Find Academic Supervisors

Manuel FerdikView profile

Associate Professor

• RFID Technology
• Wireless Sensor Networks
• IoT Applications
• +3 more

Manuel Ferdik is currently the Head of Research Focus Electronics & Data Analytics at the Management Center Innsbruck (since 2023) and holds the position of Associate Professor (FH) there since 2021. Previously, he served as Senior Lecturer (2021), Lecturer at Kufstein University of Applied Sciences (2018–2021), and University Assistant at the University of Innsbruck (2014–2019). He earned his Dr. techn. in Technical Sciences from Leopold-Franzens-University Innsbruck (2015–2019), M.Sc. in Industrial Engineering, and dual Dipl.-Ing./B.Sc. in Mechatronics. Research Interests include RFID technology, low-power electronics, wireless sensor networks, IoT applications, and Industrie 4.0. His work focuses on optimizing energy efficiency in embedded systems, developing secure communication protocols for passive devices, and advancing data analytics in industrial contexts. Awards include the prestigious Eduard Wallnöfer Prize (2023) and Science Prize 2019 from Tyrol Chamber of Commerce. He has supervised numerous theses in automation, predictive maintenance, AI-driven solutions, and digital transformation. His teaching spans electrical engineering, data science, IoT, and Industry 4.0 across multiple institutions. He also holds a Lean Production Green Belt certification from Danube University Krems.

• Sensor Systems
• Embedded Systems
• Ultrasound Imaging
• +7 more

Stefan Johann Rupitsch is a Professor at the University of Freiburg, leading the Professorship for Electrical Measurement Technology and Embedded Systems since December 2020. He holds a prominent role in academic and industrial research collaborations, focusing on interdisciplinary fields such as sensor systems, biomedical engineering, and embedded technologies. His work bridges theoretical research with practical applications, including drug delivery systems, environmental monitoring, and disaster response technologies. **Education**: Information not explicitly provided in the text. **Research Interests**: His primary research areas include wireless sensor networks, ultrasound imaging for biomedical applications, magnetic nanoparticle localization, and energy-efficient embedded systems. He has pioneered advancements in magnetomotive ultrasound for drug targeting and developed innovative sensor platforms for industrial and environmental monitoring. His projects often integrate machine learning and robotics to enhance system precision and autonomy. **Projects**: As a project manager or coordinator, he oversees initiatives such as wireless microsensor probes for tree canopy monitoring (B1), cochlear implant sensing (CIAS), and disaster-site radar systems (avaRES). Recent efforts focus on sustainable sensor technologies for wear part optimization (Smart Belt) and gas infrastructure resilience (LEAKALERT). **Grants & Advising**: Rupitsch has supervised numerous theses in fields like sensor design, AI for building acoustics, and earthquake monitoring. He actively participates in reviewing academic works and industry projects, reflecting his leadership in technical communities. **Labs & Teams**: His research is conducted through collaborations with the Microsystems for Biomedical Imaging Laboratory and the Sustainability Performance Center, emphasizing interdisciplinary teamwork and real-world impact.

• Telecommunications Engineering
• Electromagnetic Field Theory
• Wireless Sensor Networks
• +3 more

Dr. Jarosław Emilianowicz holds a PhD in Electrical Engineering and serves as a researcher at the Department of Telecommunications and Teleinformatics within Wrocław University of Science and Technology's Faculty of Information and Communication Technology. Doctoral degree in Electrical Engineering Specializes in electromagnetic field applications and wireless communication systems Active in LPWAN technologies and IoT implementations His research spans electromagnetic field shaping, wireless sensor networks, and real-time location systems. Recent work focuses on LoRaWAN-based environmental monitoring in large buildings, demonstrating practical IoT applications for smart infrastructure. Publications show expertise in microwave techniques, WLAN security analysis, and embedded communication systems. Key technical interests include signal processing algorithms, secure wireless transmission mechanisms, and microprocessor-based measurement devices. Active in conference proceedings and book chapters related to telecommunications applications, with contributions appearing in IEEE publications and Polish technical monographs.

