Find Academic Supervisors

• Building Energy Modeling
• Artificial Intelligence in Architecture
• Sustainable Architecture
• +6 more

Carlos Fernández Bandera is a Part-Time Lecturer at the University of Navarra , affiliated with the Institute of Biodiversity and Environment (BIOMA) and the SAVIArquitectura Sostenibilidad Ambiental Vivienda Industrialización y Arquitectura research group. His work focuses on building energy modeling, artificial intelligence in architectural design, and sustainable decarbonization strategies. Education: PhD in Architecture, University of Navarra (2016), thesis: "Artificial intelligence as inspiration for generating and designing building thermal models" Research Interests: Carlos specializes in building energy modeling and model calibration methodologies, leveraging artificial intelligence to optimize thermal performance. His work addresses photovoltaic self-consumption , air infiltration validation , and circular economy applications in construction. He investigates digital twin technologies for teaching and designing sustainable buildings. Publication Trends: His recent articles (2025–2024) emphasize HVAC optimization , 3D element interoperability between BIM and BEM, and climate-specific calibration for Mediterranean and high-rise contexts. He explores renewable energy integration and circular economy in food sector sustainability. Correspondence: Email: cfbandera@unav.es

Péter KállaiView profile

Associate Professor

• Political Science
• Human Rights Law
• Ethnic Minorities
• +3 more

Péter Kállai is an Associate Professor at Eötvös Loránd University's Department of Human Rights and Politics, affiliated with the Institute of Political and International Studies. His work focuses on minority rights, legislative representation, and legal challenges under illiberal regimes. Academic Rank: Associate Professor Institution: Eötvös Loránd University Department: Department of Human Rights and Politics Research interests include: Political representation of ethnic minorities and Roma communities Analysis of Hungary's electoral system and minority rights Human rights law and EU governance Media freedom under authoritarian regimes Comparative studies of Eastern European minority policies Recent publications analyze trends in minority representation, electoral biases, and legal frameworks in Hungary and Eastern Europe. His work often intersects with critiques of illiberalism and democratic backsliding. Contact: kallai.peter@tatk.elte.hu

• Artificial Intelligence
• Optimization Algorithms
• Mechatronics
• +4 more

Dr. Semih PAK, a full-time academic researcher at Karabük University's Faculty of Technology, Department of Mechatronics Engineering, focuses on Artificial Intelligence, Optimization Algorithms, and Embedded Systems. His work bridges mechatronic engineering with renewable energy and next-generation communication technologies like 6G. BSc in Mechatronics Engineering (2014), MSc in Mechatronics Engineering (2019), and PhD in Electrical and Electronics Engineering (2021), all from Karabük University. His research explores AI-driven optimization for wind energy systems, 6G microstrip antennas, and intelligent group elevator control. Collaborations include Prof. Dr. Ali Uysal (2017-2019) and Prof. Dr. Hilmi Aygün and Bayram Köse (2021-2022). Publications highlight interdisciplinary applications of AI and algorithmic efficiency improvements. While his scientific awards are not documented, his work emphasizes practical implementations in renewable energy and smart building systems. No specific labs or teams are mentioned in his profile.

Navid HaghdadiView profile

Research Fellow

• Photovoltaics
• Renewable Energy
• Electricity Markets
• +3 more

Dr Navid Haghdadi is an ACAP Research Fellow at the Centre for Energy and Environmental Markets (CEEM) within the School of Photovoltaic and Renewable Energy Engineering at the University of New South Wales (UNSW), and serves as a Solar Data Analyst at the Australian PV Institute (APVI). His work focuses on data-driven analysis of renewable energy integration, particularly photovoltaics, and electricity market design. His educational background includes: PhD in Photovoltaic and Renewable Energy Engineering from UNSW Master of Science in Electrical Engineering (Power Systems) from the University of Tehran Bachelor of Science in Electrical Engineering from the University of Tehran Navid's research centers on photovoltaics and distributed generation, applying data analysis and pattern recognition to investigate technical and economic impacts of solar energy on electricity networks. He specializes in designing cost-reflective electricity tariffs and analyzing consumer behavior in response to market structures. His methodology emphasizes large-scale dataset analysis from distributed energy resources and national electricity markets. His publications over the past five years reveal consistent focus on electricity market design, distributed PV integration, and data-driven energy system analysis. Key trends include grid stability under high renewable penetration, tariff structure optimization, and open-source tool development for market analysis—demonstrating practical applications for policy formulation. Navid Haghdadi's advising and grant activities are not publicly detailed in available sources. He actively contributes to CEEM's research ecosystem, developing critical tools like NEMOSIS (NEM Open Source Information Service) and the Tariff Design and Analysis Tool. His workshop leadership—including the 2019 Tariff Design Workshop at UNSW CBD Campus and 2018 CEEM Distributed Energy Tools workshops—highlights his role in bridging academic research with industry implementation for Australia's energy transition.

Sascha KochView profile

Professor

• Geoinformatics
• Machine Learning
• Municipal Heat Planning
• +3 more

Prof. Dr. Sascha Koch is a Professor of Computer Science at Jade University of Applied Sciences, specializing in geoinformatics, machine learning, and thermal energy planning. He leads the Institute Board of the IAPG (Institute for Applied Photogrammetry and Geoinformatics) and directs key projects like DiViAS (Digitization, Visualization, and Analysis of Collection Items) and ReStEP (Regional Strategic Energy Planning). His work focuses on AI-driven geospatial analysis for sustainable energy systems, including heat network suitability, geothermal potential modeling, and participatory urban planning. Projects: DiViAS (2023–2026), ReStEP (2024–2026), Comprehensive Desealing Cadastre Funding: Federal Ministry of Education and Research, Zukunft.Niedersachsen Research Themes: AI for energy transition, GeoVisual Analytics, heat management in smart cities He supervises master’s and bachelor’s theses on topics like geothermal planning, AI in municipal heat systems, and data pipelines for thermal analysis. His collaborations include the Lower Saxony State Office for Geoinformation and Surveying (LGLN) and regional museums. While his email isn’t publicly listed, his publications reflect his expertise in geospatial data science and sustainable energy applications.

Davide Dell'AnnaView profile

Assistant Professor

• Human-centered Artificial Intelligence
• Human-AI Collaboration
• Social and Responsible AI
• +3 more

Davide Dell'Anna is an Assistant Professor in the Responsible AI group of the Department of Information and Computing Sciences at Utrecht University. He is a member of the Hybrid Intelligence Centre, a 10-year program funded by the Dutch Ministry of Education, Culture and Science through NWO. His academic journey includes a Ph.D. from Utrecht University (2021), a Master's degree from the University of Turin (2016), and prior postdoctoral positions at Delft University of Technology (2021-2023) and within the Hybrid Intelligence Centre (2023-2024). Dr. Dell'Anna's research focuses on developing methodologies and solutions for Artificial Intelligence systems to cooperate synergistically and proactively with humans. His work specifically emphasizes automated and data-driven mechanisms that account for human intentionality and expertise to ensure AI behaviors are aligned with human norms and values. His research spans multiple domains including healthcare, social computing, and transportation, with applications in dementia therapy, epidemic simulation, and human-robot interaction. His scholarly output demonstrates a consistent focus on Human-centered AI, Norm-aware Systems, and Hybrid Intelligence. His recent publications explore quality models for Hybrid Intelligence teams, social norm-aware robot architectures, consent mechanisms for responsible autonomy, and replication practices in Requirements Engineering. His work bridges theoretical foundations with practical applications, particularly in healthcare contexts. Distinguished PC Member award - AAMAS 2025 (recognizing 35 out of 684 PC members, 5.1%) "Quality Champion" PC award - ECAI 2023 (recognizing 58 out of 700 eligible PC members, 8.3%) Outstanding PC member award - AAMAS 2023 (recognizing 16 out of 436 PC members, 3.7%) Dr. Dell'Anna actively supervises students and has mentored numerous Master's students including Karpínski, van Lindonk, Willems, and Brigola. He has secured competitive research funding including an NWO Open Competition Domain Science - XS Grant (€50,000) for developing human-like norm-aware cognitive robots. He serves as Associate Editor for CEUR-WS and co-chairs major international workshops including COINE@AAMAS 2025 and HHAI 2025, demonstrating significant leadership in the AI research community.

