Find Academic Supervisors

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +3 more

Dr. Don Tuggener is a Researcher at the ZHAW Zurich University of Applied Sciences' School of Engineering, affiliated with the Centre for Artificial Intelligence. His work focuses on Natural Language Processing (NLP), Computational Linguistics, and Machine Learning applications in professional training and AI evaluation. He leads or collaborates on projects such as Meaning@Work (stress management for healthcare professionals), Virtual Kids (child interrogation training), and Favi-Score (bias detection in AI evaluation). His research emphasizes dialogue systems, generative AI ethics, and legal text analysis. Key projects include developing frameworks for conversational AI evaluation (Spot The Bot), large-scale legal text classification (LEDGAR corpus), and innovative training tools using LLMs. He has contributed to over 30 peer-reviewed publications since 2011, spanning topics like compound splitting in German, coreference resolution, and generative AI applications in professional contexts. As an editor for SwissText conferences and reviewer for ACL/EMNLP, he actively participates in the NLP academic community. Project Leadership: Virtual Kids, Interscriber Deputy Leadership: AutoNews, PRISM, SCAI Core Research Themes: AI ethics, dialogue systems, legal NLP Recent work highlights AI's role in professional education (e.g., investigative interviews with children) and societal challenges (hate speech mitigation via social influencers).

• Financial Risk Management
• Econometrics
• Algorithmic Contract Standards
• +3 more

Prof. Henriette Elise Breymann is a Professor in the Department of Finance, Risk Management and Econometrics at the ZHAW School of Engineering, Zurich University of Applied Sciences (ZHAW). Her research focuses on financial risk modeling, algorithmic contract standards (ACTUS), big data analytics, and regulatory technology (RegTech). She has led numerous projects, including Data Driven Financial Risk and Regulatory Reporting, Strengthening Swiss Financial SMEs through Reinforcement Learning, and Explainable AI in Credit Risk Management. Her work intersects finance, physics, and computational methods, with contributions to energy economics (e.g., renewable energy systems), high-frequency financial data analysis, and quantum chaos applications. She co-authored Unified Financial Analysis: The Missing Links of Finance (2009) and pioneered the ACTUS framework for standardizing financial contracts. Projects: 12+ leadership roles in applied finance, risk modeling, and energy systems. Key Expertise: Regulatory reporting, stress testing, and data-driven financial systems. ACTUS Standard: Global initiative for granular financial contract representation. Her research spans interdisciplinary collaborations, including the Risk- and Finance-Lab, and has been presented at major conferences like the Society for Economic Measurement. She advises on regulatory innovations and financial resilience strategies for SMEs.

• Digital Transformation
• Virtual Reality in Education
• Business Process Management
• +3 more

Elke Brucker-Kley is a Professor at ZHAW School of Management and Law, leading the Centre of Information Systems - People & Technology. Her research focuses on digital transformation, virtual reality in education, and ethical technology design. She has co-led projects like 'Immersive Science Fiction Prototyping for Responsible Innovation' and 'Smart Hospital Framework'. Active in academic publishing since 2012, her work spans technology ethics, vocational training, and business process innovation. She holds an ORCID ID (0000-0001-7888-3446) and has advised multiple collaborative industry-academia initiatives. Her research highlights include analyzing VR applications in electrician apprenticeships and German language education, as well as exploring adolescent privacy on TikTok. She has authored/co-authored over 30 peer-reviewed articles and books, including Kundennutzen durch digitale Transformation (2018). Projects under her leadership address challenges like 'Proof-of-Work in VR' and 'AI-based predictive policing scenarios'. Key Research Areas: Digital Ethics, VR Pedagogy, BPM Innovation Notable Contributions: Pioneered immersive narrative scenarios for technology critique Grants & Funding: Multiple industry partnerships (e.g., Swiss Re, Roche) Her work bridges technology adoption, human-centered design, and societal impact, with a focus on responsible innovation paradigms.

