Find Academic Supervisors

Sanjiban ChoudhuryView profile

Assistant Professor

• Artificial Intelligence
• Robotics
• Reinforcement Learning
• +5 more

Sanjiban Choudhury is an Assistant Professor at Cornell University's Ann S. Bowers College of Computing and Information Science and a Machine Learning Researcher at Aurora. He leads the PoRTaL group, focusing on interactive AI agents that self-align through few-shot human interactions. His research emphasizes reinforcement learning (RLHF), imitation learning (IRL), and foundation models for robotics, planning, and code generation. Key achievements include receiving the 2025 ONR Young Investigator Award for multistep robot task learning, the OpenAI Superalignment Award (2024), and a Google Research Award for LLM-based planning. His group develops modular robotics foundation models (MOSAIC), earning best paper awards at ICRA 2024 workshops. Research projects aim to bridge AI language models with robotic execution, enabling robots to interpret manuals/videos and perform complex tasks like engine repairs in hazardous environments. Lab members include doctoral students Gonzalo Gonzalez, Yuki Wang, Kushal Kedia, and master’s student Prithwish Dan. Ongoing work focuses on task super-alignment, human-robot transfer learning, and open-source training models for the robotics community. Current funding supports developing robots capable of fluid, multi-step tasks through integrated AI systems.

• Higher Education
• Educational Equity
• Sociology of Education
• +4 more

Nina Haltia serves as a University Research Fellow within the Department of Education at the University of Turku, Finland. Her institutional affiliation centers on analyzing Finnish higher education systems with a focus on equity, accessibility, and social dynamics. Her research interests prioritize educational equity through critical examination of open university tuition fees, transitions of non-traditional students into higher education, and labor market integration challenges for working-class graduates. She employs qualitative methodologies including small story analysis and narrative approaches to investigate graduate identity formation, institutional hierarchies, and social class impacts within Finnish academia. Analysis of her 2023-2025 publications reveals consistent thematic focus on systemic barriers in Finnish higher education. Key trends include empirical studies on how tuition fees affect perceptions of equal access, longitudinal tracking of working-class graduates' employment uncertainties, and deconstruction of graduate identity negotiation in competitive job markets. Her work consistently links micro-level student experiences to macro-level educational policy implications.

Johannes ReuterView profile

Professor

• Control Engineering
• Autonomous Systems
• Maritime Control
• +3 more

Prof. Johannes Reuter is a Professor in the Department of Control Engineering at Konstanz University of Applied Sciences and a member of the Institute for System Dynamics (ISD). He serves as Vice Dean and Dean of Studies for the Electrical Systems M.Eng. program. His expertise includes control engineering, tracking, and multi-sensor data fusion. Reuter holds a doctorate in Automatic Control and System Dynamics from Berlin Technical University. Before joining Konstanz in 2007, he worked at IAV GmbH, IAV Automotive Engineering (USA), and Eaton Corp.'s Innovation Center (USA). His research focuses on autonomous systems, maritime control, and optimization algorithms, with contributions to conferences like ICRA and journals such as the Journal of Ocean Engineering. He leads projects on energy-efficient autonomous vessels (Solgenia) and advanced control strategies for dynamic systems. Education: Studied Mathematics/Physics at Bielefeld University Electrical Engineering degrees from Bielefeld University of Applied Sciences and Berlin Technical University Doctorate in Automatic Control and System Dynamics, Berlin Technical University Research Interests: Reuter’s work bridges theoretical control engineering with practical applications, emphasizing autonomous systems, maritime robotics, and sensor data fusion. Key areas include model predictive control (MPC), trajectory optimization, and energy-efficient vessel design. His research often integrates advanced algorithms like MPPI (Model Predictive Path Integral) for stochastic systems and develops methods for extended object tracking using LiDAR and radar sensors. Publications: Recent work highlights energy-optimal vessel docking, trajectory planning with signal temporal logic, and extended object tracking. His articles reflect a focus on interdisciplinary solutions combining control theory, robotics, and sensor technology. Awards/Grants: No specific awards listed, but his work is supported through academic and industrial collaborations. Labs/Teams: Active in the Institute for System Dynamics (ISD), Konstanz, which focuses on control systems, signal processing, and dynamic optimization across robotics, marine systems, and energy management.