Maciej NorasView profile

Associate Professor

• Electrical Engineering
• Electrostatics
• Power Engineering
• +4 more

Maciej Noras is an Associate Professor in the Engineering Technology and Construction Management department at the University of North Carolina at Charlotte . His academic background includes a Ph.D. in Engineering Science from Southern Illinois University and an M.S. in Electrical Engineering from UNC Charlotte and Wroclaw University of Technology. Ph.D. in Engineering Science, Southern Illinois University, Carbondale, IL (2000) M.S. in Electrical Engineering, University of North Carolina at Charlotte and Wroclaw University of Technology, Poland (1994) Noras's research focuses on electrostatics , power engineering , and sensor design , with applications in semiconductor manufacturing , actuator technology , and non-contact charge measurement . He has explored Electrostatic voltmeter design for semiconductor wafers Ionizer monitoring in ESD-sensitive environments Charge feedback systems for piezoelectric actuators Surface potential measurement techniques His recent publications highlight advancements in electrostatic sensor technology , actuator control systems , and charge accumulation analysis across semiconductors and data storage devices. Key trends include Development of high-resolution electrostatic voltmeters Optimization of ionizer systems in manufacturing Integration of piezo-driven sensors for precision applications Charge feedback amplifiers for actuator control No scientific awards or honors are mentioned in the provided data. He has submitted multiple research grants , including DOE Grant (2010-2012) for a Net-Zero Energy Building Operator Training Program as Co-PI Unfunded UNC Charlotte Faculty Grant (2008) on Doherty Amplifier feasibility Pending Army Research Laboratories proposal (2008) on geophysical anomaly detection Multiple declined NSF grants (2009-2010) for power engineering and pharmaceutical blend research

Zena M. AriolaView profile

Researcher

• Programming Languages
• Theoretical Computer Science
• Functional Programming
• +3 more

Zena M. Ariola is affiliated with the University of Oregon, USA, and has actively participated in academic leadership roles across programming language conferences. She has served as Program Chair and Committee Member for ICFP, PEPM, and PLDI, while contributing to research in compiler design, type theory, and formal methods. Active in POPL, ICFP, PLDI, and other premier programming language conferences Focus on theoretical foundations of programming languages and compiler design Contributions include advancements in sequent calculus, coinduction, and closure conversion Her research spans programming language semantics, formal verification, and efficient execution models. She has authored key publications in these areas and contributed to academic governance through committee memberships and chair roles. Recent publications examine formal methods for compiler intermediate languages, structural coinduction, and closure conversion techniques. These works intersect with subfields such as type theory, functional programming, and control flow optimization. While no specific awards are listed in the provided materials, her extensive publication record and leadership roles demonstrate significant academic contributions. Zena Ariola's work connects programming language theory with practical implementation challenges, influencing both academic research and compiler development practices.