• Natural Language Processing
• Data Science
• Artificial Intelligence
• +3 more

Farhad Nooralahzadeh is affiliated with the ZHAW School of Engineering at Zurich University of Applied Sciences (ZHAW), where he holds a Researcher position within the Intelligent Information Systems department. His primary role involves leading and co-leading key projects such as DataGEMS (Horizon Europe), Reliable Multi-lingual Open Data Exploration, and INODE4StatBot.swiss. He has contributed to advancing natural language processing (NLP) and open data exploration systems. Education: Not explicitly stated in the provided text. His research focuses on multilingual NLP applications, knowledge graph systems, and AI-driven data exploration tools. Recent work includes evaluating prompt engineering techniques for knowledge graph question answering and developing bilingual open data exploration frameworks like StatBot.Swiss. Projects emphasize cross-lingual data accessibility and automated SQL translation from natural language queries. Notable contributions include peer-reviewed publications in Frontiers in Artificial Intelligence and the Association for Computational Linguistics conference. He actively collaborates with institutions like the EU Horizon programs and maintains an ORCID profile (0000-0002-9053-0894). His work bridges theoretical AI advancements with practical applications in data management and linguistic diversity, positioning him as a key figure in intelligent information systems research.

• Applied Discourse Studies
• Text Linguistics
• Conversation Analysis
• +7 more

Prof. Ulla Kleinberger is a Professor of Applied Discourse Studies at the ZHAW School of Applied Linguistics, Zurich University of Applied Sciences (ZHAW). She holds a position at the Institute of Multilingual Communication. Her research focuses on text linguistics, conversation analysis, multilingualism, media linguistics, and professional communication in organizational and healthcare contexts. Her work addresses discourse analysis in healthcare communication, health policy debates, and multilingual challenges in homecare nursing. She has led projects like 'Digital Health for parents facing language barriers' and 'Energy Discourse and Phraseology'. Her publications span peer-reviewed journals, edited volumes, and conference proceedings addressing topics such as intercultural communication, digital media competence among youth, and phraseology in online debates. Key thematic trends in her articles include: 1) Discourse analysis in healthcare contexts (e.g., patient-professional interactions, medical terminology evolution), 2) Multilingual communication challenges in globalized workplaces and healthcare systems, 3) Digital media literacy and youth communication patterns, and 4) Energy policy discourse analysis. Projects often bridge applied linguistics with interdisciplinary fields like healthcare and education. Kleinberger has advised on overcoming language barriers in homecare nursing and collaborated on virtual patient education systems. She co-edited volumes like *Doing Applied Linguistics* (2017) and *Energiediskurs* (2017). Her work emphasizes practical applications of linguistic research to improve communication in healthcare, education, and corporate environments.

Waqar AliView profile

Lecturer

• Pattern Recognition
• Graph Neural Networks
• Deep Learning
• +3 more

Mr. Waqar Ali is a Lecturer and Research Assistant at the ZHAW School of Engineering (Zurich University of Applied Sciences), affiliated with the Machine Perception & Cognition Group. His academic journey includes a Bachelor's (2016) and Master's (2019) in Computer Science from Comsats University. He has held teaching roles at Lahore Garrison University (2021) and Abasyn University (2019–2021). His research focuses on Pattern Recognition, Graph Neural Networks, Deep Learning, and Natural Language Processing. Awards include the Shahbaz Sharif Merit Scholarship (2017) and a Bachelor Fellowship from HEC Pakistan (2012). Notable projects include an Evidence-Based Diagnostic Assistance for Echocardiography initiative. His publications span advanced graph learning techniques, sentiment analysis models, and energy optimization systems. He has contributed to peer-reviewed journals and conferences such as the Joint IAPR Statistical Techniques in Pattern Recognition (2024). His work bridges theoretical machine learning with practical applications in healthcare diagnostics, smart grids, and Urdu language processing. Collaborative projects include roles at the University of Alicante (2024).

