Maximilian Gehring | Software Engineering | Best Researcher Award

Published on by Global Mechanics Awards

Mr. Maximilian Gehring | Software Engineering | Best Researcher Award

Research Assistant at Technical University of Darmstadt | Germany

Mr. Maximilian Gehring is a distinguished German researcher and doctoral candidate at the Technical University of Darmstadt, specializing in the integration of digital technologies into construction logistics and intelligent infrastructure systems. His academic journey combines industrial engineering and civil engineering expertise with a strong focus on digital transformation, automation, and Building Information Modeling (BIM). Through his ongoing doctoral research, Further development of digital construction logistics: Design of a digital twin framework for automated construction logistics management, Gehring advances the field of smart construction by developing scalable frameworks that enhance data-driven decision-making and operational efficiency. His scholarly contributions include the publication IoT-altimeter in smart pallets for material tracking on multi-storey construction sites, which explores innovative Internet of Things solutions for improving material tracking and site logistics. In ConLogAI – Concept for an AI-enabled platform for construction logistics scheduling, he presents a robust artificial intelligence framework that optimizes scheduling and resource allocation in complex construction environments. His work Unlocking BIM Potential: Empowering Collaboration Through an Open Source-Powered BIM API Platform for Building Lifecycle Management highlights his commitment to open-source collaboration and interoperability in BIM-driven ecosystems. Additionally, his paper Data fusion approach for a digital construction logistics twin underscores his expertise in merging multiple data streams to build comprehensive digital representations of construction processes. Recognized for his academic excellence, Gehring achieved second place in the RKW Competence Centre’s ‘AufITgebaut’ competition for his master’s thesis on construction site logistics optimization. With advanced programming proficiency in Python, C#, and SQL, alongside experience in tools such as Revit, Docker, and Unity, he bridges engineering, computer science, and management to drive innovation in smart construction and digital infrastructure systems.

Profile: Scopus | Orcid | Google Scholar

Featured Publications:

Gehring, M., & Mantel, H. (2025). Towards a more sustainable re-engineering of heterogeneous distributed systems using cooperating run-time monitors. In Proceedings of the book chapter.

Putz, F., Haesler, S., Völkl, T., Gehring, M., Rollshausen, N., & Hollick, M. (2024, November 11). PairSonic: Helping groups securely exchange contact information. In Proceedings of the Conference. ACM.

See, R. A., Gehring, M., Fischer, M., & Karuppayah, S. (2023, December 4). Binary sight-seeing: Accelerating reverse engineering via point-of-interest-beacons. In Proceedings of the Conference. ACM.

Donghyun Kim | Software Engineering | Best Researcher Award

Published on by Global Mechanics Awards

Mr. Donghyun Kim | Software Engineering | Best Researcher Award

PhD student | Eul-Ji University | South Korea

Donghyun Kim is a highly accomplished researcher and senior associate at PricewaterhouseCoopers Consulting, specializing in advanced artificial intelligence applications, large language models, and LLMOps, with extensive expertise in computer vision, image processing, deep learning, and AI-driven data valuation. He has led and contributed to cutting-edge projects in segmentation, classification, one-class learning, image generation, super-resolution, colorization, 3D reconstruction, and AI agent development. Donghyun earned his Master’s and Bachelor’s degrees in Electronics and Information Engineering from Korea University, where his research focused on 3D skin surface reconstruction from single images using illumination correction and conditional generative adversarial networks for haptic tele-palpation. His research experience spans academia and industry, including senior research roles at Synapse Imaging where he headed the AI team, and visiting researcher positions at the University of Paris-Est, Créteil, focusing on rehabilitation technologies for Parkinson’s disease and gait cycle analysis. He has also worked on multi-target tracking, random finite sets, and advanced filtering techniques in 3D information processing. His publications demonstrate high-impact contributions in AI-driven imaging, tactile surface restoration, and accurate depth estimation for dynamic haptic applications, reflecting a strong commitment to interdisciplinary innovation, technological development, and practical implementation across healthcare, imaging, and AI systems.

Profile: Orcid

Featured Publications: