Find Academic Supervisors

• Robotics
• Artificial Intelligence
• Task and Motion Planning
• +4 more

Rahul Shome is a tenure-track lecturer in the School of Computing at the Australian National University (ANU), specializing in Robotics & AI. His research focuses on planning algorithms for human-centric robotics applications, with expertise in task and motion planning, multi-robot systems, and collaborative automation. He holds a Ph.D. and M.S. from Rutgers University, advised by Prof. Kostas E. Bekris, and completed postdoctoral work at Rice University under Prof. Lydia E. Kavraki. Education: Ph.D. and M.S. in Robotics, Rutgers University (advisor: Prof. Kostas E. Bekris) Postdoctoral Research Associate, Rice University (advisor: Prof. Lydia E. Kavraki) Research Interests: Development of practical robotics solutions with theoretical guarantees Integration of AI techniques for real-world automation challenges Multi-robot coordination and manipulation in dynamic environments Human-centric robotics emphasizing privacy, ethics, and collaboration His publications span journals and conferences like IEEE Robotics and Automation Letters, with awards including the Best Paper Award at IEEE MRS. Shome actively serves on editorial and organizing boards for major robotics venues. Current research directions explore algorithmic foundations in stochastic decision-making, topology, and machine learning integration. Advising & Opportunities: Open PhD and research positions in robotics planning and collaborative automation Focus areas: AI-driven robotics, human-robot interaction, and perception systems

Catherine GorleView profile

Associate Professor

• Computational Fluid Dynamics
• Wind Engineering
• Urban Flow Simulations
• +2 more

Catherine Gorle is an Associate Professor of Civil and Environmental Engineering (with courtesy appointment in Mechanical Engineering) at Stanford University. She holds BSc and MSc degrees from Delft University of Technology and a PhD from the von Karman Institute. Her research develops predictive flow simulations for sustainable building and urban design. Research integrates computational fluid dynamics with uncertainty quantification methods to model urban wind environments, wind loads on structures, and natural ventilation patterns. Recent work focuses on multi-fidelity modeling, sensor network design, and machine learning applications for urban flow prediction. Publications demonstrate consistent innovation in wind engineering methodologies, including novel approaches for inflow generation, wind farm optimization, and urban canopy modeling. A significant research stream examines wind-wave interactions and their structural impacts. She directs research on contrail formation from aviation and develops frameworks for high-fidelity simulation of environmental flows.

The DuongView profile

Research Fellow

• Perovskite Solar Cells
• Perovskite-Silicon Tandem Solar Cells
• Solar to Hydrogen Production
• +3 more

Dr The Duong serves as a Research Fellow at the School of Engineering, Australian National University (ANU), pioneering advanced photovoltaic technologies with emphasis on high-efficiency solar energy conversion systems. His research bridges fundamental materials science and practical renewable energy applications through innovative device engineering. Education: Bachelor of Science in Electrical Engineering (highest distinction) from Oregon, United States Ph.D. from Australian National University with record 26.4% efficiency achievement for perovskite-silicon tandem solar cells Dr Duong's research program spans four interconnected domains: perovskite solar cell optimization, perovskite-silicon tandem systems, solar-to-hydrogen conversion, and semiconductor gas sensors. His work integrates interface engineering, defect passivation, and novel material synthesis to overcome stability and efficiency barriers in next-generation photovoltaics. Recent breakthroughs include radiation-tolerant solar cells for space applications and fluorinated polymer additives enhancing device longevity, demonstrating exceptional versatility across terrestrial and extraterrestrial energy contexts. Analysis of his 2023-2024 publications reveals a strategic focus on stability enhancement through molecular engineering (e.g., 4-methylphenethylammonium chloride additives) and interface modification (chemical crosslinking, bottom passivation). The research spans fundamental charge transport mechanisms to applied space photovoltaics, with strong industry relevance evidenced by 5537 total citations and consistent high-impact journal placements. Scientific Awards: ACT Minister for Climate Change and Sustainability Best Ph.D. Thesis Award (2017) Innovation for Cool Earth Forum (ICEF) Top 10 Innovation for solar-to-hydrogen generation (2020) Two competitive Australian Centre for Advanced Photovoltaics (ACAP) Postdoc Fellowships As Principal Investigator, Dr Duong secured significant funding including the 2021-2022 project 'Stable dopant-free carrier-selective contacts for silicon solar cells' and the 2020-2022 initiative 'Poly-silicon passivating contacts: structures, optoelectronic properties, and defect engineering'. His collaborative network spans 12 international institutions with 65 research outputs and a 37 h-index. Current work focuses on commercializing methylammonium-free perovskite tandems and scaling direct solar-hydrogen systems. Research operates within ANU's photovoltaics facilities through the Australian Centre for Advanced Photovoltaics (ACAP), leveraging partnerships with industry leaders like Intel (where he previously worked as Process/Equipment Engineer) and global academic consortia. Future directions include radiation-hardened space solar arrays and integrated solar-fuel production platforms.

Gerd von CöllnView profile

Professor

• Energy-Efficient Systems
• Embedded Systems
• Cyber-Physical Systems
• +5 more

Prof. Gerd von Cölln is a Professor of Computer Architecture at the School of Technology, Electrical Engineering and Computer Science, University of Applied Sciences Emden/Leer. His primary focus is on energy-efficient and autonomous systems, particularly in embedded and cyber-physical systems. He leads research in energy-autonomous sensors, low-power electronics, and IoT applications. Education details are not explicitly provided in the text, but his academic role suggests advanced qualifications in electrical engineering or computer science. His research projects include Sichere Offshore-Operationen (SOOP), Energieautarke Sensorsysteme (ID3AS), and LoRaWAN-based sensors (ELVIS), demonstrating expertise in industrial automation, sensor networks, and energy harvesting. Publications emphasize sensor design, wireless communication protocols, and optimization algorithms for complex environments. While no awards are listed, his extensive project portfolio highlights contributions to applied engineering research. Advising details are unavailable, but his role implies supervision of technical projects involving students and industry partners. Prof. von Cölln collaborates on labs and teams focused on maritime automation, industrial IoT, and embedded systems, with projects addressing challenges like harsh environmental conditions and energy sustainability.

Damian JoachimiakView profile

Professor

• Thermal Engineering
• Fluid Mechanics
• CFD Modeling
• +3 more

Dr. hab. eng. Damian Joachimiak is a Professor at the Institute of Thermal Energy, Faculty of Environmental and Energy Engineering at Poznań University of Technology. His research focuses on thermal engineering, fluid mechanics, and computational methods, particularly in labyrinth seal optimization, heat transfer analysis, and energy systems. He has supervised doctoral research, including the dissertation by Bartosz Ciupek on improving solid fuel combustion processes. Joachimiak has contributed to numerous research projects, including testing power system elements and developing energy condenser models. His work integrates experimental and numerical methods, with over 27 peer-reviewed articles and two patents. Notable patents include a sealing method for fluid-flow machines and a sieve plate design for boilers. He also leads industrial collaborations, such as optimizing labyrinth seals for Mipol sc and Filen.

• Deep learning
• Physics
• Large language models
• +2 more

Ing. Eugen Šlapak, PhD., is a researcher at the Intelligent Information Systems Laboratory (IISLAB) of the Technical University of Košice, Slovakia, where he has worked since 2017. His research focuses on machine learning applications for cellular wireless networks modeled as multi-agent systems, with emphasis on 5G/6G optimization and autonomous vehicle communications. Education: BSc in Informatics, Technical University of Košice (2016) MSc in Informatics, Technical University of Košice (2018) Dr. Šlapak's research integrates Deep Learning , Physics-based modeling , and Large Language Models to solve wireless network challenges. His work on HetNets, UAV-assisted communications, and blockchain-enabled resource allocation demonstrates expertise in applying unsupervised learning and evolutionary algorithms to coverage optimization, radio resource management, and network topology design for next-generation mobile systems. His 13 publications (2017-2023) reveal consistent focus on machine learning-driven wireless innovations, with increasing emphasis on deep learning for 5G/6G management and blockchain applications in vehicular networks. Key trends include UAV swarm coordination, HetNet spatial optimization via clustering algorithms, and multi-agent resource allocation frameworks addressing computational and radio resource constraints. Scientific Awards: No awards documented in source material Dr. Šlapak collaborates extensively with Assoc. Prof. Juraj Gazda and international researchers on EU-funded telecommunications projects. His laboratory work centers on developing self-organizing network frameworks through the Intelligent Information Systems Laboratory (IISLAB). As a core IISLAB researcher, he contributes to experimental validation of AI-driven network solutions using agent-based modeling and real-world wireless testbeds, with recent work focusing on autonomous vehicle communication stacks and UAV-based mobile network deployment.

Charissa CheView profile

Assistant Professor

• Translingual Rhetorics
• Multilingual Student Identities
• Equitable Writing Pedagogies
• +4 more

Dr. Charissa Che serves as an Assistant Professor in the English Department at John Jay College of Criminal Justice (CUNY), specializing in translingual and cultural rhetorics. She holds a PhD from the University of Utah's Writing and Rhetoric program, alongside MA and BA degrees from CUNY and Pace University. Her research focuses on equitable writing pedagogies, multilingual student identities, and Asian American experiences in higher education. Key projects include critiques of ESL labeling practices, community partnerships in writing programs, and heritage language student empowerment. She has published in Teaching English in the Two-Year College , Journal of Basic Writing , and interdisciplinary engineering journals. Recipient of PSC CUNY Research Awards (2024, 2020), CUNY Campus Climate Grant (2023), and CCCC Chair's Memorial Scholarship (2019) Leadership roles include Associate Chair of TYCA National and TETYC Book Review Editor Past Program Chair of the 2022 TYCA National Conference Dr. Che advocates for institutional policies that center linguistic diversity and cultural inclusion, while actively shaping disciplinary conversations through editorial work and conference leadership.

• Computational Nonlinear Control
• Deep Learning
• Data Assimilation
• +3 more

Wei Kang is a Professor of Applied Mathematics at the Naval Postgraduate School (NPS) and an Adjunct Professor at the University of California, Santa Cruz (UCSC), Baskin School of Engineering. His research focuses on computational nonlinear control, deep learning, data assimilation, bifurcation theory, and industrial applications. He holds a Ph.D. in Mathematics from UC Davis (1991) and has held academic positions since 1991, including roles as Department Chair (2018–2021) and Director of Collaborations (2008–2011). Key awards include SIAM Fellowship (2025), IEEE Fellow (2008), and the NPS Foundation’s Menneken Award (2003). His work spans theoretical control systems, optimal control algorithms, and applications in aerospace, power systems, and manufacturing. He has collaborated widely, including with Intel and EPRI, and contributed to conferences as a keynote speaker and organizer. Recent articles emphasize data assimilation, deep learning for control systems, and HJB equation solutions. His research bridges theory and practice, addressing challenges in observability, sensor placement, and high-dimensional optimization.

Chung Hao ChenView profile

Associate Professor

• Robotics
• Automated Surveillance Systems
• Computer Vision
• +7 more

Dr. Chung Hao Chen is an Associate Professor in the Department of Electrical and Computer Engineering at Old Dominion University (ODU), part of the Batten College of Engineering and Technology. He holds a Ph.D. in Electrical Engineering from the University of Tennessee, Knoxville (2009), and B.S./M.S. degrees in Computer Science and Information Engineering from Fu-Jen Catholic University, Taiwan (1997/1999). Prior to academia, he worked at Panasonic Taiwan Laboratory (2001–2003) and served in the National Military Academy (1999–2001). His research focuses on robotics, automated surveillance systems, computer vision, image processing, intelligent systems, data mining, and network analysis . Notable projects include developing multi-camera tracking systems, UAV-based object retrieval, and dynamic environment testing facilities for watercrafts. He has secured grants such as the NSF-funded 'State of the Art in Target Handoff' (2012–2015). Dr. Chen has published extensively in journals like IEEE Transactions on Image Processing , Computer Vision and Image Understanding , and Physics of Plasmas . His work spans technical areas including plasma chemistry, strain analysis in materials, and sensor fusion. Awards include Sigma Xi membership (2009) and travel grants from IEEE and TECRO. Education: Ph.D., Electrical Engineering, University of Tennessee, Knoxville (2009) M.S., Computer Science & Engineering, Fu-Jen Catholic University (1999) B.S., Computer Science & Engineering, Fu-Jen Catholic University (1997) Affiliations: Old Dominion University (2011–present) North Carolina Central University (2009–2011) He leads efforts in modular robotics, unmanned systems, and intelligent imaging , with applications in security, healthcare, and environmental monitoring. Current openings exist for Ph.D./MS students in computer vision, statistical analysis, and robotics.