• NMR Spectroscopy
• Machine Learning
• Fluid Dynamics
• +2 more

Prof. Dr. Dirk Wilhelm serves as Dean of the School of Engineering and Professor of Medical Physics at Zurich University of Applied Sciences (ZHAW). With extensive experience spanning academic leadership and industry R&D, his work focuses on integrating computational methods with experimental physics. His research bridges NMR spectroscopy, fluid dynamics, and machine learning, with particular emphasis on: Developing deep learning frameworks for NMR spectral analysis and classification Modeling fluid-structure interactions in biomedical devices Advancing computational fluid dynamics for industrial applications Designing cryogenic instrumentation for high-resolution spectroscopy Recent publications demonstrate a strong trend toward AI-driven analytical methods in NMR spectroscopy, with several studies focusing on spectral deconvolution, multiplet classification, and signal processing using deep neural networks. Earlier foundational work established expertise in computational fluid dynamics, particularly in instability analysis and multiphase flow modeling. His research group actively collaborates with industrial partners including Bruker BioSpin, with projects ranging from microturbine design to pharmaceutical pump optimization.

Wolfgang TressView profile

Researcher

• Solar Energy
• Photovoltaics
• Materials Science
• +3 more

Wolfgang Tress is a researcher at the École Polytechnique Fédérale de Lausanne (EPFL), focusing on advanced photovoltaic technologies, particularly third-generation solar cells. His work centers on perovskite materials, exploring their optoelectronic properties, efficiency limitations, and stability challenges. He pioneered investigations into hysteresis phenomena in perovskite devices and contributed to understanding ion migration effects on performance. Key research interests include organic solar cells, perovskite-based optoelectronics (e.g., LEDs and photodetectors), and the development of novel interlayers for enhanced stability and efficiency. Tress received the Zeno Karl Schindler Award 2016 for his contributions to electroluminescent perovskite solar cells. His recent studies leverage machine learning to analyze hysteresis and optimize perovskite properties, while experimental work addresses defects, charge transport, and environmental resilience. Publications highlight advancements in material design, device physics, and stability protocols. Tress collaborates on projects involving perovskite commercialization roadmaps and FAIR data-driven analyses. His interdisciplinary approach bridges material science, physics, and engineering to accelerate sustainable energy solutions.

• Data Science
• Computational Chemistry
• Biochemistry
• +3 more

Dr. Manuel Dömer is a Programme Director for the BSc Data Science program and Co-Head of the ZHAW Datalab at the ZHAW School of Engineering, Zurich University of Applied Sciences. He holds a PhD in Computational Chemistry & Biochemistry from École Polytechnique Fédérale de Lausanne (EPFL) and a Master of Science in Chemistry from Zurich University. His professional development includes a Certificate of Advanced Studies in Higher Education from the University for Teacher Education Zurich (2022). His research focuses on Data Science methodologies, computational chemistry, and molecular dynamics modeling. Notable projects include leading the Soilspector initiative, which employs computer vision for soil property detection. He also serves as a Lecturer in the Master of Applied Information and Data Science at Lucerne University of Applied Sciences and Arts. His work spans roles in Swiss Re, including Lead Modeling & Analytics and Data Scientist positions, highlighting his industry-academia collaboration. Key research interests include advanced computational techniques for chemical systems, data-driven innovation, and educational methodologies in higher education. His publications bridge theoretical chemistry and practical data science applications, emphasizing methodological rigor and interdisciplinary approaches.

