Find Academic Supervisors

Arnold SchumannView profile

Professor

• Precision Agriculture
• Artificial Intelligence in Agriculture
• Crop Nutrition
• +4 more

Dr. Arnold Schumann is a Professor in the Department of Soil, Water, and Ecosystem Sciences at the University of Florida's Citrus Research and Education Center. His research emphasizes precision agriculture, AI applications in farming, and sustainable citrus production. Key focuses include soil spatial variability, irrigation optimization, nutrient management, and automated crop monitoring technologies. He leads projects developing variable-rate technologies (VRT) to enhance fertilizer efficiency and groundwater protection. Schumann's research spans precision irrigation, soil sensing, AI-driven pest/disease detection, and citrus under protective screen (CUPS) systems. His work integrates machine vision, deep learning, and sensor technologies to address challenges in crop nutrition, weed control, and yield prediction. Recent studies explore convolutional neural networks for real-time plant identification and soil health characterization. Schumann advises graduate students including Laura Cano Castro (Masters) and Perseveranca Mungofa (Ph.D.). His lab employs a Biological Scientist III, Laura Waldo, supporting field and computational research. The team collaborates extensively on grants addressing HLB (citrus greening) mitigation, sustainable water use, and agrochemical efficiency, though specific grants are not detailed in the source text.

Chengyuan XuView profile

Professor

• Crop Physiology
• Carbon Farming
• Precision Agriculture
• +4 more

Professor Chengyuan (Stephen) Xu is a faculty member in the Faculty of Science and Technology at [University Name], affiliated with the Research Institute for Environment and Livelihoods. His research focuses on enhancing tropical cropping systems' sustainability through crop physiology, carbon farming, precision agriculture, and circular economy approaches. He holds a PhD in Plant Ecophysiology from Columbia University (2006) and a Bachelor's from Fudan University (2001). Key research areas include crop responses to climate variability, biochar applications for soil health, and agri-tech integration. He collaborates with industries like dragon fruit, mushroom, and AgTech sectors, emphasizing interdisciplinary solutions. Current projects address cotton resilience in Northern Territory, mushroom circular economy development, and bilateral Australia-China academic partnerships. Education: PhD in Plant Ecophysiology (Columbia University, 2006), Bachelor's (Fudan University, 2001) Industry Partnerships: Dragon fruit, camellia oil, AgTech sectors SDG Contributions: Zero Hunger, Climate Action, Responsible Consumption Recent research outputs include studies on dragon fruit volatile compounds, UAV-based weed management, and fertilizer consumption trends in Australia. Projects emphasize translating research into practical applications for rural economic diversification and climate resilience.

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +17 more

Prof. Dr. Antonio Krüger is the CEO of the German Research Center for Artificial Intelligence (DFKI) and Director of the Ubiquitous Media Technology Lab (UMTL) at the Saarland Informatics Campus in Saarbrücken, Germany. He is a leading researcher in human-computer interaction, virtual and augmented reality, multimodal interfaces, and intelligent systems. His research interests span a broad range of topics including virtual reality (VR), augmented reality (AR), gesture interaction, haptic feedback, EEG and eye tracking, gamification, cognitive load estimation, brain-computer interfaces, and smart environments. His work emphasizes user-centered design, perceptual illusions, and real-world applications in domains such as automotive, healthcare, and education. His recent publications (2023–2024) demonstrate a strong focus on advancing VR interaction through techniques like hand redirection, synthetic gesture generation for vehicles, implicit intent recognition using multimodal sensing, and personalized object referencing. These works reflect trends toward seamless, natural, and adaptive interfaces that leverage AI, perception, and real-time feedback. Prof. Krüger supervises a large team of researchers and students, including Mansi Sharma, Amr Gomaa, André Zenner, and Martin Feick, indicating active mentorship and collaborative research leadership. His lab, UMTL, develops innovative technologies in immersive environments, wearable systems, and intelligent user assistance, contributing to both academic knowledge and practical applications.