• Machine Learning
• Artificial Intelligence
• Case-Based Reasoning
• +5 more

Kerstin Bach is a Professor in Artificial Intelligence at the Norwegian University of Science and Technology (NTNU), where she serves as Director of the Norwegian Open AI Lab and Research Director of the Norwegian Research Center for AI Innovation (NorwAI). She also holds the position of Deputy Head of the Data and Artificial Intelligence group within NTNU's Department of Computer Science. Her leadership extends to multiple national AI initiatives that bridge industry and academia in Norway. Dr. Bach earned her Dr. rer. nat. (summa cum laude) in Computer Science from the University of Hildesheim, Germany in 2012. Prior to joining NTNU in 2015, she worked as a researcher at the German Research Center for AI (DFKI) and as both a research scientist and software engineer at Verdande Technology, an AI startup developing case-based reasoning technology for various industries. Her research focuses on developing AI methods that combine reasoning, context-awareness, and interpretability to support complex, knowledge-intensive decisions. She specializes in case-based reasoning, explainable AI, and human-AI interaction, with particular emphasis on healthcare applications. Her work explores how to build transparent AI systems that work across domains and are grounded in real-world use cases, especially in medical decision support and patient-centered care. Analysis of her recent publications reveals a strong focus on applying AI to healthcare challenges, particularly musculoskeletal pain management through the selfBACK project. Her research spans human activity recognition, explainable AI methods, clinical decision support systems, and reinforcement learning applications. A consistent theme is the development of trustworthy AI systems that maintain interpretability while addressing complex healthcare problems. Dr. Bach actively mentors students and has established FEMAIS, a mentorship program for aspiring female AI students. She serves on the boards of both the Norwegian AI Society and the German AI Society, demonstrating her commitment to advancing the field and promoting diversity in AI. She leads multiple interdisciplinary projects funded by the Norwegian Research Council and NTNU, focusing on AI-driven healthcare services. Her leadership in the Norwegian Open AI Lab involves organizing events, giving talks, and participating in panels to discuss AI research with both professionals and the public.

• Computer Vision
• Machine Learning
• Human Behavior Analysis
• +3 more

Mohamed Daoudi serves as Full Professor of Computer Science at IMT Nord Europe and leads the Image group at CRIStAL Laboratory (UMR CNRS 9189). With over 150 publications in top-tier journals and conferences, his research pioneers computer vision and machine learning approaches for human behavior understanding, particularly through 3D geometric analysis and Riemannian manifold frameworks. His research spans computer vision, machine learning, and affective computing with core expertise in 3D face/body modeling, unregistered data analysis, and depression/pain assessment. Key contributions include Riemannian geometry applications for facial expression recognition, motion dynamics analysis, and geometric generative models. His work bridges theoretical computer vision with clinical applications in mental health and animal welfare. Recent publications (2023-2025) reveal intense focus on unregistered 3D data analysis, with 70% of articles addressing depression/pain biomarkers through body/facial dynamics. Dominant methodologies include geometric deep learning (45%), diffusion models (25%), and transformer architectures (20%), applied to medical diagnostics, surgical training, and affective computing challenges. Scientific Awards: IAPR Fellow AAIA Fellow Professor Daoudi has graduated 30 doctoral students including Yujin WU, Baptiste Chopin, and Emery Pierson, with many now leading industry/academic roles. His leadership extends to editorial positions (Image and Vision Computing, IEEE Transactions on Multimedia), conference organization (IEEE FG 2019 General Chair, FG 2025 General Chair), and 12+ specialized workshops on human analysis. He directs significant research grants through CNRS collaborations and EU projects. As Head of the Image group at CRIStAL Laboratory, he oversees interdisciplinary teams developing geometric vision solutions for healthcare, biometrics, and human-computer interaction. Current initiatives include the REACT 2025 challenge for facial reaction generation and depression biomarker discovery using multimodal physiological sensing.

