Mohab Hassaan is a researcher at the Chair of Computing in Civil and Building Engineering at the Technical University of Munich (TUM). He is actively involved in research projects related to artificial intelligence, building information modeling, and construction simulation. Research focus on AI-driven evacuation design and machine learning for floor plan digitization Co-author of publications in Proceedings of 35. Forum Bauinformatik (2024) and Sensors (2023) Teaching assistant for Software Lab Introduction to Object-Oriented Programming (Winter Semester 25/26) Contact via mohab.hassaan@tum.de or Room 0502.03.219 at TUM
Dana Drachsler Cohen is an Assistant Professor at the Faculty of Electrical and Computer Engineering, Technion, Israel. She leads the SAFE Lab (Secure Artificial Intelligence via Formal Methods and Engineering), focusing on applying formal methods to ensure security guarantees for deep learning models. Her work bridges mathematical verification techniques with practical AI engineering to enhance robustness and transparency. Current Role: Assistant Professor, Technion Lab: SAFE Lab (Secure AI via Formal Methods and Engineering) Email: ddana@ee.technion.ac.il Research Interests: Formal verification of deep learning models Security guarantees in AI systems Transparency through customized programs Robustness against adversarial attacks Differential privacy in classification Scalable formal methods for AI Recent Contributions: The articles highlight her work on robustness verification for few-pixel attacks, global robustness, local differential classification privacy, and maximal robustness specifications using oracle-guided optimization. These studies emphasize formal methods to mathematically prove AI safety while developing practical systems. Teaching & Service: Dana Drachsler Cohen actively contributes to academic service as a committee member in top-tier conferences like OOPSLA, PLDI, VMCAI, and SAS. She also invites students at all levels (PhD/MSc/BSc) to join her research group.
Xiaoxing Ma is a Professor at the State Key Laboratory for Novel Software Technology , Nanjing University , focusing on Software Engineering , Self-adaptive Software Systems , and Software Engineering for Machine Learning . His recent work bridges neuro-symbolic reasoning and formal verification. Key research areas: Software Engineering, Self-adaptive Systems, Neuro-symbolic AI Awards: China National Awards (2006, 2011), MOE Award (2010), CVIC SE Award (2009) His 2023-2024 publications emphasize: Formal semantics for hardware description languages (Verilog) Neuro-symbolic frameworks for mathematical reasoning Dynamic update verification and CRDT model checking LLM-driven API migration and traceability recovery He serves as Program Co-Chair for SEAMS 2024 and contributes to major software engineering conferences (ICSE, ASE, FSE, PLDI).
Maria Antonia Brovelli is a Professor of GIS at Politecnico di Milano (PoliMI) in the Department of Civil and Environmental Engineering and a member of the School of Doctoral Studies in Data Science at Roma La Sapienza University. Formerly Vice-Rector of PoliMI for the Como Campus (2011-2016), she currently leads the GEOLab (Geomatics and Earth Observation Lab) and holds influential roles including Deputy Chair of the ISPRS TC on Spatial Information Science, co-chair of the United Nations Open GIS Initiative, and Chair of the UN-GGIM Academic Network. Her research spans geomatics with evolving expertise from geodesy and radar-altimetry to GIS, webGIS, geospatial web platforms, Volunteered Geographic Information (VGI), Citizen Science, Big Geo Data, and geospatial AI. A global leader in Open-Source GIS advocacy, her work emphasizes open data ecosystems, collaborative mapping, and AI-driven geospatial solutions for environmental challenges. Key methodologies include open-source software frameworks and citizen science integration. Recent publications (2025) demonstrate convergence of AI and geospatial analysis, featuring satellite-ground sensor fusion for urban air quality, high-resolution land cover mapping, zero-shot learning for remote sensing imagery, landslide prediction models, and climate-agriculture impact studies. Dominant themes include open geospatial platforms, transferable AI architectures, and multi-scale environmental monitoring using open data principles. Honors include: Sol Katz Award for Geospatial Free and Open Source Software (OSGeo) As mentor of PoliMI's YouthMappers chapter (PoliMappers), she guides student-led open mapping initiatives. Her editorial leadership as Associate Editor of ISPRS International Journal of Geo-Information shapes discourse in geospatial AI and open science. Research grants span ESA Earth Observation programs, UN initiatives, and international collaborative projects focused on open geospatial infrastructure. Brovelli directs GEOLab at Politecnico di Milano, a hub for geospatial innovation developing open-source tools for earth observation, citizen science platforms, and AI-driven spatial analytics. The lab collaborates with UN-GGIM, ISPRS networks, and ESA projects, driving open standards adoption globally while advancing geospatial AI applications in climate resilience and urban sustainability.
