Find Academic Supervisors

Ben HardyView profile

Clinical Professor

• Management and Physiology Interaction
• Philosophical Foundations of Management Research
• Linguistic Factors in Survey Research
• +3 more

Clinical Professor of Organisational Behaviour and Academic Director overseeing Sloan, EMBA Dubai, and EMBA London programmes at London Business School. Holds veterinary medicine (Edinburgh) and management degrees (Cambridge). His research bridges management and physiology, exploring hormonal impacts, autonomic nervous systems in leadership, and philosophical foundations of management knowledge. Media-featured work has been covered by BBC, Wall Street Journal, and Financial Times. Recognitions include AT Kearney Global Prize and IBM Fellowship. Consults with global firms like Barclays, HSBC, and Novartis. Education : BVM&S (Edinburgh) MPhil, MBA, PhD (Cambridge) Research Focus : Explores physiological correlates of decision-making (e.g., cortisol effects on risk-taking), linguistic survey pitfalls, and philosophical rigor in operational research. Notable work includes interoceptive ability predicting trader success and cortisol's role in financial choices. Publications Trends : Recent work spans public policy analysis, healthcare decision-making during pandemics, and mixed-methods research innovations. Earlier studies examined morale in contact centres and hormonal influences in organisational settings. Awards & Roles : AT Kearney Global Prize Winner IBM Fellowship Recipient Former BBC University Challenge finalist Trustee of International Cat Care Teaching focuses on leadership and management across industries. Consulting expertise spans financial services, healthcare, and technology sectors. Active in promoting workforce wellbeing through physiological and psychological insights.

Simon McKenzieView profile

Research Fellow

• International Humanitarian Law
• Autonomous Weapons Systems
• Law of Armed Conflict
• +2 more

Dr. Simon McKenzie is a Research Fellow at the University of Queensland School of Law, focusing on legal challenges in defense and security technologies, particularly autonomous systems and their regulation under international law. His research spans autonomous weapons, maritime security, and cyber warfare frameworks. Education includes combined Arts/Law degree from University of Tasmania (2011) and PhD in international criminal law from University of Melbourne (2018). Professional experience includes policy work in Victorian Department of Justice and researcher roles at Supreme Court of Victoria and International Criminal Court. Research Focus: McKenzie examines legal implications of emerging military technologies: Autonomous weapons systems regulation Maritime law and unmanned vehicles Cyber operations compliance International humanitarian law applications AUKUS security implications His recent publications demonstrate growing expertise in autonomous maritime systems regulation and computational aspects of warfare law.

Tulga ErsalView profile

Associate Professor

• System Dynamics and Control
• Autonomous and Semi-Autonomous Vehicles
• Human-Autonomy Interaction
• +6 more

Tulga Ersal is an Associate Professor in the Department of Mechanical Engineering at the University of Michigan's College of Engineering. His work focuses on system dynamics and control, with applications in autonomous vehicles, energy systems, and human-autonomy interaction. He leads research at the 2019 Auto Lab in Ann Arbor, Michigan, and mentors PhD and Master’s students in fields like robotics, powertrain optimization, and biofeedback systems. B.S.E. from Istanbul Technical University (2001) M.S. and Ph.D. from University of Michigan (2003, 2007) Dr. Ersal’s research spans three core areas: Vehicle Systems: Autonomous/semi-autonomous navigation, trajectory planning on deformable terrains, and powertrain management Energy Systems: Battery modeling, fuel cells, microgrid optimization using extremum seeking Human Factors: Driver distraction modeling, cognitive workload estimation via eye tracking, and haptic shared control frameworks His publications often integrate control theory with real-world applications, emphasizing computational efficiency and robustness. Recent work includes terrain-adaptive trajectory planning (2025), Bayesian workload estimation (2024), and 3D terrain navigation algorithms (2023). He advocates for model fidelity and practical implementation in hardware-in-the-loop simulations. Scientific awards include: Kenneth M. Reese Outstanding Research Scientist Award (2018-19) UMOR Research Faculty Recognition Award (2016) Dr. Ersal's advising philosophy prioritizes individualized guidance, weekly one-on-one meetings, and collaborative group discussions. His students frequently present at conferences like the American Control Conference and ASME Dynamic Systems and Control Conference. Funding for student travel comes through Rackham Travel Grants, conference support programs, and research projects.

Junichiro KawaguchiView profile

Professor

• Asteroid navigation and characterization
• Spacecraft engineering
• Solar sails
• +3 more

Junichiro Kawaguchi is a Professor of Aerospace Engineering at the Australian National University (ANU), School of Engineering, within the College of Engineering and Computer Cybernetics. Previously, he served as a Senior Fellow at JAXA and held professorial roles at Tohoku University and the University of Tokyo. He is renowned for leading the Hayabusa mission (1996-2011), which achieved the first asteroid sample return from Itokawa, and pioneered the Ikaros solar sail project. His career includes contributions to lunar and Martian missions, and he has advised over 120 graduate students. Education: Bachelor's in Mechanical Engineering, Kyoto University (1978) PhD in Aerospace Engineering, University of Tokyo (1983) Research Interests: Focus on spacecraft engineering, asteroid exploration, solar sails, and interplanetary mission design. His work emphasizes innovative propulsion systems, sample return technologies, and low-cost deep-space exploration solutions. Awards: Guinness World Record Award (2011) AIAA Space Operations Award (2011) IAA Team Achievement Award (2011) National Space Foundation Award (2012) Von Braun Award (2011) Advising & Grants: Supervised over 20 PhD and 100 master's students. His grants include funding for Hayabusa-2 advisory work and OKEANOS solar sail missions. Labs/Teams: Core contributor to JAXA's Hayabusa project team and ANU's aerospace engineering research groups focused on solar sail and CubeSat technologies.

Serio AgriestiView profile

Visiting Professor

• Transportation Engineering
• Urban Planning
• Traffic Simulation
• +3 more

Serio Agriesti is a Visiting Professor at the Spatial Planning and Transportation Engineering department within Aalto University's Department of Built Environment . His expertise spans transportation engineering, urban planning, and automated mobility systems. He holds a Doctor of Technology (2024) and a Master's degree in Engineering from Politecnico di Milano (2017). Research Focus: Dr. Agriesti investigates traffic simulation methodologies , automated mobility services , and sustainable urban transportation systems . Key areas include multimodal transportation integration, large-scale transport model calibration, and the application of AI techniques like graph neural networks for traffic flow analysis. Recent Work Trends: His 2025 articles emphasize seamless multimodal integration , automated mobility demand analysis , and city-scale simulation frameworks . Earlier work (2023–2024) focuses on Bayesian optimization for transport model calibration and sustainability assessment of automated vehicles . Collaborations: Active in international transport research networks, with presentations at conferences on topics like activity-based modelling integration and synthetic population assignment. Co-developed a Zenodo dataset supporting a traffic simulation review paper (2024). Teaching/Advising: No formal student advisees listed. Academic contributions include peer-reviewed articles (22+) and datasets shared via academic platforms.

Merve KeskinView profile

Lecturer

• Operational Research
• Logistics Optimization
• Transportation Systems
• +3 more

Merve Keskin is a Lecturer in Operations Management and Decision Sciences at the Sheffield University Management School (The University of Sheffield). She holds a PhD and MSc in Industrial Engineering from Sabanci University and a BSc in Industrial Engineering from Istanbul Technical University. Her research focuses on modeling optimization problems in logistics and transportation, particularly addressing challenges such as resource allocation at airports, waste collection logistics, and the integration of electric vehicles into transportation networks. Previously, she worked as a Senior Research Associate at Lancaster University Management School on the OR-MASTER project (CENTRAL group), tackling airport resource allocation and real-world logistics optimization. She also served as a Knowledge Transfer Partnership Associate at Warwick Business School, collaborating with a waste collection company to reduce transportation costs via Decision Support Systems. Her teaching includes courses such as MGT138: Analysis for Decision Making B and MGT6155: Supply Networks Management . She is an Editorial Advisory Board Member of Transportation Research Part E . Currently, she supervises PhD candidate Razvan Marius Ionescu, whose research explores energy-efficient last-mile delivery using autonomous electric vehicles. Key research themes include electric vehicle routing, congestion charge zones, and adaptive optimization algorithms. Her work bridges theoretical operational research methodologies with practical industry applications, emphasizing sustainability and efficiency in logistics systems.

Sabrina M. NeumanView profile

Assistant Professor

• Computer Architecture
• Robotics
• Domain-Specific Accelerators
• +3 more

Sabrina M. Neuman is an Assistant Professor of Computer Science at Boston University, specializing in computer architecture design informed by domain-specific insights, particularly for robotics applications. She holds a PhD in Electrical Engineering and Computer Science from MIT and was a postdoctoral NSF Computing Innovation Fellow at Harvard University. Her research focuses on closing computational gaps in robotics through domain-specific accelerators, leveraging robot morphology for hardware design. She has received honors including the 2021 EECS Rising Star and the Boston University Innovation Career Development Professorship (2023-2026). Education: PhD in Electrical Engineering and Computer Science, MIT M.Eng. in Electrical Engineering and Computer Science, MIT S.B. in Electrical Engineering and Computer Science, MIT Research Interests: Her work emphasizes domain-specific computing for robotics, including automated hardware design flows, FPGA/ASIC acceleration for motion planning, and scalable accelerator deployment across robot platforms. She develops methodologies like Robomorphic Computing, which translates robot morphology into customized hardware accelerators, achieving significant speedups in critical robotics kernels. Awards & Recognition: 2021 EECS Rising Star IEEE Micro Top Picks Honorable Mentions (2022, 2023) 2023-2026 Boston University Innovation Career Development Professorship Grants & Contributions: Developed RobotPerf, an open-source benchmarking suite for robotics computing systems Worked on Grid (GPU-accelerated rigid body dynamics) and RobotCore (ROS 2 hardware acceleration) Labs & Teams: While no specific lab name is mentioned, her work integrates closely with Boston University's robotics and computer architecture groups, emphasizing open collaboration with industry and academia.

Richard HanView profile

Professor

• Mobile and Ubiquitous Computing
• Wireless Sensor Networks
• Drone Systems
• +4 more

Richard Han is a Professor in Networks and Distributed Systems at the School of Computing, Macquarie University. He leads the Macquarie University Advanced Drone Systems Research Centre and is affiliated with the Future Communications Research Centre. Previously, he held professorial roles at the University of Colorado Boulder (2001-2020) and was a Research Staff Member at IBM TJ Watson Research Center (1997-2001). Education: PhD in Electrical Engineering (UC Berkeley, 1997), BS with Distinction in Electrical Engineering (Stanford, 1989) His research focuses on drone systems, wireless sensor networks, cybersecurity, and cloud computing. Notable achievements include four best paper awards, over 13,000 Google Scholar citations, and prestigious grants like NSF CAREER and IBM Faculty Awards. Key Projects: Robust Autonomous Drone Landing (2022-2025) Research emphasizes practical applications such as emergency drone battery services, cooperative payload delivery, and privacy-preserving drone vision systems. He directs multiple research groups and collaborates internationally on sensor fusion and UAV applications.

Michele D. SimoniView profile

Assistant Professor

• Transportation Systems Analysis
• Urban Mobility Planning
• Traffic Flow Simulation
• +3 more

Michele D. Simoni is an Assistant Professor at the Department of Urban Planning and Environment at KTH Royal Institute of Technology in Stockholm, Sweden. He leads the project Investigating Sidewalks’ Mobility and Improving it with Robots (ISMIR) . His research focuses on advanced transportation systems, including last-mile freight optimization, autonomous vehicle impacts, and urban mobility policies. Education: Ph.D. in Civil Engineering (2019), University of Texas at Austin M.Sc. in Civil Engineering (2013), Delft University of Technology B.Sc. in Civil Engineering (2011), Polytechnic University of Milan Research Interests: Michele’s work integrates cutting-edge technologies like machine learning and sensor-based systems to address challenges in urban logistics, traffic management, and transportation policy. He has pioneered methods for curbside management, dynamic speed limit policies, and optimization of autonomous delivery systems. Grants & Projects: Current PI of ISMIR (2023–2025) and former postdoctoral research at MIT (2019–2020) and UT Austin (2015–2019). Active in collaborative projects on congestion pricing and automated vehicle integration. Labs & Teams: Leads the Transport Systems Analysis group at KTH, focusing on simulation frameworks for urban systems and robotics in logistics.

Faheem AhmadView profile

Research Fellow

• Power Electronics
• Industrial Heating
• Wide Bandgap Semiconductors
• +3 more

Faheem Ahmad is a Research Fellow at AAU Energy, Aalborg University, specializing in power electronics and industrial heating applications. He holds a PhD in Power Electronics from Aalborg University (2023), an M.Sc. in Energy Engineering (2020), and a B.Sc. in Electrical Engineering (2014) from Delhi Technological University. His research focuses on high-frequency converter topologies, resonant converters, and wide bandgap semiconductors, particularly for industrial heating systems. He has contributed to projects like GreenHeat (2023–2026) and RFheat (2020–2021), addressing energy-efficient RF generators and curing technologies. Education: PhD in Power Electronics, Aalborg University (2021–2023) M.Sc. in Energy Engineering, Aalborg University (2018–2020) B.Sc. in Electrical Engineering, Delhi Technological University (2010–2014) Research Interests: His work emphasizes advancing power electronics for industrial applications, including high-frequency converters and semiconductor integration in dielectric heating systems. He explores RF-based solutions for energy efficiency and modernizing industrial heating processes. Projects: GreenHeat : Developing energy-efficient RF generators for industrial heating (Innovation Fund Denmark, 2023–2026). CoDE : Center for Digitalized Electronics (Poul Due Jensen Foundation, 2021–2026). Transistorization of Industrial Dielectric Heating Plants : PhD project focusing on semiconductor-based heating systems (2021–2023). Impacts: His work on modular power converters has yielded economic impacts through improved industrial heating systems. He has presented at events like the PDJF Grundfos Prize Expo (2022–2023).