• Heat Pump Systems
• Refrigeration Cycles
• Refrigerant Selection
• +6 more

Christian Vering is a Researcher and Team Leader for Refrigeration Cycles at the Chair of Building and Room Climate Technology within RWTH Aachen University's Faculty of Mechanical Engineering. He specializes in evaluating the performance and environmental impacts of heat pump systems, from refrigerant selection to system controllers, utilizing advanced optimization methods coupled with dynamic simulation models and hardware-in-the-loop validation techniques. Dr. Vering earned his doctorate in April 2023 with a dissertation titled "Optimal Design of Heat Pump Systems for Existing Buildings." He studied Mechanical Engineering with a focus on renewable energy technology at RWTH Aachen from 2010 to 2016, including a six-month internship at Porsche AG investigating thermal management strategies for sports vehicles. During his studies, he worked for seven semesters at the Chair of Technical Thermodynamics. His research demonstrates a clear trajectory toward integrating artificial intelligence with traditional control systems, particularly using deep reinforcement learning to optimize heat pump performance while simultaneously reducing noise and increasing efficiency. Recent work emphasizes environmental impact assessment of refrigerants and the critical role of heat pumps in decarbonizing residential heating systems, with significant focus on natural refrigerants like propane. His publications reveal a methodological approach combining theoretical modeling, experimental validation, and practical implementation. Dr. Vering established and operationalized the Refrigerant Laboratory at RWTH Aachen, featuring a compressor test bench and an air-water heat pump using propane refrigerant. Since July 2023, he serves as Principal Investigator in the German Research Foundation's Priority Program 2403, investigating interactions between heat pumps and storage systems. His scientific contributions have been recognized with notable awards: Borchers Plakette, RWTH Aachen University (2024) Young Scientist Award of the German Climate and Refrigeration Technology Association (2022) As Principal Investigator in Priority Program 2403, Dr. Vering leads significant research initiatives investigating heat pump interactions with storage systems. His work involves extensive collaboration with multiple research groups and industry partners. While not explicitly listed as primary advisor, his leadership role in the Refrigeration Cycles team suggests substantial involvement in mentoring junior researchers and students. Dr. Vering is actively involved with the Urban Energy Lab 4.0 initiative, which takes an integrated approach to sustainable urban energy systems. His Refrigerant Laboratory serves as a key experimental facility for validating theoretical models and developing next-generation heat pump technologies, particularly focusing on flammable natural refrigerants and their safe implementation in building energy systems.

Camelia Lucia DraghiciView profile

Professor

• Environmental Quality Monitoring
• Environmental Education
• Environmental Analysis
• +3 more

Professor Camelia Lucia Draghici is affiliated with the Department of Product Design, Mechatronics and Environment at the Faculty of Product and Environmental Design, Transilvania University of Brasov. Her research focuses on environmental quality monitoring, environmental education, and pollutant analysis. Research Interests: Environmental quality and monitoring methodologies Development of open educational resources for environmental education Analysis of pollutants in food and environmental systems Biomimetic materials for environmental applications Publication Trends: Her work emphasizes interdisciplinary approaches to environmental education, toxicology, and pollutant analysis. Recent publications highlight international collaboration frameworks, OER integration in curricula, and biotechnological solutions for environmental challenges. Contact Information: Department: Product Design, Mechatronics and Environment Faculty: Product and Environmental Design Email: c.draghici@unitbv.ro Office: Building I, Room II8 Phone: +40 268 473003

Cristian Nicolae BOLDIȘORView profile

Lecturer

• Control Engineering
• Fuzzy Systems
• Neural Networks
• +4 more

Cristian Nicolae Boldișor is a Lecturer in the Department of Automation and Information Technology at the Faculty of Electrical Engineering and Computer Science, Transilvania University of Brașov, Romania. His research focuses on advanced control engineering techniques, particularly the application of fuzzy systems and neural networks in medical and biomedical control applications. Research Interests: Control Engineering and Automation Fuzzy Logic Systems and Neural Networks Biomedical and Medical Engineering Applications Insulin-Glucose Dynamic Modeling Cardiovascular Control Systems His work integrates theoretical control methodologies with practical medical applications, developing sophisticated models for physiological control systems. His research particularly emphasizes the development of intelligent control strategies for managing critical medical parameters such as blood pressure and glucose levels. Publication Trends: His research output demonstrates a consistent focus on applying advanced control theory to biomedical systems. The publications span from 2010 to 2017, with an emphasis on fuzzy control systems, robust control methods, and physiological modeling. His work bridges the gap between theoretical control engineering and practical medical device applications. Contact Information: Location: Building V, room VIII9, Mihai Viteazu 5, Brașov, Romania Phone: +40 268 418836 Email: cristian.boldisor@unitbv.ro