Ole BallingView profile

Professor

• Multibody Dynamics
• Wind Turbine Engineering
• Operational Modal Analysis
• +4 more

Ole Balling is a Professor at the Department of Mechanical and Production Engineering, Aarhus University, Denmark, specializing in multibody dynamics and vibration analysis. His work bridges theoretical mechanics with practical applications in renewable energy and agricultural systems, leveraging advanced computational modeling for industrial-scale engineering challenges. His primary research interests include Multibody Dynamics for structural simulation, Operational Modal Analysis in rotating machinery, Wind Turbine Engineering (focusing on gearboxes and blades), and Soil-Vehicle Interaction for agricultural/military applications. He also develops Digital Twin frameworks for agricultural vehicles and investigates Vibration Control in robotic systems, with strong emphasis on experimental validation and energy-efficient design. Recent publications (2020-2023) reveal concentrated expertise in offshore wind turbine reliability (gear microgeometry, tower vibrations), soil mechanics modeling (aggregate fracture, drawbar pull testing), and autonomous vehicle mobility frameworks. A recurring theme is the application of operational modal analysis to diverse systems—from parallel manipulators to wind turbine hubs—demonstrating cross-domain adaptability of his core methodologies in dynamics and control. Scientific Awards: No awards documented in source materials. Grants and project leadership highlight sustained NATO collaboration, including the ongoing Next Generation NATO Reference Mobility Model (NG-NRMM) (extending to August 2025) and Mobility Assessment Methods for Autonomous Military Ground Systems . Past projects include INNOMILL (2015-2018) for large-component machining, BioXtek (2014-2017) for agricultural technology, and Low Bottom Soft Soil Modeling (2013-2017) for terrain damage reduction. He operates within the Mechatronics and Dynamics section of the department, utilizing laboratories for vibration testing, soil mechanics experiments, and multibody simulation. Current work focuses on autonomous military vehicle assessment and wind turbine gearbox optimization, with future projects targeting energy-efficient accelerator magnets and large-scale machining cell development.

Barry TillmanView profile

Professor

• Agronomy
• Plant Breeding
• Crop Science
• +3 more

Dr. Barry Tillman is a Professor of Agronomy at the North Florida Research and Education Center (NFREC). His research focuses on improving peanut varieties through conventional breeding and integrating genomic tools. He emphasizes sustainable agricultural practices, including water stress tolerance, herbicide efficacy, and precision agriculture technologies. His work bridges crop physiology, weed management, and technological innovation to enhance peanut production. Research interests include peanut breeding, drought resilience, and the application of hyperspectral imaging and robotics for crop monitoring. He explores transgenerational stress memory and melatonin seed priming to improve crop yield under environmental stress. Recent studies address aflatoxin risk modeling, weed control strategies, and disease management using hydrothermal time models. Dr. Tillman collaborates on developing cost-effective agricultural technologies, such as hyper-spectral cameras and robotic systems for plot-scale analysis. He has contributed to the registration of new peanut varieties like FloRun ‘T61’ and TUFRunner ‘297’, emphasizing functional food traits and disease resistance.

• Medieval History
• Crusades
• First Crusade
• +5 more

Simon Parsons is a Teaching Fellow in the Department of History at the London School of Economics and Political Science (LSE), specializing in medieval British and continental European history. His institutional affiliation is centered within LSE's School of History, where he contributes to historical research and pedagogy. His research concentrates on the First Crusade's historiography, particularly examining British Isles participation through Angevin narratives and regional perspectives across England, Scotland, and Wales. Notably, his fingerprint reveals significant work on 12th-century stylistics and Norman borderland societies. An unusual interdisciplinary dimension appears in his 2020 co-authored robotics paper, suggesting collaborative ventures beyond traditional historical scholarship. Publication trends indicate dual scholarly trajectories: rigorous medieval analysis (80% of output) focused on crusading heritage and British identity formation, alongside emergent work in human-robot interaction (20%). This juxtaposition highlights either methodological innovation in historical research or cross-disciplinary partnerships. Parsons' advising activities and grant acquisitions remain undocumented in available sources. His laboratory or research team affiliations are unspecified, though his robotics collaboration implies engagement with LSE's interdisciplinary centers or external technical institutions.

Jiajun XuView profile

Researcher

• Agricultural Engineering
• Robotics
• Machine Vision
• +4 more

Jiajun Xu is a Research Associate in the Department of Biosystems and Agricultural Engineering (BAE) at Michigan State University's College of Engineering. His work focuses on advancing agricultural automation through machine vision systems, robotics, and path planning algorithms. Key areas of expertise include automated crop sorting, weed detection systems, and the development of cable-driven parallel robots for precision agriculture. His research integrates mechanical engineering principles with cutting-edge computer vision technologies, aiming to enhance efficiency in agricultural post-harvest processes and autonomous farming operations. Notable contributions include the OpenWeedGUI platform for weed imaging and the design of LiDAR-based systems for real-time crop quality assessment. Publications highlight trends in sensor integration, path optimization for mobile robots, and cross-season weed detection adaptations. Collaborative projects emphasize practical applications in agricultural automation, with a focus on open-source tools and industry-relevant solutions. Awards and grants are not explicitly mentioned in available texts, though his work indicates strong engagement with both academic and applied research in biosystems engineering.

Nilanjan ChakrabortyView profile

Associate Professor

• Robotics
• Artificial Intelligence
• Dynamical Systems
• +5 more

Nilanjan Chakraborty is an Associate Professor in the Department of Mechanical Engineering at Stony Brook University, where he has been since 2014. His research focuses on robotics, artificial intelligence, and dynamical systems, with particular emphasis on developing robust autonomy for robots operating in collaboration with humans or independently. He directs the Interacting Robotic Systems Laboratory, exploring algorithmic foundations for multi-robot systems, manipulation planning, and human-swarm interaction. Chakraborty holds a Ph.D. from Rensselaer Polytechnic Institute (2008) and previously served as a Postdoc/Project Scientist at Carnegie Mellon University’s Robotics Institute. His work includes pioneering contributions to contact dynamics-based algorithms, multi-robot coordination, and human-robot interaction. He is an IEEE member and has reviewed for top-tier robotics conferences/journals. Research interests span: (1) Manipulation planning with environmental interactions, (2) Safe whole-body robot control using complementarity constraints, (3) Human-guided motion planning via screw geometry, (4) Swarm robotics coordination under uncertainty, and (5) Agricultural automation with cobots. Recent trends in his publications emphasize real-time obstacle avoidance, deep learning for mechanism design, and provable search methods with imperfect sensors. He has received the 2013 Best Paper Award (HFES) and 2007 Best Student Paper (RSS). His lab investigates topics like LiDAR-based tripping hazard detection, time-optimized trajectory planning, and connectivity-resilient multirobot teams. Ongoing work addresses challenges in human-swarm interfaces and adaptive grasping systems.

• Agricultural Engineering
• Soil Compaction
• Energy Efficiency in Agriculture
• +3 more

Dipl.-Ing.Dr.nat.techn. Gerhard Moitzi is a researcher at the University of Natural Resources and Life Sciences (BOKU Vienna) , specifically affiliated with the Experimental Farm Groß-Enzersdorf and the Institute of Agricultural Engineering . His work focuses on agricultural engineering , soil compaction mitigation , and energy efficiency in farming practices . With a career spanning over two decades, Moitzi has contributed to understanding soil tillage systems , field traffic-induced compaction , and carbon sequestration in agricultural soils . He has led multiple research projects funded by the European Commission , Austrian Research Promotion Agency (FFG) , and Federal Ministries , including studies on CO2 emissions and ammonia mitigation in farming contexts. His recent publications (2023-2025) highlight innovations in soil compaction analysis , drone-based crop monitoring , and sustainable nitrogen management . Moitzi employs multispectral imaging , machine learning , and life cycle assessment to evaluate agricultural impacts. He actively participates in international conferences like ALVA Jahrestagung and EGU General Assembly , emphasizing climate-resilient farming and precision agriculture .

• Wireless sensor networks
• Internet of Things (IoT)
• Air pollution monitoring
• +11 more

Renato Ferrero is an Associate Professor at the Department of Control and Computer Science (DAUIN), Politecnico di Torino (Polito) , with key roles as contact person for training activities and member of the PIC4SeR Interdepartmental Center for Service Robotics . His research spans Wireless Sensor Networks (WSN) , Internet of Things (IoT) , and Environmental Monitoring , supported by competitive grants like AGRITech Spoke 6 (2022-2025) and MIUR funding (2017). He has published extensively on topics including air pollution monitoring , quantum-inspired security , and agricultural technology , with recent work focusing on deep learning for mask/respirator detection and biofertilizer analysis . As an IEEE Access Associate Editor and program committee member for conferences like COMPSAC and RFID-TA, he contributes to academic governance. His teaching includes Computer Architecture (2019-2025) and Ubiquitous Computing (2019-2021) at Polito. He advises PhD students Chiara Panico and Nicola Dilillo , with projects in Data Science , Computer Vision , and AI Life Sciences .