• Organic Electronics
• Photovoltaics
• Material Science
• +6 more

Christoph Kirsch is a Researcher at the ZHAW School of Engineering's Department of Organic Electronics & Photovoltaics. His work focuses on interdisciplinary research spanning organic electronics, photovoltaics, materials science, and biomedical engineering. He holds a PhD in Applied Mathematics from the University of Basel (2005) and an MSc in Mathematics from ETH Zurich (2001). His research emphasizes advanced modeling techniques for semiconductor devices, thermal imaging systems, and porous media processes. Key projects include: Advanced Imaging and Machine Learning for PV Quality Assurance Advanced Materials and Characterization Tools for Quantum-Dot Enhanced Displays Skinobi – Affordable Sensor for Skin Condition Tracking Research interests include OLED device simulation, solar cell characterization, and thermal properties of biological tissues. Recent work explores non-invasive skin thermal diffusivity measurement and charge transport modeling in organic semiconductors. His publications reflect a strong focus on multiscale modeling and experimental validation across materials science and biomedical applications. Notable contributions include: Electrothermal modeling of large-area semiconductor devices Development of mathematical models for intradermal drainage quantification Lock-in thermal imaging setups for nanoparticle detection Currently leads the Organic Electronics & Photovoltaics research group at ZHAW, collaborating with industry partners on applied materials science and device optimization projects.

• Data Science
• Healthcare Informatics
• Biomedical Imaging
• +5 more

Dr. Robert Vorburger is a Lecturer and Co-Head of the Research Centre Focus: Data Management & Visualization at the ZHAW School of Life Sciences and Facility Management. He holds a PhD and specializes in interdisciplinary applications of data science across healthcare, agriculture, and industrial systems. His work bridges academic research with real-world enterprise solutions. Education: PhD in Computational Life Sciences (specific university not explicitly listed) Research Focus: His research spans data-driven healthcare solutions , automated image analysis , and IoT-enabled business models . Notable areas include: Development of web-based food frequency questionnaires for public health studies Automated MRI analysis techniques for neurodegenerative diseases Data science education frameworks for modern enterprises Cocoa production optimization through data analytics Recent Trends in Publications: Vorburger's articles reflect a growing emphasis on interdisciplinary problem-solving , with contributions to: Medical imaging biomarkers (WMH quantification, beta-amyloid deposition) Digital agriculture tools (pest surveillance systems) Industry 4.0 business models for manufacturing Projects & Leadership: Deputy leader for Breeding Wheat for High Baking Quality and Compensation Study Universities Project leader for Bridging the Gap: Autonomous Maintenance Services and Predictive Analytics for Hospital Supply Chains Contributions to AWACS Animal Welfare Assessment System and Cocoa in Numbers initiatives Labs & Teams: He leads the Data Management & Visualization Research Centre at ZHAW, focusing on: Enterprise data strategies Healthcare informatics tools IoT-enabled industrial systems

Oliver StrubView profile

Lecturer

• Operations Research
• Quantitative Finance
• Machine Learning
• +3 more

Dr. Oliver Strub is a Lecturer at the University of Bern, affiliated with the Group for Business Analytics, Operations Research and Quantitative Methods. His research focuses on quantitative finance, optimization algorithms, and data-driven decision making. He holds a PhD and has expertise in applying mathematical and computational techniques to financial and operational problems. His research interests include index-tracking portfolio optimization, feature selection in machine learning, and the development of heuristic and mathematical programming methods. He has explored hybrid approaches combining genetic algorithms, MILP models, and data-mining techniques to enhance portfolio performance while adhering to regulatory constraints like UCITS. Recent work emphasizes optimization methods for portfolio management, particularly under constraints such as UCITS regulations. He has developed solutions that blend heuristic algorithms with mathematical programming to achieve efficient financial and operational outcomes. His contributions span algorithmic trading, risk management, and compliance-driven portfolio construction. Dr. Strub's affiliations include the Group for Business Analytics, where he collaborates on projects involving business analytics, operations research, and quantitative methodologies. While no awards or grants are explicitly noted, his extensive publication record reflects a strong focus on practical and theoretical advancements in quantitative fields.

Marialuisa CaveltiView profile

Associate Professor

• Mental Health Care
• Digital Technologies in Psychiatry
• Adolescent Psychiatry
• +3 more

PD Dr. Marialuisa Cavelti is the Head of Research/Group Leader at the University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern. Her academic focus is on clinical research aimed at improving mental healthcare for young people with severe mental disorders such as borderline personality disorder (BPD) and psychosis. She emphasizes collaboration with patients, families, and clinicians, and specializes in applying digital technologies like ecological momentary assessment and intervention to enhance traditional clinical services. Her work addresses gaps in current care, particularly through transdiagnostic approaches. Education: Habilitation in Psychiatry (2023), CV available at CV_Cavelti_April23.pdf. Research Interests: BPD in adolescents, early intervention, psychotic symptoms in youth, digital health technologies, and psychosocial correlates of personality dysfunction. Her research highlights include evaluating stepped-care approaches for BPD, analyzing age-dependent treatment outcomes, and investigating bullying’s impact on personality functioning. She has contributed to over 85 publications, focusing on clinical profiles, therapeutic effectiveness, and neurobiological correlates of self-injury and aggression. Her work spans journals like European Child & Adolescent Psychiatry and Psychological Medicine . Key projects include smartphone-assisted therapies for voice distress (SmartVoices trial) and systematic reviews on home treatment efficacy. She actively participates in international conferences, advocating for transdiagnostic and early intervention strategies. Her lab focuses on translating research into clinical practice, emphasizing real-time interventions and collaborative care models. She collaborates with institutions globally, including Australia and Canada, to advance understanding of adolescent mental health challenges.

• Psychiatry
• Clinical Psychology
• Psychosis Research
• +4 more

Chantal Michel is an Associate Professor and Group Leader at the University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern. She is also the Scientific and Clinical Co-Head of the Early Detection and Intervention Centre for Mental Crisis (FETZ Bern). Her work focuses on early detection and intervention for individuals at clinical high risk (CHR) for psychosis, with expertise in transdiagnostic therapeutic approaches and the application of technologies like ecological momentary assessments and virtual reality. Dr. Michel holds a habilitation in Psychiatry and has led numerous studies on neuroimaging correlates of psychosis risk, cognitive deficits, and mental health service utilization patterns. Her research interests span psychosis spectrum disorders, developmental psychopathology, and the neurobiological underpinnings of mental health issues. Dr. Michel has published extensively on topics such as EEG biomarkers in psychosis, white matter abnormalities in CHR populations, and the implementation of national psychosis prevention networks. She is actively involved in clinical trials and machine learning approaches to personalize treatment decisions for at-risk individuals. Dr. Michel's contributions include pioneering work on age-related effects of psychosis symptoms, the role of coping strategies in psychopathology, and the integration of innovative technologies in mental health monitoring. She has presented her findings at major conferences like the International Early Intervention in Mental Health (IEPA) and the European Society for Child and Adolescent Psychiatry (ESCAP).

• Cybersecurity
• Artificial Intelligence
• Data Security
• +3 more

Dirk Bruckmann is a Researcher affiliated with the Department of Civil, Environmental and Geomatic Engineering at ETH Zurich. His work focuses on cybersecurity, AI-driven threat detection, and critical infrastructure protection. He has collaborated on multiple high-profile research grants including the NSERC Discovery Grant ($180,000), the National CyberSecurity Consortium's IntruderInsight project ($2M), and Mitacs-funded initiatives in fraud detection and federated learning systems. Dr. Bruckmann has received over a dozen prestigious awards and scholarships, including the Best Paper Award at the 2015 IFIP Conference and multiple travel awards from IEEE, ACM, and leading academic institutions. His research emphasizes robust anomaly detection frameworks and secure machine learning methodologies. Key Projects: Robust Threat Detection Framework (2025-2031) IntruderInsight: AI-Driven Cyber Attribution (2025-2027) Secure Federated Learning with Homomorphic Encryption (2023-2025) He contributes to the DANS Lab and maintains active partnerships with industry leaders like Mastercard and HCL Inc. His research spans both theoretical advancements and practical implementations in cybersecurity systems.