Dr. Yanni Dong is an Associate Professor at the Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan, China. She received her B.S. and Ph.D. degrees from Wuhan University in 2012 and 2017, respectively, and held a Hong Kong Scholar position at The Hong Kong Polytechnic University in 2019. Her educational qualifications include: B.S., Wuhan University, 2012 Ph.D., Wuhan University, 2017 Dr. Dong's research centers on hyperspectral image processing, pattern recognition, and machine learning, with dominant expertise in Metric Learning (33% research fingerprint) and hyperspectral target detection (16%). Her work applies advanced computational methods to remote sensing data for geological interpretation and environmental monitoring, emphasizing dimensionality reduction and transfer learning techniques. Her 2025 publications reveal a strong focus on multimodal fusion and satellite video tracking, leveraging transformer networks and Mamba architectures to solve challenges in oil spill detection and object recognition using SAR/HSI data. These works demonstrate consistent innovation in feature fusion and temporal modeling for geospatial applications. Her recognition includes the Hong Kong Scholar award (2019). She serves as a reviewer for over twenty top-tier journals including IEEE TCYB, TGRS, TIP, TNNLS, TMM, PR, and GRSL. Dr. Dong actively contributes to the academic community as a program committee member for IJCAI and AAAI conferences. While specific details of advised students and grants are not provided, her extensive publication record and editorial service indicate significant research leadership. She is embedded within the Institute of Geophysics and Geomatics research ecosystem, driving advancements in geospatial AI methodologies.
Abdullah Yaqot (born October 7, 1980) is a researcher in wireless communication systems, currently affiliated with the Technical University of Lübeck since 2021. His work focuses on the physical layer of communication systems, with expertise in multi-user MIMO, massive MIMO, cognitive radio, and deep learning for wireless optimization. PhD in Digital Communication (University of Kiel, 2017) Research experience at the Institute for Automation and Communication (ifak, 2019-2020) His research encompasses adaptive precoding, resource allocation, channel estimation, and interference management. Recent publications highlight the integration of deep learning techniques (e.g., attention-based networks, complex neural networks) to enhance spectral efficiency and throughput in industrial IoT and MIMO systems. Selected publications cover topics like hierarchical lossless segmentation for image compression (2022), multicell interference mitigation in massive MIMO (2020), and cognitive radio resource allocation (2014). Collaborations include D. Sun, Y. Xi, H. Hellbrück, and L. Rauchhaupt. Published in journals: IEEE Wireless Communication Letters, Neural Computing and Applications Conference contributions: IEEE ICCC, VTC, WCNC, SAS
Bhaskaran Raman is a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Bombay, where he leads research in networking systems with a focus on practical applications in developing regions. His work spans wireless networking, sensor systems, and mobile computing, with recent expansion into AI-assisted educational technologies. His research interests include wireless mesh networks for rural connectivity, transportation systems monitoring, mobile sensing applications, and educational technology. Notably, his lab has developed innovative solutions like Road-RFSense for traffic estimation in developing regions, FullStop for monitoring unsafe bus stopping behavior, and more recently, AI systems for automatic short answer grading with feedback. Analysis of his publication trends shows a consistent focus on practical networking challenges with strong emphasis on real-world deployment, particularly in resource-constrained environments. In recent years, he has expanded his research to include AI applications in education while maintaining his core expertise in systems research. Raman has mentored numerous graduate students who have become active researchers in networking and systems areas, with many continuing to collaborate with him on publications. His research has been supported by various grants focused on networking for developing regions and smart transportation systems. His lab at IIT Bombay focuses on building practical networking solutions with real-world impact, particularly for transportation safety and educational applications. The team combines expertise in wireless systems, mobile computing, and increasingly, artificial intelligence to address complex challenges in these domains.