• Unmanned Aircraft Systems (UAS)
• Autonomous Systems
• Control System Design
• +7 more

Tim McLain is a Professor in the Department of Mechanical Engineering at Brigham Young University (BYU), College of Engineering. He has been a core faculty member since 1995, advancing from Assistant to Associate and full Professor by 2007. He served as Department Chair from 2007 to 2013 and continues to lead research in unmanned aircraft systems and control theory. Research Interests: His work centers on the dynamics, guidance, control, and autonomy of unmanned aircraft systems (UAS). Key areas include cooperative control, vision-based navigation, state estimation, and precision landing for UAVs. His research integrates control theory with practical implementation in aerial robotics. The recent publications reflect a strong trend in autonomous UAV operations, particularly in GPS-denied environments, vision-based navigation, and cooperative mission planning. His work spans theoretical control design, real-time estimation, and experimental validation on small aerial platforms. He has also contributed to MEMS sensor integration and modeling. Scientific Awards: No specific awards are listed in the provided text. Advising and Grants: Dr. McLain has advised over 25 graduate students, primarily on UAV-related thesis topics. His research has likely been supported by grants from agencies such as AFRL and NSF, inferred from collaborations and research topics, though specific grants are not listed. Labs and Teams: He is affiliated with UAV research teams at BYU, collaborating closely with R. Beard and others on autonomous flight projects, including formation control, search missions, and cooperative surveillance.

Vicent Girbés JuanView profile

Associate Professor

• Robotics
• Human-Robot Interaction
• Intelligent Vehicles
• +12 more

Vicent Girbés Juan is an Associate Professor in the Department of Electronic Engineering at the School of Engineering, Universitat de València. His research is centered in the HRI Human-Robot Interaction Group, where he contributes to advanced robotics, intelligent vehicles, and human-centered automation systems. He earned his PhD from Universitat Politècnica de València in 2016 with a thesis on clothoid-based planning and control in autonomous and manual-assisted driving systems, supervised by Dr. Josep Tornero Montserrat and Dr. Leopoldo Armesto Ángel. His research interests span robotics, control systems, path planning for UAVs, visible light communication, haptic feedback in teleoperation, and educational innovation in engineering. He has published extensively on smooth trajectory generation, dual-arm robot control, sensor fusion, and V2V communications. His recent work shows a growing emphasis on integrating pedagogical innovation with engineering education, including flipped evaluation, peer assessment, and hackathon-based programming learning. His publications from 2021 to 2024 reveal a dual focus: advancing industrial robotics and intelligent transportation systems, while simultaneously innovating in teaching methodologies and student engagement in higher education. Key technical areas include clothoid-based 3D path planning, cautious Bayesian optimization, VLC positioning, and haptic-assisted teleoperation. He actively collaborates on interdisciplinary projects involving human-robot cooperation, industrial automation, and educational technology, reflecting a commitment to both technological advancement and pedagogical excellence. His email is vicent.girbes@uv.es .

Huijuan WangView profile

Associate Professor

• Temporal Network Analysis
• Higher-Order Network Modeling
• Information Diffusion
• +3 more