Christoph GoebelView profile

Professor

• Energy Management Systems
• Renewable Energy Integration
• Smart Grids
• +4 more

Prof. Christoph Goebel is a Professor of Energy Management Technologies at the TUM School of Engineering and Design, Technical University of Munich. His research focuses on optimizing energy systems through advanced algorithms, machine learning, and data-driven approaches. Key areas include renewable energy integration, smart grid technologies, electric vehicle charging optimization, and the application of graph neural networks in power systems. His work bridges theoretical advancements with practical implementation, such as developing platforms like e-SparX for collaborative machine learning in energy research and frameworks like EnergyOS for modular energy management systems. Recent studies explore thermal energy storage models, cost-effective CO2 reduction strategies via heat pumps, and the economic incentives of wind energy data sharing. Goebel's publications (2016–2025) consistently emphasize predictive control, optimization under market constraints, and the integration of ICT innovations into energy infrastructure. Notable contributions include transfer learning models for building thermal dynamics and benchmarking frameworks for energy hardware-software systems.

Huacheng ZengView profile

Associate Professor

• Computer Networking
• Wireless Communication Systems
• Sensing Technologies
• +3 more

Huacheng Zeng is an Associate Professor in the Department of Computer Science and Engineering (CSE) at Michigan State University (MSU), part of the College of Engineering. His research focuses on computer networking, wireless communication systems, and sensing technologies with applications in IoT security, signal processing, and machine learning. He received his Ph.D. in Computer Engineering from Virginia Tech in 2015 and was awarded the NSF CAREER Award in 2019. Dr. Zeng’s work spans innovative areas such as radar-based human motion tracking (e.g., RadEye), acoustic emotion decoding, and mmWave network optimization. His recent publications address challenges in device localization, vehicular communication, and secure RFID systems. His research often integrates machine learning techniques with traditional signal processing to enhance system performance and security. Education: Ph.D., Computer Engineering, Virginia Tech (2015) Awards: NSF CAREER Award (2019) His contributions to interference management, jamming-resilient communications, and distributed inference frameworks have advanced both theoretical and applied aspects of wireless networks. While no specific grants or advising details are listed, his extensive publication record reflects active collaboration in cutting-edge research domains.

Jesus Rafael Hernández MonteroView profile

Researcher

• Animal Behavior
• Cognitive Ecology
• Chiroptera Research
• +2 more

Dr. Jesus Rafael Hernández Montero is a Researcher at the Department of Applied Zoology and Nature Conservation at the University of Greifswald. His work focuses on associative learning in bats, particularly how they recognize suitable roosts through cognitive mechanisms. University: University of Greifswald Department: Applied Zoology and Nature Conservation Research Focus: Bats' roost selection and cognitive processes Research Interests: Dr. Hernández Montero investigates associative learning in bats, specifically how they connect external roost characteristics with suitability. His studies emphasize cognitive mechanisms in roost localization and knowledge retention. Publications: His recent work includes experiments on acoustic cues in artificial roost attraction and memory retention in free-ranging bats, utilizing RFID technology for monitoring.

Simon NestlerView profile

Professor

• Human-Computer Interaction
• User Experience Design
• Interactive Systems
• +9 more

Prof. Dr. Simon Nestler is a Professor for Human-Computer Interaction at Technische Hochschule Ingolstadt (THI) since 2019, previously at Hochschule Hamm-Lippstadt (HSHL) (2011-2019). He holds a Diploma in Computer Science and a Ph.D. in Human-Computer Interaction from Technische Universität München (TUM) and International Graduate School of Science and Engineering (IGSSE) , supervised by Prof. Gudrun Klinker . Educated: TUM (Diploma), IGSSE (Ph.D.) Affiliations: THI (2019-present), HSHL (2011-2019), Intraworlds (User Experience Engineer) Research Interests focus on applying HCI principles to safety-critical systems , particularly in emergency scenarios . He designs interfaces for car drivers , disaster response teams , and crisis management , addressing challenges like mental workload , collaborative problem-solving , and RFID patient tracking . His work includes developing virtual reality crisis simulations and mobile disaster apps . Teaching includes courses like Masterpraktikum GAMES and FAR Oberseminar . He also offers digital accessibility training , UX workshops , and keynotes on digitalization through his Prof. Nestler Akademie , which has trained 5000+ learners and delivered 100+ corporate trainings .

• Signal Processing
• Embedded Systems
• Machine Learning
• +2 more

Dr. Ergun Erçelebi is a Professor at Gaziantep University's College of Engineering , Department of Electrical and Electronics Engineering. With expertise in Signal Processing , Embedded Systems , and Machine Learning , he has led research in power electronics, wireless localization, and biomedical applications. PhD in Electrical-Electronics Engineering (Gaziantep University, 1999) MSc in Electrical-Electronics Engineering (Gaziantep University, 1992) BSc in Electrical-Electronics Engineering (Middle East Technical University, 1990) His research spans power electronics (multilevel inverters, photovoltaic systems), signal processing (speech enhancement, wavelet transforms), and embedded systems (UAV control, RFID localization). Recent work focuses on hybrid optimization techniques and deep learning for harmonic reduction, modulation classification, and biomedical antenna design. His 2021-2024 publications demonstrate trends in machine learning applications for Turkish lira recognition, UAV-bird classification, and metamaterial design. Earlier work (2014-2020) includes energy management systems, medical imaging phantoms, and smart home automation. 2024: Stanford Most Effective Scientists recognition 15+ patents in embedded systems and medical devices He has supervised 7+ graduate student projects and led 8 research grants, including TÜBİTAK 1501 funding for wearable nebulizer design. His work includes developing smart security systems , remote energy management devices , and RFID-based indoor localization solutions.

• Artificial intelligence
• Data mining/analytics and knowledge discovery
• Data science
• +4 more

Professor Simeon Simoff is Dean of the School of Computer, Data & Mathematical Sciences at Western Sydney University , with a career spanning institutions like University of Technology Sydney , University of Sydney , and Middle East Technical University . His work bridges Artificial Intelligence , Data Mining , and Virtual Worlds , focusing on visual analytics and human-computer interaction . Qualifications: PhD, Moscow Power Engineering Institute MScEng, Moscow Power Engineering Institute BScEng, Moscow Power Engineering Institute Research Interests include AI interpretability , data sonification , and immersive environments , as evidenced by projects like Visual Data Mining (Springer, 2008) and FriendZone Smart Living Space (2010-2011). His 15 most recent publications (2014-2021) span genomics visualization , RFID healthcare applications , and 3D virtual agent design . Awards & Leadership: Founding Director of the Institute of Analytics Professionals of Australia Editor of ACS Conferences in Research and Practice in Information Technology (CRPIT) series Associate Editor for ASCE's Journal of Computing in Civil Engineering Projects include Waves of Words (2018-2022, Australian Research Council) and Deep Learning of Complex Genomics Data (2016-2017, Cancer Institute NSW), with collaborations across Sydney Children's Hospital Network and Intersect Consortium .

• Wireless Networks
• Mobile Systems
• Network Protocols
• +3 more

Lili Qiu is a Professor in the Department of Computer Science at the University of Texas at Austin and Vice Managing Director of Microsoft Research Asia (Shanghai). She previously worked at Microsoft Research Redmond (2001-2004). Her research spans wireless networks, mobile systems, and network protocols, with recent work in acoustic sensing and AI-driven networking solutions. Research Focus Qiu's research addresses fundamental challenges in: Wireless network performance and interference management Mobile system optimization for real-world environments Acoustic-based localization and tracking technologies Deep learning applications for network reliability Next-generation cellular architectures (5G and beyond) Publication Trends Her recent publications (2020-2023) demonstrate a shift toward multimodal sensing systems combining acoustics and computer vision, edge intelligence optimization, and robust mobility management for next-generation networks. This reflects industry-academia convergence through her dual appointments. Awards and Honors IEEE Fellow (2017) ACM Fellow (2018) National Academy of Inventors Fellow (2022) N2Women: Stars in Networking (2017) ACM Distinguished Scientist (2013) NSF CAREER Award (2006) Best Paper Awards: ACM MobiSys 2018, IEEE ICNP 2017 Leadership and Affiliations She bridges academic research and industrial innovation through her joint appointment at UT Austin and Microsoft Research Asia, where she oversees strategic research directions in computing systems.