Lancho, Gino
Short Bio
Gino Lancho is a research assistant and PhD student at the Chair of Logistics Management. He received his diploma in Business Informatics with distinction from the Technical University of Dresden (TU Dresden), specializing in the intersection of computer science and economics. During his studies at TU Dresden, he wrote his diploma thesis on robust deep representation learning for vehicle data at the Bosch IoT Lab (Chair of Information Management) at ETH Zurich. Accompanying his studies, Gino gained additional practical experience through internships and student seminars with industry partners such as Wandelbots. These interdisciplinary endeavors further exposed him to software engineering, data-driven analytics, and project management in diverse industries such as semiconductor manufacturing or IT consulting. He also worked as a student assistant in health technology projects at TU Dresden.
Since graduating in late 2021, Gino has been working at the Fraunhofer Institute for Cognitive Systems in Munich. There, he contributed to industry projects and conducted translational and applied research on trustworthy artificial intelligence (AI) in healthcare and predictive maintenance.
His research interests are centered around the intersection of supply chain management and AI.
Selected publications
Zamanian, Alireza/von Kleist, Henrik/Ciora, Octavia-Andreea/Piperno, Marta/Lancho, Gino/Ahmidi, Narges (2024): Analysis of Missingness Scenarios for Observational Health Data, Journal of Personalized Medicine, Vol. 14, No. 5, 514, doi: external page 10.3390/jpm14050514
Graf, Johannes/Lancho, Gino/Zschech, Patrick/Heinrich, Kai (2022): Where Was COVID-19 First Discovered? Designing a Question-Answering System for Pandemic Situations, in: Proceedings of the Thirtieth European Conference on Information Systems (ECIS 2022), 1-19, doi: external page 10.48550/arXiv.2204.0878