Maurizio BocciaView profile

Associate Professor

• Operations Research
• Optimization
• Logistics
• +5 more

Maurizio Boccia is an Associate Professor at the University of Naples Federico II, affiliated with the Department of Electrical Engineering and Information Technologies. His research focuses on optimization methodologies and their applications in logistics, transportation systems, and healthcare management. He holds a Ph.D. in Operations Research and has contributed extensively to the development of exact and heuristic algorithms for complex scheduling and routing problems. Key research interests include combinatorial optimization, vehicle routing problems (e.g., TSP variants with drones), automated guided vehicle (AGV) scheduling, and optimization in healthcare settings. He has also explored educational strategies, such as the OPS4Math project, which integrates optimization techniques into mathematics education. His work frequently involves mixed-integer linear programming (MILP), branch-and-cut algorithms, and matheuristics. Notable applications include railway dispatching for the Union Pacific Railroad, operating room planning in hospitals, and logistics network design. He has collaborated on real-world projects, such as improving exam scheduling in Norway and optimizing postal collection routes in rural areas. Boccia’s publications span over two decades, with contributions to both theoretical advancements (e.g., lifted cover inequalities, Fenchel cuts) and practical implementations (e.g., web cache location models, traffic sensor placement). His research often bridges theoretical optimization frameworks with real-world operational challenges.

• Polymer Engineering
• Composite Materials
• Materials Science
• +6 more

Prof Xuesen Zeng is a Professor in the Centre for Future Materials at the University of Southern Queensland. His research focuses on advanced composite materials, polymer processing, and sustainable manufacturing. He holds a BEng from Shanghai Jiao Tong University and a PhD from NUSingapore. His work spans polymer composites, flame retardancy, and material defect detection using machine learning. Key research interests include thermoset composites, additive manufacturing, and environmental applications of materials science. He has pioneered methods for optimizing composite curing processes and reducing manufacturing costs through dielectric monitoring and digital twin technologies. His publications highlight innovations in fire-retardant materials, pultrusion process optimization, and modeling fiber distribution effects. Despite no explicit awards listed, his high research output (over 33,926 views and 7,345 downloads) reflects significant academic impact. Current projects include waste-to-value materials for energy storage and eco-friendly biocomposites.

• Shape Optimization
• Convex Geometry
• Spectral Geometry
• +3 more

Ilias Ftouhi serves as Assistant Professor at University of Nîmes, France, following an Alexander von Humboldt Postdoctoral Fellowship at Friedrich-Alexander Universität (Erlangen, Germany) from June 2023 to June 2025. He completed his PhD in January 2021 at Sorbonne University (Paris 6) under Professors Jimmy Lamboley and Antoine Henrot. His educational background includes: PhD in Mathematics, Sorbonne University (Paris 6), 2021 Thesis: "Blaschke--Santaló diagrams and other shape optimization problems" Dr. Ftouhi's research centers on shape optimization and geometric analysis, with specialized expertise in Cheeger constant inequalities, Blaschke-Santaló diagrams, and spectral properties of convex domains. His work bridges theoretical geometry with numerical methods to solve complex optimization problems involving planar convex sets and spectral functionals. Key contributions include establishing sharp geometric inequalities and developing numerical frameworks for shape optimization. Analysis of his 13 publications (2021-2025) reveals consistent focus on geometric optimization: 60% address Cheeger constant properties, 30% investigate Blaschke-Santaló diagrams and spectral diagrams, and 10% develop sensor placement methodologies. His research demonstrates increasing sophistication in handling width constraints, parallel bodies, and L^p-approximations, with strong emphasis on deriving complete systems of geometric inequalities. His scientific recognition includes: Alexander von Humboldt Postdoctoral Fellowship During his postdoctoral fellowship, he collaborated with Professor Enrique Zuazua's research group on dynamics and control problems. While no current advisees are documented, his collaborative publications with researchers like G. Saracco, E. Zuazua, and J. Lamboley indicate active mentorship roles. His work on sensor placement suggests potential future applications in control theory and industrial optimization. He was affiliated with the Chair for Dynamics, Control, Machine Learning and Numerics at Friedrich-Alexander Universität during his postdoctoral period, contributing to interdisciplinary research combining geometric analysis with numerical PDE methods.

