Find Academic Supervisors

Aldo LipaniView profile

Researcher

• Information Retrieval
• Search Evaluation
• Bias Correction
• +3 more

Aldo Lipani is a researcher at the E-Commerce Research Area (E194-04) within TU Wien, specializing in information retrieval and search evaluation methodologies. Holding a Dr.techn. doctoral degree, he has maintained consistent research output since 2014 with significant contributions to IR evaluation frameworks. His educational background includes completing his doctoral thesis titled "On Biases in Information retrieval models and evaluation" at TU Wien in 2018. This foundational work established his research trajectory in evaluation bias and normalization techniques. Dr. Lipani's research centers on critical evaluation challenges in information retrieval, with particular expertise in bias correction mechanisms, document length normalization, and pooling strategies for test collection construction. His work addresses high-recall search scenarios essential for systematic literature reviews and e-commerce applications, often developing visualization tools like VoMBaT to analyze evaluation measure behavior. Recent publications demonstrate growing focus on transformer model position bias mitigation and contextualized re-ranking approaches. Analysis of his 15 most recent publications reveals a sustained commitment to improving IR evaluation reliability through methodological innovations. Key trends include the application of fixed-cost pooling strategies to systematic review automation, development of bias correction frameworks, and integration of visualization techniques for evaluation transparency. His work consistently bridges theoretical model improvements with practical applications in academic search and e-commerce contexts. As an active member of TU Wien's Network Lab within the E-Commerce Research Area, Dr. Lipani collaborates extensively on projects involving search system evaluation, systematic review automation, and e-commerce search technologies. His research group maintains strong connections with international IR communities through regular publications at major conferences.

Pascal WeisenburgerView profile

Researcher

• Programming Languages
• Multitier Programming
• Tierless Programming
• +12 more

Pascal Weisenburger is a researcher at the School of Computer Science , University of St. Gallen. His work focuses on programming languages for distributed systems , emphasizing multitier programming, reactive paradigms, and type-driven placement reasoning. Research Themes : Multitier programming languages, CRDTs, dynamic placement type systems, reactive microservices, compiler correctness, and domain-specific scheduling. Recent Articles : Explored E-graphs for disequality reasoning (POPL 2025), array type duality in functional languages (ECOOP 2024), and formal verification of CRDTs (PLDI 2023). Committee Roles : Participated in program/steering committees for ECOOP, SPLASH, APLAS, and IEEE BigData conferences. Key Contributions : Developed the ScalaLoci language for multitier systems, proposed Propel for algebraic property verification, and introduced Dyno for static reasoning in dynamic placement scenarios.

• Quantum Physics
• Atomic Physics
• Molecular Physics
• +3 more

Dr. Ruth Le Sueur is a Research Fellow in the Department of Chemistry, specializing in quantum physics and molecular physics. Her work focuses on ultracold atomic and molecular systems, quantum scattering, and computational modeling. Institution: Affiliated with the Department of Chemistry Role: Research Fellow Her research spans quantum mechanics, atomic physics, and chemical physics, with a focus on: Ultracold molecule creation Feshbach resonance manipulation Quantum scattering dynamics Optical trapping techniques Computational modeling of molecular interactions STIRAP and precision spectroscopy Recent publications highlight her contributions to merging optical tweezers, shielding molecular collisions, and refining interaction potentials. She collaborates on developing computational tools like BOUND , FIELD , and MOLSCAT for quantum state calculations.

Artur AndrzejakView profile

Professor

• Artificial Intelligence
• Programming Systems
• Distributed Systems
• +6 more

Prof. Dr. Artur Andrzejak is a full professor (W3) at Heidelberg University since 2010, serving as the Head of the research group Artificial Intelligence for Programming (AIP), and currently as Executive Director of the Institute of Computer Science. He has held significant academic roles including Deputy Dean of the Faculty of Mathematics and Computer Science (2019-2024), Dean of Studies for Computer Science (2015-2017), and Liaison Professor of the German National Academic Foundation (2014-2023). Habilitation in Computer Science (2009), Freie Universität Berlin Ph.D. in Computer Science (2000), ETH Zurich Diploma in Mathematics (1995), Freie Universität Berlin His research focuses on artificial intelligence applications in software engineering, particularly code generation and error correction techniques. He has also made significant contributions to software aging analysis, distributed systems, and cloud computing, with publications spanning federated learning, secure computation, and software rejuvenation. Recent publications demonstrate a strong focus on code generation and error correction methods using large language models, while earlier work includes foundational studies in distributed systems, grid computing, and software rejuvenation techniques. His research combines theoretical computer science with practical applications in enterprise software systems. As an academic leader, he has organized Dagstuhl Seminars on Parallel Data Analysis (2013) and Self-Healing Systems (2009), and served on editorial boards for the journals Parallel Processing Letters and Multiagent and Grid Systems. He has held various leadership roles in academic institutions and research networks.

Anna Corbo CrehanView profile

Senior Lecturer

• Police Ethics
• Community Policing
• Vulnerable People Policing
• +7 more

Anna Corbo Crehan PhD is a Senior Lecturer at Charles Sturt University’s Australian Graduate School of Policing and Security, where she has worked full-time since 1999. Her expertise spans police ethics, procedural justice, domestic violence, and vulnerable people policing, with a focus on merging Western and Eastern perspectives in counter-terrorism contexts. Education: PhD, BA (Hons) from University of Melbourne Research Groups: Practical and Public Ethics, Future of the Professions Key Collaborations: UN Sustainable Development Goals (Social Justice, Peace & Security) Her research explores ethical dilemmas in policing, including: Police accountability in Indigenous deaths in custody Professional boundaries in law enforcement Deradicalization strategies and drug court rehabilitation Police cynicism’s impact on community policing Recent publications (2025-2022) focus on: Police accountability frameworks Ethical challenges in police psychology Comparative analysis of professional doctorates vs. PhDs Scientific awards include 2024 grants for criminology research and discretionary funding for Aboriginal justice studies. She has supervised over 30 HDR and coursework students in policing, security, and ethics, with a focus on: Community policing models Aviation accident investigation protocols Child sexual abuse institutional responses Her work intersects with SDG 16 (Peace, Justice & Strong Institutions) through policing reforms and SDG 10 (Reduced Inequalities) via vulnerable populations research.

Jonas GeipingView profile

Professor

• Machine Learning
• AI Safety
• Efficient AI Systems
• +4 more

Jonas Geiping is a Professor at the ELLIS Institute Tübingen, leading the Safety- and Efficiency- aligned Learning research group. He has previously worked at the University of Maryland, University of Siegen, and University of Münster. His research focuses on safety and efficiency in machine learning, exploring data poisoning principles, watermarking for generative models, privacy in federated learning, and adversarial attacks against large language models. He also investigates how to make AI systems more efficient through weight averaging, recursive computation, and computational constraint analysis. His recent work includes test-time computation scaling using recurrent depth approaches, adversarial attacks on LLMs beyond jailbreaking, and zero-shot detection of machine-generated text through contrasting LLMs (Binoculars method). He has contributed to arithmetic capabilities in transformers with positional embeddings and scalable LLM training frameworks like AxoNN. His research addresses critical questions about the intersection of safety and efficiency in AI systems: Can models reason well without sacrificing safety? How do computational constraints affect safety guarantees? Can systems be designed where intelligence and safety reinforce each other?

Gerson SunyéView profile

Associate Professor

• Model-Based Engineering
• Software Testing
• Distributed Systems
• +6 more

Gerson Sunyé is an Associate Professor at Nantes University, where he teaches topics related to Software Engineering. He is a member of the Naomod research group within the LS2N research laboratory, focusing on Model-Based Engineering (MDE) techniques applied to software engineering problems, particularly in testing distributed systems. His work bridges academic research and industrial applications through the Atlanmod open-source platform developed within the Eclipse Community. His primary research interests span Model-Based Engineering, Software Testing, Distributed Systems, Cloud Computing, and Domain-Specific Languages. He investigates how rigorous application of models can improve software engineering practices, focusing on model merging, conflict resolution, and large-scale model management. His work particularly emphasizes executable DSLs, model views, and testing methodologies for complex systems. Analysis of his recent publications (2020-2024) reveals a strong trend toward integrating AI techniques with model management, particularly using machine learning for inter-model relations and reinforcement learning for conflict resolution. His work continues to evolve from foundational model management toward more applied contexts including low-code development platforms, energy-aware computing, and large language model integration for software engineering tasks. Dr. Sunyé actively collaborates with numerous researchers including Jean-Marie Mottu, Massimo Tisi, and Erwan Bousse. His research has been supported by European projects including Heterogeneous and Distributed Services for the Future Computing Continuum and Training the Next Generation of Experts in Scalable Low-Code Engineering Platforms. He leads research within the Naomod group at LS2N, which develops the Atlanmod platform for model-based engineering. The group focuses on practical applications of MDE in industrial contexts, particularly addressing scalability challenges in model management and the integration of model-based techniques with modern software development practices including cloud computing and low-code platforms.

• Scientific Computing
• High Performance Computing
• Numerical Analysis
• +8 more

Robert Klöfkorn is an Associate Professor and Senior Lecturer in the Department of Mathematics at Lund University's Faculty of Sciences, affiliated with MERGE: Modelling the Regional and Global Earth system and eSSENCE: The e-Science Collaboration. His research focuses on Numerical Analysis and Scientific Computing, particularly in high-performance computing frameworks. Research Interests: Klöfkorn specializes in: Development of open-source scientific software (DUNE, OPM initiatives) Higher-order adaptive methods for partial differential equations Applications ranging from climate dynamics to porous media flow Structure-preserving methods for multiphase flow with imaging applications Discontinuous Galerkin methods and mesh refinement techniques His recent publications (2018-2021) demonstrate consistent focus on computational mathematics frameworks, finite volume/discontinuous Galerkin methods, and adaptive algorithms for complex physical systems like fluid dynamics and porous media. Work frequently intersects high-performance computing and open-source tool development. Projects & Leadership: Principal Investigator for AI-Twin project (Swedish Research Council, 2025-2029) on physics-informed AI for imaging reconstructions Leads eSSENCE@LU 11:1 initiative in computational imaging (2025-2026) Co-founder of Distributed and Unified Numerics Environment (DUNE) Core contributor to Open Porous Media Initiative (OPM) Teaching: Oversees courses across all academic levels including Computational Programming (Python), Numerical Methods for PDEs, and Simulation Tools. Supervises bachelor/master theses requiring advanced numerical analysis proficiency.

• Special Education
• Systems Change
• Prevention Strategies
• +3 more

Ruth Ervin is an Associate Professor in the Department of Educational and Counselling Psychology, and Special Education at the University of British Columbia's Faculty of Education. Her work focuses on special education, particularly systems change and evidence-based prevention/intervention strategies for students with behavioral and academic challenges in school settings. Her research centers on Systems Change, Prevention Strategies, and Intervention Strategies within Special Education, with emphasis on functional behavioral assessment, Response-to-Intervention (RTI) frameworks, and peer-mediated approaches. She investigates how data-informed problem-solving models can be implemented at school-wide levels to address reading and behavior difficulties through multi-tiered support systems. Analysis of her recent publications reveals consistent focus on translating research into practice, particularly in scaling model demonstration projects to statewide initiatives. Her work emphasizes merging research agendas with practical implementation, especially in systems change literature and tiered intervention models for diverse student populations. Dr. Ervin has received significant recognition including: Article of the Year Award, School Psychology Review (2006) Presidential Mini-Grant Award for Research Recognition (1998) Research Development Award (1997) Dissertation Research Award, BSP Interest Group of NASP (1997) She teaches graduate courses in the ECPS department (EPSE 535, 551A, 552B, 565B) focused on special education assessment and intervention methodologies, contributing to the training of future school psychologists and special educators.

• Environmental Fluid Mechanics
• Wildfire Propagation Modeling
• Computational Wind Dynamics
• +5 more

Professor Rob Stoll at the University of Utah's Mechanical Engineering Department specializes in environmental fluid dynamics, wildfire modeling, and urban/agricultural canopy flows. His work bridges computational modeling with field measurements across diverse domains. Develops GPU-accelerated QES simulation tools Focuses on wildfire-atmosphere coupling Advances low-cost sensor networks for environmental monitoring Research Trends revealed through 15 recent publications include: Wildfire propagation under heterogeneous terrain/fuel 3D wind modeling in vineyards and urban environments Particle transport in sparse and row-organized canopies Turbulence characterization in stable boundary layers Open-source hardware for atmospheric sensing Scientific Contributions 2008: Best PhD Dissertation (University of Minnesota) 2017-2022: NSF Grant for wildfire modeling 2020-2025: Systems approach for carrot blight management 2023-2026: Vineyard smoke exposure modeling grants Teaching Activities include graduate courses in Numerical Methods for Engineering Systems and advising PhD/Master's theses since 2015.

• Interaction Design
• Hypermedia
• Interactive Systems
• +2 more

Carsten Heisterkamp serves as a Lecturer at Hochschule Düsseldorf's Peter Behrens School of Arts, specializing in contemporary digital design disciplines. His academic focus bridges artistic practice with technological innovation within the university's applied sciences framework. His research interests center on Interaction Design , Hypermedia , and Interactive Systems , with particular emphasis on temporal dimensions in digital media through his Zeit & Interaktion coursework. The curriculum integrates physical-digital interfaces via Gestaltungslabor (Design Lab) methodologies and explores advanced hypermedia applications. As a Lehrbeauftragter (contract lecturer), he contributes to the university's practice-oriented pedagogy within Germany's applied sciences education model. His teaching portfolio reflects the institution's commitment to merging artistic exploration with technical implementation in digital media contexts.

Martin MarinovView profile

Researcher

• Computer Graphics
• Geometric Modeling
• 3D Mesh Processing
• +3 more

Dr. Martin Marinov is a researcher affiliated with RWTH Aachen University, specializing in computer graphics, geometric modeling, and 3D mesh processing. His work focuses on multiresolution modeling, subdivision surfaces, and GPU-accelerated algorithms for real-time rendering. Research areas: Subdivision surfaces, quad-dominant remeshing, scattered data approximation, and GPU computing. His publications include innovative methods for mesh decimation, feature preservation, and anisotropic remeshing, with applications in computer graphics and geometric modeling. Marinov has contributed to optimizing parameter correction for subdivision surfaces and developing robust algorithms for complex 3D models.

Kate SimkoView profile

Professor

• Electronic Music
• Film Scoring
• Orchestral Composition
• +2 more

Kate Simko is a Professor of Composition for Screen at the Royal College of Music , where she leads the classical-electronic ensemble London Electronic Orchestra . Her work merges orchestral traditions with electronic innovation, creating immersive soundscapes for film, television, and live performance. Formed LEO during her Masters studies Collaborated with Jamie Jones and Carl Craig Represented by Manners McDade film agency Her research focuses on genre hybridization and spatial audio techniques , with a strong emphasis on cross-cultural storytelling and modern soundtrack distribution . Recent projects include large-scale orchestral adaptations of electronic works and boundary-pushing collaborations with streaming platforms like Netflix and Amazon Prime Video . Notable partnerships include: BBC documentaries Netflix series scoring Carl Craig at Royal Albert Hall Philip Glass remix Kate's works explore: Electronic-classical instrumentation Narrative-driven composition Global audience engagement Streaming-era soundtrack release strategies

Oriol Bosch-JoverView profile

Research Fellow

• Survey Methodology
• Computational Social Science
• Data Science
• +5 more

Oriol Bosch-Jover is a Postdoctoral Researcher in Data Donation and Computational Methods at the Leverhulme Centre for Demographic Science, University of Oxford, and a Research Fellow at the Research and Expertise Centre for Survey Methodology (Universitat Pompeu Fabra). He contributes to Professor Melinda Mill’s ERC advanced grant CHRONO, the Data4Science project, and the ERC starting grant WEB DATA OPP, focusing on interdisciplinary demographic and survey methodology research. His academic background includes a PhD in Social Research Methods from The London School of Economics, an MSc in Survey Methods for Social Research from the University of Essex, and a BSc in Political Science from Pompeu Fabra University. As a computational methodologist, Bosch-Jover specializes in integrating survey techniques with digital trace data collection. His research prioritizes developing error-minimization frameworks for web tracking and data donation systems, while innovating survey methodologies through emoji-based responses, image analysis, and voice input interfaces. He examines generational differences in survey participation and cross-national variations in polarization and income perception. His publication portfolio reveals a dominant trend in hybrid data collection approaches, merging traditional surveys with digital footprints. Key thematic clusters include digital trace data quality assessment, experimental comparisons of response formats (sliders vs. radio buttons, images vs. text), and computational solutions for bias reduction in affective polarization studies. His work consistently addresses methodological validity in cross-cultural online panels. Bosch-Jover has secured significant research funding through ERC grants CHRONO and WEB DATA OPP, collaborating with institutions including The Alan Turing Institute, Wellcome Trust, and University of Southampton. His professional trajectory demonstrates extensive grant management experience in large-scale international survey projects. He operates within the Leverhulme Centre for Demographic Science’s interdisciplinary ecosystem and the Research and Expertise Centre for Survey Methodology’s methodological innovation hub, contributing to teams that bridge demographic science, computational statistics, and social research design.

Pablo Cárdenas RamírezView profile

Assistant Professor

• Bioengineering
• Evolution
• Systems and Synthetic Biology
• +2 more

Pablo Cárdenas Ramírez is an incoming Assistant Professor in the R.F. Smith School of Chemical and Biomolecular Engineering at Cornell University, commencing summer 2026. A Colombian native from Bogotá, he earned his B.Sc. in Microbiology from Universidad de los Andes (2018) and Ph.D. in Biological Engineering from MIT (2024). Currently, he conducts postdoctoral research on influenza immunity and evolution at the Ragon Institute and Harvard Medical School. His academic credentials include: B.Sc. Microbiology, Universidad de los Andes, Bogotá, Colombia (2018) Ph.D. Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA (2024) Dr. Cárdenas Ramírez pioneers multiscale evolutionary engineering through his upcoming Multiscale Evolutionary Engineering Lab (mseelab.org). His research integrates synthetic biology and computational modeling to quantitatively engineer evolutionary processes from molecular to population levels. Key methodologies involve orthogonal transcriptional control systems, CRISPR-based pathogen manipulation, and machine learning-enhanced simulations to predict evolutionary trajectories. Applications span immunoengineering for infectious diseases and cancer, microbiome therapeutics for human health and agriculture, and synthetic cell factories for industrial biotechnology, emphasizing predictive uncertainty quantification in evolutionary design. His publication record demonstrates a cohesive interdisciplinary trajectory merging synthetic biology, computational epidemiology, and pathogen engineering. Dominant themes include CRISPR-Cas applications for microbiome modulation and infectious disease treatment, malaria parasite manipulation via orthogonal gene regulation, and big data-driven pandemic response modeling. The work consistently bridges high-precision wet-lab experimentation with advanced computational frameworks, reflecting a systems-level approach to evolutionary bioengineering challenges. No scientific awards were documented in the source materials. Committed to pedagogical excellence, Dr. Cárdenas Ramírez developed mentorship resources as an MIT Teaching Development Fellow and earned a Teaching Certificate through the Teaching and Learning Lab. His five-year service in MIT's REFS program as a peer counselor and conflict coach underscores his dedication to inclusive academic communities. While specific grants remain unspecified, his research has been supported by institutions including MIT, the Ragon Institute, and Harvard Medical School, with future work anticipated through Cornell University mechanisms. The Multiscale Evolutionary Engineering Lab will establish cutting-edge capabilities in evolutionary prediction and engineering, featuring synthetic biology platforms for pathogen manipulation, computational frameworks integrating mechanistic simulations with machine learning, and translational pipelines for therapeutic development across infectious disease, oncology, and microbiome applications.