• Automation and Control Systems
• Robotics in Agriculture
• Artificial Intelligence in Agriculture
• +7 more

Assoc. Prof. Ing. Vladimír Cviklovič, PhD. is a full-time Associate Professor at the Slovak University of Agriculture in Nitra, Faculty of Engineering, Institute of Electrical Engineering, Automation, Informatics and Physics. He is also identified as a faculty member of the Department of Electrical Engineering, Automation and Informatics (TF). Research Interests: His work spans automation systems, robotics, artificial intelligence in agriculture, sensor networks, and precision farming. He is particularly active in developing autonomous mobile robotic systems for crop production, integrating AI and computer vision into smart farming applications. Publications & Trends (2025): In 2025 alone, he co-authored five outputs ranging from AI-based evaporation modeling and ultrasonic cow localization to real-time plant segmentation using YOLO on smartphones. These reflect a clear trend toward AI-driven precision agriculture and sensor-based environmental monitoring. Projects & Grants: He currently leads or co-leads 23+ projects funded by VEGA, KEGA, APVV, EIT, Erasmus+, and national recovery programs. Key ongoing projects include autonomous greenhouse-gas mapping around livestock facilities, AI-based disease diagnosis in orchards, robotic tomato harvesting, and integrating Industry 4.0 technologies into engineering education. Supervision & Teaching: He has supervised more than 130 final theses (bachelor, diploma, dissertation) since 2012, with topics covering PID control, robotics, sensor design, renewable energy, and smart systems. His consultation hours are every Thursday 9:00–10:00 in office MF-B_2_Va320.

Zhihang SongView profile

Assistant Professor

• Plant Phenomics
• Controlled Environment Agriculture
• Digital Agriculture
• +5 more

Dr. Zhihang Song serves as Assistant Professor in the Department of Horticulture at the University of Georgia's College of Agricultural & Environmental Sciences, with dual affiliation at the Institute for Integrative Precision Agriculture. His work advances digital agriculture through plant phenomics and controlled environment agriculture (CEA) to enhance food security and sustainability. Education: B.S. in Agricultural Engineering, China Agricultural University (CAU), Beijing, China, 2017 B.S. in Agricultural Engineering (Machine Systems), Purdue University, West Lafayette, IN, 2017 M.S. in Agricultural & Biological Engineering, Purdue University, West Lafayette, IN, 2020 Ph.D. in Agricultural & Biological Engineering, Purdue University, West Lafayette, IN, 2024 Dr. Song's research integrates imagery sensors, machine learning, computer vision, and robotics to solve critical challenges in CEA crop production. His work spans plant phenotyping (above and below ground), nutrient deficiency detection, disease resistance screening, and root system analysis. He develops innovative robotic platforms and imaging solutions that enable precise crop monitoring and management, significantly contributing to sustainable food production systems through data-driven approaches. His publication record (2019-2025) reveals a clear research evolution from foundational hardware development (MISIRoot, LeafSpec) to advanced spatial-spectral analysis methods. The work consistently focuses on corn and soybean phenotyping using hyperspectral/multispectral imaging, with increasing sophistication in machine learning applications for nitrogen estimation, disease detection, and stress analysis. This trajectory demonstrates growing integration of AI with agricultural robotics for precision farming. Scientific Awards: Estus H. and Vashti L. Magoon Award for Excellence in Teaching Dr. Song actively mentors undergraduate, Master's, and Ph.D. students through paid research assistantships in his top-tier CEA laboratory. While specific grant details aren't provided, his research profile indicates strong funding potential in digital agriculture technologies, with appointment allocations showing 70% research commitment supporting his extensive publication output in agricultural robotics and precision phenotyping. He leads a specialized research group within the Institute for Integrative Precision Agriculture, operating advanced facilities at the 1111 Plant Sciences Building (Office: 1311 Miller Plant Sciences). The lab develops cutting-edge technologies including drone-based phenotyping systems (PhenoBee), minimally invasive root imaging robots (MISIRoot), and portable spectral imaging devices for field and controlled environment applications.