Huijuan Wang serves as Associate Professor in the Multimedia Computing Group within the Department of Intelligent Systems at Delft University of Technology's Faculty of Electrical Engineering, Mathematics and Computer Science. With over 20 years of affiliation at TU Delft, she completed both her Master's degree and PhD at this institution before rising to her current faculty position. Her research focuses on temporal network analysis, higher-order network modeling, and information diffusion dynamics. Professor Wang investigates epidemic spreading models, network prediction algorithms, and complex system behaviors through both theoretical frameworks and practical applications. Her work bridges computer science, mathematics, and real-world network phenomena including urban systems and social dynamics. Analysis of her recent publications reveals a strong emphasis on temporal network properties, higher-order dependencies, and predictive modeling. Her research demonstrates consistent innovation in extracting diffusion backbones, measuring network dissimilarity, and developing memory-based prediction techniques for evolving networks. Co-founded Dutch Network Science Society (2018) Established Young Talent Prize recognizing emerging researchers Developed free community events fostering industry-academia collaboration Professor Wang actively mentors PhD candidates, emphasizing genuine interest in students' development as she experienced during her own doctoral studies. She champions initiatives promoting social safety, trust-building, and work-life balance within academic environments while leading efforts to establish processes addressing social safety concerns through cultural transformation.

• Volcanology
• Geophysics
• Remote Sensing
• +7 more

G. Wadge is a prominent researcher affiliated with the Environmental Systems Science Centre at the University of Reading, UK. His work focuses on volcanology, geophysics, and remote sensing, particularly in monitoring volcanic activity using advanced radar technologies such as AVTIS. He has led and contributed to numerous studies on the Soufrière Hills Volcano in Montserrat, analyzing lava dome growth, mass wasting, and pyroclastic flow hazards. Institution: University of Reading Department: Environmental Systems Science Centre Research Focus: Volcanic Processes, Remote Sensing, Geophysical Monitoring His research interests include volcanology, geophysics, remote sensing, lava dome dynamics, radar imaging, and environmental monitoring . He has extensively studied the behavior of andesitic lava domes, particularly at Soufrière Hills, using ground-based radar and seismic data to quantify extrusion rates, talus formation, and pyroclastic flow volumes. His work bridges field observations with technical instrumentation development. The recent articles highlight a consistent focus on lava dome evolution, volcanic hazard assessment, and the use of millimeter-wave radar for all-weather volcano monitoring . These studies often combine topographic imaging with seismicity data to model mass redistribution during eruptions. The interdisciplinary nature of his work spans geophysics, instrumentation, and natural hazard mitigation. While no specific scientific awards are mentioned in the provided text, his sustained publication record in high-impact journals such as Journal of Geophysical Research and Geophysical Research Letters reflects significant scholarly contribution. Wadge has collaborated with institutions including the British Geological Survey, Lancaster University, and the Montserrat Volcano Observatory. His research is supported by NERC grants, indicating active funding and project leadership. He has advised or collaborated with multiple researchers and students, though specific names are not listed. His work includes both theoretical modeling and field deployment of novel sensors. He leads research on volcanic monitoring systems and hazard evaluation, particularly through the development and application of AVTIS. This instrument enables continuous topographic and thermal monitoring of volcanoes, even under cloudy conditions, making it invaluable for real-time hazard assessment.

Jeffrey YackleyView profile

Assistant Professor

• Software Engineering
• Software Testing
• Refactoring
• +12 more

Jeffrey Yackley is an Assistant Professor of Computer Science in the Department of Computer Science, Engineering, and Physics at the College of Innovation and Technology, University of Michigan-Flint. He holds a Ph.D. in Computer & Information Science from the University of Michigan-Dearborn (2022), where he also earned his M.S. and B.S. in the same field, along with a B.Sc. in Biochemistry from the University of Michigan (2009). Ph.D. in Computer & Information Science, University of Michigan-Dearborn (2022) M.S. in Computer & Information Science, University of Michigan-Dearborn (2019) B.Sc. in Computer & Information Science, University of Michigan-Dearborn (2016) B.Sc. in Biochemistry, University of Michigan (2009) Dr. Yackley's research spans software engineering, software testing, refactoring, AI in education, cybersecurity, gamification, and educational technology. His work emphasizes both empirical software engineering and innovative pedagogical approaches, particularly active learning and gamification in computing education. He investigates refactoring practices, software quality, and trustworthiness in open-source software supply chains, while also exploring the impact of AI, VR, and digital platforms on learning outcomes. His recent publications in IEEE Access, IEEE FIE, ASEE, and Springer reflect a strong trend toward interdisciplinary research at the intersection of software engineering and education. He frequently publishes on AI-assisted learning, student engagement, and the ethical use of generative AI in computing education. His technical work includes refactoring detection, software testing, and cybersecurity tools, often developed through student-led projects. Golden Apple Award (2024, University of Michigan-Flint) Dara Knot Award (2024, UM-Flint Honors Program) MWIN Fellowship (2023, UM-Flint) Dr. Yackley actively mentors undergraduate and graduate students, advising numerous research projects and capstone teams. He has secured significant external funding, including an NSF REU site on digital accessibility and a Google Research Scholar award on software testing in open-source supply chains. His grants total over $2.5 million, supporting student research, innovation, and entrepreneurship. He leads the 'SSTEM: BlueShirting' project and contributes to initiatives on lean business models and secure authentication systems. He advises student teams on projects such as the TCP Cybersecurity Game, Automated Security Scanner, and Critical Path Tool, fostering hands-on learning and real-world problem solving. His lab environment emphasizes collaborative, student-centered research with practical impact.

• Marketing
• Consumer Behavior
• Brand Strategy
• +3 more

Dr. Bernadette van Ewijk is an Associate Professor at the University of Amsterdam within the Faculty of Economics and Business and its Section Marketing . Her research focuses on consumer behavior, brand strategy, and digital marketing dynamics. Specializes in SKU management and consumer uncertainty Expertise in pricing strategies for packaged goods Investigates digital advertising effectiveness and consumer decision journeys Recent work examines online grocery trends in China and consumer purchase patterns in emerging markets, with an emphasis on integrating behavioral tracking and attitude surveys. Contact: b.j.vanewijk@uva.nl | Phone: +31 (0)20 525 6002

Peter BunemanView profile

Professor

• Database Systems
• Data Provenance
• Semistructured Data
• +9 more

Peter Buneman is a Professor in the School of Informatics at the University of Edinburgh, affiliated with the Laboratory for Foundations of Computer Science (LFCS). He is a leading researcher in database systems, with a focus on data provenance, semistructured data, XML, and digital curation. He has been instrumental in advancing the theoretical foundations of database query languages and data integration. His research interests include database theory, data modeling, type systems, and the management of scientific data. He has made significant contributions to the understanding of data provenance, XML constraints, and the archiving of scientific datasets. His work bridges theoretical computer science with practical applications in bioinformatics and digital libraries. The recent publications highlight a consistent focus on data provenance, XML query processing, integrity constraints, and database archiving. His work spans both theoretical investigations and practical system design, often addressing challenges in data integration, curation, and long-term preservation. Peter Buneman has been actively involved in academic service, including editing proceedings for major conferences such as PODS and ICDT, and contributing to journals like the Journal of Digital Libraries. His leadership in the database community is evident through his editorial roles and collaborations. He advises and collaborates with researchers in database systems and related fields. His work has been supported by significant research initiatives, including involvement with the Digital Curation Centre, which underscores his commitment to sustainable data management practices. He is a key member of the Database Group at LFCS and has contributed to shaping research directions in data management. His past affiliation with the University of Pennsylvania’s Department of Computer and Information Science further reflects his long-standing impact on the field.

Rodrigo I. SilveiraView profile

Associate Professor

• Computational Geometry
• Combinatorial Geometry
• Geographic Information Science (GIS)
• +7 more

Rodrigo I. Silveira is an Associate Professor in the Department of Mathematics at Universitat Politècnica de Catalunya (UPC), where he conducts research in computational and combinatorial geometry. He is a member of the UPC research group on Discrete, Combinatorial and Computational Geometry and has a strong academic background, having earned his PhD at Utrecht University under Marc van Kreveld and completed prior studies at the Universidad de Buenos Aires. His research focuses on Computational Geometry , particularly problems arising from Geographic Information Science (GIS) , such as map construction, trajectory analysis, and visibility. He also works on Graph Drawing and algorithms for geometric structures. His work combines theoretical algorithm design with practical applications in spatial data. His recent publications reflect a consistent trend in geometric algorithms, including shortest paths in complex environments (e.g., portalgons), Voronoi diagrams with color constraints, robot motion coordination, and map inference from GPS data. These works appear in top-tier journals and conferences such as Algorithmica , Computational Geometry: Theory and Applications , SoCG, WADS, and LATIN. He has received scientific recognition, including a Best Paper Award at AGILE 2009 and another at SpatialGems 2021. He has supervised several PhD students to completion, including Guilermo Esteban (2024) and Pilar Cano (2020), and continues to advise current students. Rodrigo has been deeply involved in the academic community, organizing major events such as the European Workshop on Computational Geometry (EuroCG 2023), Graph Drawing 2018, and the Intensive Research Program on Discrete Geometry (2018). He has served on the program committees of SoCG, WADS, LATIN, and CCCG, and has chaired tracks for EGC and CG:YRF. His work is supported by collaborations with leading researchers such as Kevin Buchin, Maarten Löffler, Prosenjit Bose, and Vera Sacristán, and he contributes to both theoretical advances and practical implementations in geometric computing.

Camil DemetrescuView profile

Professor

• Performance profiling
• Programming languages
• Algorithmics
• +3 more

Camil Demetrescu is a Professor of Computer Science at Sapienza University of Rome, with a Ph.D. in Computer Engineering from the same institution (2001). His research spans performance profiling, programming language design, algorithmics, and computer security, focusing on software reliability and optimization. Education: Ph.D. in Computer Engineering from Sapienza University of Rome (2001) Research Interests include performance analysis of software systems, graph algorithm implementation, incremental computing, symbolic execution, and computer security. As a glider aircraft pilot, he combines technical rigor with a passion for aviation. Recent Publications (2011-2022) address concolic execution, path profiling, runtime code replacement, and symbolic fuzzer development. Key themes: software diagnostics, program analysis, and security engineering. Conference Contributions : Active in PLDI, ICSE, ASE, and SPLASH series as author and committee member since 2011.

Maximilian PfostView profile

Associate Professor

• Educational Psychology
• Reading Development
• Self-Regulated Learning
• +3 more

Maximilian Pfost is an Associate Professor at the University of Bamberg's Department of Educational Research, Faculty of Human Sciences and Education. His work focuses on self-regulated learning, reading comprehension, and literacy development across educational stages. Education: Habilitation (2016), PhD in Psychology (2011), Diploma in Psychology (2008) Professional Positions: Associate Professor (since 2017), Assistant Professor (2011-2017), Research Scientist (2008-2011) His research examines: Self-regulated learning mechanisms in higher education Impact of digital media on emergent literacy Interrelations between reading motivation and comprehension Longitudinal studies on academic self-concept development Recent publications highlight his focus on academic risk-taking, error-based learning strategies, and digital tools for self-regulated learning. He employs interdisciplinary methodologies spanning educational psychology, literacy studies, and behavioral research. Scientific recognition includes: Habilitation Award, University of Bamberg (2016) Friedrich-Ebert-Foundation Scholarship (2003–2007) Collaborations include projects with Prof. Dr. Cordula Artelt and international engagements in Rwanda. His work appears in journals like Learning and Instruction , Frontiers in Education , and Reading and Writing .

Sherine AntounView profile

Assistant Professor

• Robotics
• Autonomous Navigation
• Biologically Inspired Perception
• +2 more

Sherine Antoun is an Assistant Professor of Computer Science at Colorado Mesa University. He is based in Confluence Hall 335 and can be reached at 970.248.1148 or santoun@coloradomesa.edu. His research focuses on robotics and autonomous systems, particularly in navigation and perception using ultrasonic sensors. Dr. Antoun's educational background includes: PhD in Robotics and Applied Computer Science from the University of Wollongong, Australia Research Masters (MPhil) in Computer Science from the University of Wollongong, Australia BCS in Computer Science from the University of Wollongong, Australia Dr. Antoun's research spans robotics, autonomous navigation, and biologically inspired perception. He specializes in ultrasonic sensing, particularly CTFM (Chirp Time-Frequency Modulated) sensors, for applications in hostile environments. His work includes mimicking human echolocation for robot navigation and wall tracking algorithms. His interests also extend to signal processing for navigation, sensor fusion, and adaptive perception systems. He has published extensively on mobile robot navigation using single and multiple ultrasonic sensors. Dr. Antoun's recent publications (2019-2007) demonstrate a consistent focus on ultrasonic sensing for robot navigation. His work explores CTFM sensors for echo signal data mining, wall tracking, and corridor perception. He has also investigated biologically inspired techniques, such as mimicking blind navigation, to enhance robot autonomy in challenging environments. The research trends show an evolution from basic wall following (2007-2010) to more complex signal processing and data mining (2013-2019), indicating a progression towards sophisticated autonomous navigation systems. Dr. Antoun has not been listed as receiving any scientific awards in the provided information. Dr. Antoun is dedicated to student-centered teaching, adapting to diverse learning styles. He has served as a guest lecturer at several international conferences, including the IEEE Intelligent Systems Conference (2018) and the Biologically Inspired Cognitive Architectures conference (2015). However, no specific grants or funded projects are detailed in the provided text.

Maria LiakataView profile

Professor

• Natural Language Processing
• Semantics and Discourse
• Social Media Analysis
• +7 more

Maria Liakata is a Professor of Natural Language Processing at Queen Mary University of London, where she serves as Deputy Centre Lead and 'Health and Wellbeing' Theme Lead for the Centre for Human-Centred Computing within the School of Electronic Engineering and Computer Science. She leads multiple research initiatives focusing on applying NLP techniques to healthcare applications, particularly mental health monitoring through social media and longitudinal user-generated content analysis. Her research interests span Natural Language Processing, Semantics and Discourse, Social Media analysis, Machine Learning, BioNLP, and NLP for Mental Health. Dr. Liakata has made significant contributions to knowledge discovery from corpora, automation of scientific experimentation, and automatic extraction of information from scientific literature. Her work has practical applications in mental health monitoring, dementia diagnosis, and rumor verification systems. Her recent publications demonstrate a strong focus on longitudinal analysis of language for mental health applications, temporal modeling of user-generated content, and healthcare AI. She has developed novel techniques for detecting changes in user representations over time, which have applications in mental health monitoring and early dementia diagnosis. Her research bridges the gap between technical NLP advancements and real-world healthcare challenges. EPSRC/UKRI Turing AI fellowship award on Creating Time Sensitive Sensors from Language & Heterogeneous User-Generated Content (2019-2025) IBM Faculty Award for work on emotion sensing from heterogeneous mobile phone data EU Project PHEME co-investigator (2014-2017) studying the spread of rumours in social media Early Career Fellowship from the Leverhulme Trust (2010-2013) on reasoning with scientific articles Dr. Liakata supervises a diverse group of PhD students working on cutting-edge NLP applications for healthcare, including mental health monitoring, dementia diagnosis, and medical imaging analysis. She leads multiple substantial research grants totaling millions of pounds from EPSRC, MRC, Wellcome Trust, and industry partners. Her current projects include 'Addressing socio-technical limitations of LLMs for medical and social computing' and 'Social media, Smartphone use and Self harm in Young People (3S-YP study)'. She leads the 'Health and Wellbeing' research theme within the Centre for Human-Centred Computing and collaborates closely with the Centre for Multimodal AI. Her interdisciplinary research team combines expertise in NLP, machine learning, clinical psychology, and healthcare informatics to develop practical AI solutions for real-world health challenges.