Srinivas AkellaView profile

Professor

• Robotics
• Motion Planning
• Multi-Agent Systems
• +3 more

Srinivas Akella is a Professor of Computer Science at the University of North Carolina at Charlotte, affiliated with the College of Computing and Informatics. He holds a Ph.D. in Robotics from Carnegie Mellon University (1996). His research focuses on robotics, particularly motion and manipulation planning, multi-robot coordination, and digital microfluidic systems. His work includes developing geometric and optimization algorithms for applications in robotics, biotechnology, and data analytics. Key contributions include coordination of UAVs for coverage/formation tasks, digital microfluidic systems optimization, and manufacturing automation. His research has been supported by NSF, DOD, DARPA, and NCDOT. He received the NSF CAREER Award for outstanding research and education integration. Recent work emphasizes multi-robot path planning, sensor placement for environmental monitoring, and wastewater surveillance systems for public health applications. His projects often bridge theoretical algorithm development with practical implementations in domains like autonomous systems and biomedical engineering. Education: Ph.D. Robotics, Carnegie Mellon University (1996) Funding: NSF, DOD, DARPA, NCDOT Lab Focus: Multi-Agent Systems, Microfluidics, and Data Analytics

Antonia Baeza CaracenaView profile

Associate Professor

• Environmental Engineering
• Air Quality Management
• Industrial Hygiene
• +3 more

Antonia Baeza Caracena is an Associate Professor in the Department of Chemical Engineering at the University of Murcia's Faculty of Chemistry. Her research focuses on industrial hygiene, air quality management, and pollution control, particularly in urban environments. She holds a PhD from the University of Murcia (2001), where her thesis examined benzene, toluene, and xylene impacts on air quality in Murcia City under the LIFE-MACBETH project. Her work integrates technical and policy dimensions, addressing challenges like industrial noise evaluation, emission control in petrochemical facilities, and multi-pollutant monitoring strategies. She leads the Safety and Hygiene in Industry research group, emphasizing practical solutions for occupational safety and environmental sustainability. Notable contributions include methodologies for locating air quality monitoring stations and assessing benzene exposure in European cities. Recent research trends highlight urban pollution mitigation, with studies on nitrogen oxides, particulate matter, and benzene hotspot analysis. Her publications reflect interdisciplinary approaches combining environmental engineering, public health, and regulatory compliance. Grants and collaborations have supported field studies in Murcia and beyond. No scientific awards are listed. While no advisees are explicitly noted, her thesis supervision experience indicates mentorship capabilities. She actively contributes to the university's industrial ventilation design and environmental safety initiatives through her research group.

José Carlos AlvesView profile

Associate Professor

• Reconfigurable Digital Systems
• FPGA Technology
• Underwater Robotics
• +3 more

José Carlos Alves is an Associate Professor at the Faculty of Engineering of the University of Porto and a Senior Researcher at INESC TEC's Robotics and Autonomous Systems Centre. He holds a PhD in Electrical and Computer Engineering (1998) and has taught advanced digital design, microelectronics, and circuit analysis. His primary research focuses on reconfigurable digital systems (FPGA-based), underwater robotics, and acoustic localization. Education: BEng (1985) and PhD (1998) in Electrical and Computer Engineering from the University of Porto. Early career included roles as a teaching assistant and research at INESC Porto's CAD & Microelectronics group. Research interests span FPGA technology, marine robotic systems, sensor optimization, and underwater navigation. He has supervised multiple theses on topics like underwater acoustic systems, sensor calibration, and autonomous vehicle design. Contact: jose.c.alves@inesctec.pt.