• Agricultural Safety
• Precision Agriculture
• Agricultural Technology
• +4 more

Aaron Etienne is an Assistant Professor in the Department of Applied Sciences, Technology and Education at Utah State University's S.J. & Jessie E. Quinney College of Agriculture & Natural Resources. His research focuses on integrating technology with agricultural practices to enhance safety, efficiency, and sustainability in farming operations. Located at the ASTE facility in Logan, Utah, Dr. Etienne investigates critical areas including lone worker safety systems, precision agriculture technologies, and automation solutions. Research Focus Areas: Agricultural Safety Innovation: Development of wearable devices and response systems for lone agricultural workers, incident database creation, and geospatial risk analysis. Precision Agriculture: UAV-based weed detection using deep learning, crop management systems, and sensor technology integration. Agricultural Automation: Grain handling robotics, machinery network systems (CAN-bus), and efficiency optimization technologies. His recent publications (2019-2025) demonstrate consistent focus on technology-driven solutions for agricultural challenges. Safety research dominates his recent output (7 publications), followed by automation (4) and precision agriculture (4). Key technological themes include deep learning applications, sensor systems, and geospatial analysis. Notably, 9 of 15 recent publications involve empirical validations or system developments, reflecting a strong applied research approach.

• Art
• Fine Arts
• Plastic Arts
• +1 more

Ali Doğan is a Lecturer at Çukurova University's Faculty of Education, Department of Fine Arts Education, specializing in Original Printmaking and Exlibris. He has held this position since 2000 and previously served as a Lecturer at Mustafa Kemal University from 1994 to 2000. His academic career spans over 30 years, with teaching experience in courses like Basic Art Education, Contemporary World Art, and Painting Technologies. Undergraduate: İnönü University, Faculty of Education, Art Teaching (1989-1993) Master's: Mustafa Kemal University, Institute of Social Sciences, Department of Art Education (1994-1997) Doctorate: Çukurova University, Institute of Social Sciences, Fine Arts Education (2020-Continues) His research interests focus on Art, Fine Arts, Plastic Arts, and Printing Arts, with significant artistic activity in international printmaking and exlibris exhibitions. While his publications primarily address agricultural sciences and environmental risk assessment, his academic role remains rooted in art education. Scientific awards include: Ankara Barosu Sanat Eserleri Yarışması - Özgün Baskıresim '3.ÖDÜLÜ' (2008) F.I.S.A.E. International CGD Ex-libris Competition - 'Honourable Mention' (2004) International 'Nazım Hikmet 1902-2002' Exlibris Competition - 'THIRD PRIZE' (2002) 1.Antalya Resim Festivali - 'BAŞARI ÖDÜLÜ' (2002)

Pan ZhaoView profile

Assistant Professor

• Control Theory
• Machine Learning
• Autonomous Systems
• +4 more

Dr. Pan Zhao is an Assistant Professor in the Department of Aerospace Engineering and Mechanics at the University of Alabama (UA). He directs the Autonomous Systems and Control Lab (ASCL), focusing on the integration of control theory, machine learning, and autonomy for aerospace and robotics applications. Prior to UA, he was a Postdoctoral Researcher at the University of Illinois at Urbana-Champaign. B.E., Automation, Beihang University (2009) M.E., Mechanical Engineering, Beihang University (2012) Ph.D., Mechanical Engineering, University of British Columbia (2018) Dr. Zhao’s research spans robust, adaptive, and nonlinear control theory, with applications to autonomous systems in aerospace, robotics, and sustainable agriculture. His group develops algorithms for safe and efficient operation under uncertainties, validated through real-world experiments on unmanned vehicles. Recent work includes advancements in control barrier functions, contraction metrics, and adaptive control for VTOL aircraft and quadrotors. Notable scientific awards include the NSERC Vanier Canada Graduate Scholarship (2015) and recognition as an Excellent Reviewer by the Journal of Guidance, Control, and Dynamics (2022). The ASCL lab has secured funding from UA’s ORED Small Grant Program for resilient autonomous systems research.