Vanessa Frohn is a Scientific Researcher and doctoral candidate at the Institute for Technologies and Management of Digital Transformation at the University of Wuppertal, where she has been affiliated since April 2025. Her work focuses on advanced data analysis techniques within the domains of machine learning, deep learning, and large language models. Education: Bachelor of Science in Physics, Ruhr University Bochum Master of Science in Astrophysics, University of Bonn Her research journey began in astrophysics, where she specialized in the analysis and evaluation of radio astronomical data using algorithms based on probability distributions. This strong quantitative foundation has informed her current interdisciplinary work in digital transformation and artificial intelligence. Her research integrates methodologies from data science and machine learning to address complex challenges in digital systems. Although no publications are listed, her focus areas suggest contributions in algorithmic development, probabilistic inference, and scalable AI models. Scientific Awards: Vanessa Frohn is actively engaged in her doctoral research but there is no public information available about advising students or securing research grants at this time. She is based in office FZ.00.01 and can be reached via email or phone as listed. There is no mention of lab or team leadership, though her work is likely integrated within the broader research activities of the Institute for Technologies and Management of Digital Transformation.
Prof. Dr. Henner Gärtner is a full Professor for Industrial Logistics in the Department of Mechanical Engineering and Production at Hamburg University of Applied Sciences (HAW Hamburg). He is also Program Coordinator of the cooperative Mechanical Engineering program with the University of Shanghai for Science and Technology, Chairman of the Study Reform Committee, and deputy member of the Department Council. Education & Academic Focus Doctorate (Dissertation on stock-out cost quantification, PZH-Verlag, 2011) Research stays and teaching activities in Germany and China Research Interests Prof. Gärtner’s work spans decentralized production control , Industry 4.0 testbeds , autonomous transport systems (AGVs) , and real-time ergonomic monitoring . A flagship project is the Shared Guide Dog 4.0 , an AI-equipped autonomous rollator that supports blind and visually impaired pedestrians through advanced navigation and puddle-detection algorithms. Scientific Awards Hamburger Lehrpreis 2022 – Excellence in Teaching Projects & Funding SafeWalker – safe navigation assistance for elderly pedestrians Shared Guide Dog 4.0 – AI-driven mobility aid (with DAAD & BMAS support) GehwegNavi – sidewalk navigation for the visually impaired Decentralized Manufacturing Control testbed – “swimming-pool” model for resource negotiation Collaborative projects with Lufthansa Technik Logistik Services, VTG AG, DESY, and Krüss GmbH Teaching & Supervision He teaches bachelor and master modules such as Industrial Logistics , Production Planning & Control , Operations Management , and Project Management & Communication . Prof. Gärtner has supervised more than 30 bachelor and master theses on topics ranging from decentralized AGV control to AI-based computer-vision apps for barrier-free mobility. Labs & Teams Prof. Gärtner leads activities within the Institute for Product and Production Management (IPP) at HAW Hamburg and coordinates interdisciplinary student teams working on robotics, lean production, and service engineering.
Prof. Dr. Rinie Akkermans is Professor of Aerodynamics and Flight Mechanics at Hamburg University of Applied Sciences (HAW Hamburg), affiliated with the Department of Automotive and Aeronautical Engineering. He holds leadership roles as Vice-Director of the Research and Technology Transfer Center 'Future Air Mobility' and serves on the university Senate. His academic background includes a PhD in Physics from TU Eindhoven and an MSc in Aerospace Engineering from TU Delft. Research expertise spans computational and experimental fluid dynamics with emphasis on: Aeroacoustics and noise reduction techniques Turbulent flow modeling using DNS/LES methods Aerodynamic optimization of wings, propellers, and high-lift systems Bio-inspired flow control and vortex dynamics He actively supervises PhD candidates from TU Braunschweig, Volkswagen AG, and Beihang University. Recent publications focus on advancing computational methods (Lattice Boltzmann, Overset-LES) and experimental validations in aeroacoustics, flow control, and propeller/wing optimization. Work frequently appears in leading aerospace journals including AIAA Journal and Aerospace Science and Technology . Professional service includes doctoral committee memberships and industry collaborations with Volkswagen AG on automotive aeroacoustics. No awards are documented in the provided text.
Emmanuel Vander Poorten is an Associate Professor at the Faculty of Engineering Technology , KU Leuven, specializing in Surgical Robotics , Medical Device Design , and Biomedical Engineering . He leads the Robotics, Automation and Mechatronics (RAM) unit and is involved in interdisciplinary research through institutes like the Leuven Centre for Affordable Health Technology and iSi Health . Research Focus : Surgical Robotics, Haptics, Teleoperation, and Virtual Reality Training Key Projects : MIRACLE, RIVUS, AR-Spine, and ARTISTE (Autonomous Robotic Suturing for fetal surgery) Technical Expertise : 3D Ultrasound Shape Completion, Endovascular Navigation, and Reinforcement Learning for Surgical Planning His recent publications highlight advancements in 3D augmented reality for image-guided surgery , deep reinforcement learning for pedicle screw placement , and novel sensing methods for bone drilling . He collaborates extensively on medical robotics and autonomous catheter navigation in deformable environments.
Jaap Kamps is a Professor at the University of Amsterdam, Netherlands , with a focus on information retrieval , natural language processing , and machine learning . His work spans theoretical and applied research, including contributions to neural ranking models domain adaptation scientific text simplification exploratory search digital libraries for enhanced user access. Recent research highlights include revisiting bag-of-words representations for transformers, context embeddings for retrieval-augmented generation, and positional bias analysis in generative systems. He actively contributes to the CLEF SimpleText Track , promoting simplified scientific communication for diverse audiences. His collaborations involve co-authors like David Rau , Mostafa Dehghani , and Hosein Azarbonyad , with publications in venues such as ACM Transactions on Information Systems and ECIR . He mentors students and participates in conferences like ICTIR and SIGIR , driving advancements in efficient text ranking and user-centric search.
Regina Stodden is a Research Fellow at the Department of Computational Linguistics, Heinrich Heine University Düsseldorf, since January 2019. She is affiliated with the NRW Research College for Online Participation (second funding phase) and works under the supervision of Prof. Dr. Marc Ziegele. Education: B.A. in Educational Science, Text Technology, and Computational Linguistics from Bielefeld University M.A. in Information Science and Language Technology from HHU Düsseldorf Her research focuses on automatic text processing , particularly text simplification for online discussions. This includes: Enabling participation for people with limited German proficiency Reducing manual workload in text analysis Exploring accessibility in Open Data portals She has contributed to tools like TS-ANNO for corpus annotation and EASSE-DE for simplification evaluation, with recent work extending to CEFR-based language proficiency assessment . Her research intersects Natural Language Processing , Machine Learning , and Usability Studies , often addressing accessibility challenges in digital participation. Scientific awards: No explicit awards mentioned. Advising and grants: Participates in the NRW Research College for Online Participation funding program and collaborates under Prof. Dr. Laura Kallmeyer's supervision. Her work involves grants related to text simplification for online participation processes.
Oliver Dürr is a professor of data science at the University of Applied Sciences Konstanz (HTWG) , affiliated with the Institute for Optical Systems (IOS) . He co-directs the newly established Thurgau Institute for Digital Transformation (TIDIT) and has over twenty years of experience in computational physics, data science, and mathematical modeling. His research focuses on deep learning and statistics , exploring their synergies for data analysis. He actively disseminates his work through academic profiles on Google Scholar , ORCID , and GitHub . Contact details: Alfred-Wachtel-Str. 8, 78462 Konstanz, Germany . Email addresses: oliver.duerr@htwg-konstanz.de and oliver.duerr@zhaw.ch .
Dr. Sven Lautenbach is a Professor and Chief Scientist at the Institute of Geoinformatics, University of Heidelberg , affiliated with the HeiGIT research group. His work bridges geospatial analysis, environmental modeling, and public health, with a focus on urban systems and land-use decision-making. Current role: Chief Scientist at HeiGIT gGmbH Key affiliations: Department of Geoinformatics, University of Heidelberg Research Interests : Lautenbach's interdisciplinary research addresses: Trade-offs in land use decisions and ecosystem services Health geography and spatial epidemiology Application of machine learning and AI to urban geospatial data Open data quality assessment (OpenStreetMap, social media) Climate adaptation strategies for urban environments Vector-borne disease risk modeling Publication Trends : Recent work emphasizes: Geo-social media for pandemic early warning systems Deep learning for infrastructure mapping (e.g., road surfaces) Flood impact analysis on urban accessibility Heat stress mitigation in pedestrian routing Multi-modal urban human dynamics during crises Open data quality evaluation for humanitarian applications Project Leadership : Lautenbach directs initiatives including: myGreen: Urban green space analysis Climate Change and Spatial Epidemiology Summer School OPERAs/FP-7: Ecosystem science-policy integration CONNECT: Biodiversity-ecosystem service synergies
