructure.