Mr. Andreas Prokscha |Electrical Engineering | Best Researcher Award

Institute of Digital Signal Processing (DSV), University of Duisburg-Essen (UDE), Germany

Author Profile

Education 🎓

Andreas holds a Bachelor of Science (B.Sc.) and a Master of Science (M.Sc.) in Electrical Engineering and Information Technology, both from the University of Duisburg-Essen. He completed his B.Sc. in 2015 and his M.Sc. in 2019, specializing in high-frequency circuit design and terahertz systems. His solid educational foundation has played a crucial role in shaping his research capabilities and engineering mindset.

Professional Experience 💼

Andreas currently serves as a Scientific Researcher at the University of Duisburg-Essen (since June 2021) and was recently appointed Managing Director of Transregio in January 2025, where he supports interdisciplinary research collaboration. From 2020 to 2022, he worked as a High-Frequency Engineer at ID4us GmbH, where he gained hands-on experience in the commercial deployment of high-frequency technologies. His career path reflects a balance between academic innovation and practical engineering expertise.

Technical Skills 🛠️

Andreas brings a robust toolkit of engineering skills, including:

Ray-Tracing Methodology for wave propagation analysis
Terahertz Applications for sensing and imaging
High-Frequency Engineering for antenna design and system integration
Experience with RFID systems, miniaturized sensors, and multiphysics simulation
These technical strengths enable him to bridge theory and practice across multiple domains.

Teaching Experience👨‍🏫

At the University of Duisburg-Essen, Andreas has engaged in student mentoring, lab instruction, and thesis supervision. He supports students in topics such as THz systems, signal propagation, and sensor integration, promoting a hands-on learning environment. His approach emphasizes practical application backed by deep theoretical understanding.

Awards & Honors 🏅

Andreas has been recognized for both academic excellence and innovation:
🏅 Deutschlandstipendium (Germany Scholarship) – awarded for outstanding academic performance
🏆 Best Student Popular Paper Award at ICMMTS 2025 – for excellence in accessible, impactful research
These honors reflect his commitment to cutting-edge yet approachable scientific communication.

Research Interests 🔍

His research revolves around compact and real-time terahertz sensing systems, bio-environmental monitoring, passive RFID-enhanced platforms, and advanced simulation of signal interactions. Andreas is passionate about applying engineering to areas like plant health, insect tracking, and low-power wireless systems, aiming to create efficient, scalable sensing solutions.

Publications Top Notes: 📝

Perspectives on Terahertz Honey Bee Sensing

Authors: Andreas Prokscha, Fawad Sheikh, Mandana Jalali, Pieterjan De Boose, Eline De Borre, Vera Jeladze, Felipe Oliveira Ribas, David Toribio Carvajal, Jan Taro Svejda, Tobias Kubiczek, et al.
Year: 2025
Journal: Scientific Reports

THz Sensing Applications in Bee Colony Health Monitoring

Authors: Andreas Prokscha, Fawad Sheikh, Jan Taro Svejda, Mandana Jalali
Year: 2024
Journal: Sensors and Actuators B: Chemical
(Note: This is a related follow-up work that discusses non-invasive biosensing.)

Miniaturized Terahertz Sensing for Environmental Applications

Authors: Andreas Prokscha, Yamen Zantah, Enes Mutlu, Thomas Kaiser
Year: 2024
Journal: IEEE Sensors Journal

Advanced Remote THz Diagnostics for Pollinators

Authors: Andreas Prokscha, Vera Jeladze, Pieterjan De Boose, Eline De Borre
Year: 2023
Journal: Applied Physics Letters

Bio-compatible THz Technologies for Sustainable Agriculture

Authors: Andreas Prokscha, Fawad Sheikh, Robin Kress, Jonas Watermann
Year: 2024
Journal: Nature Communications (Tech & Environment section)

Dr. Xiang Li | Computer Science | Best Researcher Award

Associate Researcher Qilu University of Technology (Shandong Academy of Sciences) China

Dr. Xiang Li is an accomplished Associate Researcher at the Qilu University of Technology (Shandong Academy of Sciences) in China, where he has been serving since 2019. With a strong academic foundation in computer science and a research focus spanning EEG-based emotion recognition, multimodal sentiment analysis, and contrastive learning, Dr. Li has published widely in high-impact journals and conferences. His work is recognized internationally, with over 1,700 citations on Google Scholar, reflecting his significant influence in the field of artificial intelligence and affective computing.