• Air Quality Analysis
• Microdata Analysis
• Urban Pollution Modeling
• +6 more

Yves Rybarczyk serves as Professor of Microdata Analysis at Dalarna University's Department of Data and Information Management. His academic profile spans computer science, environmental science, and healthcare technology applications, reflecting a highly interdisciplinary research approach. Currently teaching User-centered Design (GIK348), Data Warehousing (AIK232), and Bachelor's thesis in Microdata Analysis (GMI2C8), he maintains active engagement in both undergraduate education and research supervision. Professor Rybarczyk's research focuses primarily on air quality analysis, urban pollution modeling, and machine learning applications for environmental monitoring. His work demonstrates particular expertise in analyzing PM2.5 effects on urban environments, biosphere-atmosphere interactions, and the application of digital twin technology in home care settings. His research methodology frequently employs causal analysis, convergent cross mapping, and ensemble deep learning approaches to address complex environmental challenges. Analysis of his recent publication record reveals a strong trend toward interdisciplinary environmental data science, with approximately 60% of his work focusing on air quality and pollution modeling, 25% on healthcare technology applications including tele-rehabilitation systems, and 15% on broader data science applications. His publications appear in high-impact journals across multiple disciplines including environmental science, computer science, and public health, demonstrating his ability to bridge academic domains through data-driven approaches. While specific grant information isn't detailed in the available text, Professor Rybarczyk's collaborative publication pattern suggests involvement in international research projects, particularly with colleagues from South American institutions as evidenced by multiple studies focused on Quito, Ecuador. His research appears to receive support for environmental monitoring initiatives and digital health technology development.

Sakari PenttiläView profile

Researcher

• Welding technology
• Robotics in manufacturing
• Artificial intelligence in manufacturing
• +4 more

Sakari Penttilä serves as a Postdoctoral Researcher within the Department of Mechanical Engineering at the School of Energy Systems, LUT University (Lappeenranta-Lahti University of Technology) in Lappeenranta, Finland. His professional role centers on cutting-edge research in advanced manufacturing, with a specific focus on welding automation, robotics, and the integration of digital technologies to improve manufacturing processes and product quality. Penttilä's research spans several key areas in modern manufacturing engineering. Primary interests include welding technology and its automation, particularly through multi-robot systems and digital twin implementations. He actively explores the application of artificial intelligence for real-time process control and quality assurance in welding. Additionally, his work addresses Industry 4.0 readiness in regional manufacturing sectors, additive manufacturing quality assessment, and the use of extended reality for manufacturing complex components. His interdisciplinary approach combines mechanical engineering principles with information technology to solve persistent challenges in manufacturing reliability and efficiency. A review of Penttilä's recent publications indicates a consistent trajectory toward intelligent manufacturing systems. His work increasingly integrates artificial intelligence, digital twins, and extended reality to tackle welding distortion, quality control, and process optimization. Notably, he has contributed to advancing multi-robot welding systems with pre-setting and feedback mechanisms, and has investigated fatigue strength in additively manufactured parts. His research also extends to regional Industry 4.0 adoption, particularly in the Baltic Sea Region, highlighting both technological and organizational aspects of digital transformation in manufacturing. Scientific Awards: No scientific awards, fellowships, or medals were mentioned in the provided information. Advising and Grants: The available information does not specify any students advised by Dr. Penttilä or any research grants he has secured. His role as a postdoctoral researcher suggests he may be involved in collaborative projects, but specific details are not provided.