Joe JohnsonView profile

Researcher

• Precision Agriculture
• Robotics in Agriculture
• Plant Phenotyping
• +4 more

Joe Johnson is a Researcher at Texas A&M University’s College of Agriculture & Life Sciences, affiliated with Texas A&M AgriLife Research. He holds a PhD in Agronomy and completed his undergraduate studies in Electronics & Communications at the University of Calicut (2010) and a Master’s in Robotics from SRM University (2014). His research focuses on precision agriculture, integrating robotics, artificial intelligence, and 3D modeling to address challenges in crop-weed interaction analysis, automated weed control systems, and agricultural automation. His work emphasizes multi-modal data collection platforms, deep learning applications for crop phenotyping, and robotic systems for precision agriculture. Key technical contributions include developing robotic flaming weed control systems using quadruped robots, multi-view 3D reconstruction techniques for plant morphological trait estimation, and AI-driven approaches for crop-row detection and biomass estimation. He collaborates closely with the Texas A&M AgriLife Extension Service and the Department of Soil and Crop Sciences. His research bridges computer science, mechanical engineering, and agricultural science to advance sustainable farming solutions. His publications from 2023–2025 highlight trends in robotic platforms for field monitoring, deep learning applications in crop-weed analysis, and thermal weed management systems. While no awards are explicitly listed, his work reflects innovative contributions to agricultural robotics and precision agriculture methodologies. Advising and grants: No formal advisees listed, but he collaborates with Prof. Muthu Bagavathiannan as part of his research team. His lab focuses on robotic systems integration and field-based agricultural technologies. He contributes to Texas A&M’s broader efforts in AgriLife Research programs targeting sustainable agriculture solutions.

• Turbulence
• Unmanned Systems
• Sensors
• +5 more

Dr. Abdulghani Mohamed is a Senior Lecturer in the School of Engineering at RMIT University, specializing in aerospace engineering with a focus on unmanned aerial systems, turbulence research, and biomimetic flight technologies. His research integrates principles from biology with engineering applications to advance drone technology and flight control systems. His research interests span Turbulence , Unmanned Systems , Sensors , Biomimetics , Aerodynamics , Experimental fluid dynamics , Computational fluid dynamics , and Energy harvesting systems . Dr. Mohamed's work demonstrates a strong connection between natural flight mechanisms observed in birds and engineered solutions for drone technology. His recent publications (2018-2024) reveal consistent research productivity with a clear trajectory toward increasingly sophisticated drone control systems, turbulence adaptation mechanisms, and biomimetic applications. The research shows a progression from fundamental aerodynamic studies toward practical implementations in urban air mobility and advanced drone systems. Open to Masters Research or PhD student supervision Active research projects in drone propeller optimization, turbulence mitigation, and biomimetic flight Dr. Mohamed maintains an active research program with numerous projects related to unmanned aerial systems and their applications in complex environments. His work bridges theoretical aerodynamics with practical engineering solutions for next-generation flight systems.

• Communications Systems
• Defence Information Systems
• Cybersecurity
• +7 more

Dr Philip Nobles is a Lecturer at Cranfield University, affiliated with the Centre for Defence Engineering and Physical Science within the College of Engineering and Physical Sciences. He holds a PhD and MEng from Swansea University and has over 25 years of experience in academic and applied research in communications and cybersecurity. PhD, Swansea University MEng, Swansea University His research expertise lies in communications systems, defence information systems, and cybersecurity, with a focus on wireless networks, software-defined networking, military communications, and intrusion detection. He leads the development and delivery of an MSc module on Networked Systems and Cybersecurity for Connected and Autonomous Vehicles, and supervises research students. His work is supported by collaborations with DSTL/MOD, Airbus, EPSRC, BBC, and Philips Research Laboratories. Dr Nobles has published extensively on topics including intrusion detection sensor characterization, false positive responses, insider threat detection, and wireless communication systems. His publications reflect a strong trend in network security, sensor deployment optimization, and secure communications for defence and autonomous systems. Notable scientific contributions include work on: Characterising intrusion detection sensors False positive response mechanisms Scalable intrusion detection architectures Bayesian approaches to insider threat detection He actively supervises research students and contributes to high-impact projects funded by EPSRC and other strategic partners. His research integrates theoretical modeling with practical system deployment, particularly in military and critical infrastructure contexts. Dr Nobles is associated with the Department of Informatics and Sensors at Cranfield University, where he contributes to advanced research in network-centric warfare concepts and secure communication systems.

Roberto FurfaroView profile

Professor

• Guidance, Navigation and Control
• Machine Learning in Aerospace
• Space Situational Awareness
• +7 more

Roberto Furfaro is a Professor in the Department of Systems and Industrial Engineering and the Department of Aerospace and Mechanical Engineering at the University of Arizona, College of Engineering. He serves as Deputy Director of the Space, Security, Safety & Sustainability Center (S4C) and is a key figure in space situational awareness and planetary exploration systems. His educational background includes a Laurea Degree (MS equivalent) in Aeronautical Engineering from the University of Rome 'La Sapienza' (1998) and a PhD in Aerospace Engineering from the University of Arizona (2004). His research spans guidance and control of planetary landers, machine learning applications in space systems, hypersonic vehicle G&C, and systems engineering for small body proximity operations. He leverages advanced AI, particularly reinforcement learning and deep learning, to solve complex aerospace challenges. The recent publications reflect a strong trend toward intelligent, autonomous systems in spaceflight, especially using deep reinforcement learning for planetary landing, guidance under uncertainty, and space-based object tracking. His work bridges control theory, astrodynamics, and artificial intelligence. 2021 Da Vinci Fellow, College of Engineering AIAA Associate Fellow (2022) AAS Fellow (2021) Asteroid 133474 Roberto Furfaro named in honor of OSIRIS-REx contributions Prof. Furfaro has served as PI or Co-PI on over $80M in research grants from NASA, AFRL, and DoD. He has advised numerous students and leads research teams in autonomous space systems and machine learning applications. He is the Target Follow-up Working Group lead for the NASA NEO Surveyor Mission and was Systems Engineering Lead for SPOC during OSIRIS-REx Phase B-D. He is actively involved in professional service as Associate Editor for IEEE Transactions on Aerospace and Electronic Systems and technical member of the AIAA Astrodynamics Committee and AAS Space Surveillance Committee.

Larry HeadView profile

Professor

• Systems Engineering
• Industrial Engineering
• Intelligent Transportation Systems
• +7 more

Larry Head is a Professor in the Department of Systems and Industrial Engineering at the University of Arizona, College of Engineering. He serves as Director of the Craig M. Berge Engineering Design Program and is a Member of the Graduate Faculty. His extensive leadership roles include former Interim Dean of Engineering and Director of the Transportation Research Institute. He is actively engaged in transportation policy as a member of the Arizona Governor’s Task Force for Self-Driving Vehicles. Education: PhD in Systems and Industrial Engineering, University of Arizona MS in Systems Engineering, University of Arizona BS in Systems Engineering, University of Arizona Larry Head's research centers on intelligent and connected transportation systems, with a strong focus on cyber-physical systems, adaptive traffic signal control, and urban traffic operations. His work integrates real-time data from connected and automated vehicles to optimize traffic flow, improve intersection safety, and support multi-modal transportation. He also contributes significantly to engineering education, teaching courses in systems engineering, simulation, and financial modeling. His recent publications (2014–2022) demonstrate a consistent trajectory in leveraging connected vehicle technology for adaptive signal control, pedestrian safety, and traffic efficiency. Key themes include priority control for emergency and freight vehicles, smooth progression modeling, and data-driven safety assessment. The research spans disciplines such as transportation engineering, machine learning, and cyber-physical systems. Scientific Awards: Trevor O. Jones Outstanding Paper Award (2021) Exceptional Paper Award, TRB Traffic Signal Systems Committee (2017) 2016 Best ITS Implementation Project 2016 Member of the Year, ITS Arizona da Vinci Fellow, College of Engineering D. Grant Mickle Award for Outstanding Paper Best Dissertation Advisor Award, COTA Larry Head has advised numerous graduate students, many of whom are co-authors on his publications. He has secured significant research funding in intelligent transportation systems, though specific grants are not listed. His professional service includes editorial work for Transportation Research – Part C and leadership in TRB, SAE, IEEE, and other societies. He leads research initiatives at the ATLAS Research Center and collaborates on interdisciplinary transportation projects. He is an active member of several research teams focused on connected vehicle systems, traffic safety, and urban mobility. His lab work emphasizes real-world implementation of intelligent signal control and data analytics for transportation infrastructure.