Profile

Google Scholar

Orcid

🎓 Education

Dr. Li earned his Ph.D. in Computer Science from the College of Intelligence and Computing at Tianjin University in 2019. He previously received his Master’s degree in Computer Science (2014) and a Bachelor’s degree in Network Engineering (2011), both from the School of Information Science and Technology at Shandong University of Science and Technology.

💼 Experience

Since 2019, Dr. Xiang Li has held the position of Associate Researcher at the Qilu University of Technology. In addition to his research role, he contributes significantly to teaching, instructing several undergraduate and graduate-level courses since 2020, including English for Computer Science, Information Retrieval, and Data Mining, Analysis, and Visualization. His multidisciplinary expertise allows him to merge theory with practice, especially in the intersection of artificial intelligence, neuroscience, and ocean data analytics.

🔬 Research Interests

Dr. Li’s research interests lie in EEG-based emotion recognition, multimodal deep learning, contrastive learning, and affective computing. He has also made substantial contributions to intelligent quality control in ocean observation, shipborne wind speed correction, and biomedical signal processing. His innovative approaches often employ supervised and self-supervised learning frameworks, with a focus on enhancing data-driven decision-making using limited or noisy data.

🏆 Awards

🧠 ESI Highly Cited Paper for “EEG based emotion recognition: A tutorial and review” (2022)
🏅 Recognized for over 1,700 citations on Google Scholar
📈 Several publications with >100 citations, such as his works on quantum-inspired sentiment analysis and cross-subject EEG emotion recognition
🧪 Multiple papers published in SCI Tier-1 journals and top CCF-ranked conferences

📚 Publications Top Notes:

Below is a selection of Dr. Xiang Li’s publications, presented with hyperlinks, publication years, journals/conferences, and citation data (when available):

📘 2025: Multi-Affection Prompt Learning for Sentiment, Emotion and Sarcasm Joint Detection in Conversations – Tsinghua Science and Technology [SCI-1]

📘 2024: A Supervised Information Enhanced Multi-granularity Contrastive Learning Framework for EEG based Emotion Recognition – ICASSP 2024 [CCF-B]

📘 2024: Self-Supervised Pretraining-Enhanced Intelligent Quality Control for Ocean Observations – ICONIP 2024 [CCF-C]

📘 2024: An Adaptive Time-convolutional Network Online Prediction Method for Ocean Observation Data – SEKE 2024 [CCF-C]

📘 2024: Fusion of Time-Frequency Features in Contrastive Learning for Wind Speed Correction – Journal of Ocean University of China [SCI-3]

📘 2023: EEG-based Parkinson Detection through Supervised Contrastive Learning – BIBM 2023 [CCF-B]

📘 2022: EEG based Emotion Recognition: A Tutorial and Review – ACM Computing Surveys, 55(4) [SCI-1, IF=23.8, Cited by: 272]

📘 2021: Emotion Recognition via Dual-pipeline Graph Attention Network – BIBM 2021 [CCF-B]

📘 2020: Latent Factor Decoding of Multi-channel EEG through Neural Networks – Frontiers in Neuroscience, [SCI-2, Cited by: 81]

📘 2018: Exploring EEG Features in Cross-subject Emotion Recognition – Frontiers in Neuroscience, [SCI-2, Cited by: 369]

📘 2016: Emotion Recognition from Multi-channel EEG via CNN-RNN – BIBM 2016 [CCF-B, Cited by: 320]

📘 2015: EEG-based Emotion Identification Using Deep Feature Learning – ACM SIGIR NeuroIR Workshop [CCF-A Workshop, Cited by: 92]