Find Academic Supervisors

Alejandro MartinezView profile

Lecturer

• Mechanical Engineering
• Materials Science
• Robotics
• +5 more

Alejandro Martinez is an Instructor at the Michael W. Hall School of Mechanical Engineering, Mississippi State University (MSU), since 2021. He holds an M.S. (2021) and B.S. (2019) in Mechanical Engineering from MSU. His research focuses on gecko-inspired adhesives, leveraging mold design, casting, and precision CNC micro-machining. He develops predictive finite element models to enhance adhesive designs for applications in robotics and electronics. He advises the MSU Manufacturing Club, Formula SAE, Baja SAE, and Mississippi State Space Robotics Club, emphasizing hands-on learning and innovation. Education: M.S., Mechanical Engineering, Mississippi State University, 2021 B.S., Mechanical Engineering, Mississippi State University, 2019 Research Interests: Manufacturing of bio-inspired materials Finite element modeling for material performance Robotics applications in adhesive systems Integration of smart materials into mechanical systems Publications highlight contributions to structural dynamics, materials science, and education innovation. His work on titanium microstructure and digital twins demonstrates interdisciplinary reach. He collaborates with the PACCAR Advanced Manufacturing Lab and Mississippi State Space Robotics team, fostering student engagement through competitive engineering initiatives. Advising and Service: Co-advisor for multiple engineering clubs, emphasizing student-led projects in manufacturing and robotics. No grants explicitly mentioned in provided materials. Labs & Teams: Active in the PACCAR Advanced Manufacturing Lab and Mississippi State Space Robotics, promoting applied research and student development.

Sanjoy DasView profile

Associate Professor

• Machine Learning
• Quantum Computing
• Multi-agent Systems
• +3 more

Sanjoy Das is Associate Professor in Electrical and Computer Engineering at Kansas State University's College of Engineering, with research expertise in bio-inspired computing and complex systems. His laboratory investigates machine learning, quantum algorithms, and optimization techniques applied to energy grids and natural resource management. Key research areas: Evolutionary algorithms and swarm intelligence Neural networks for pattern recognition Quantum computing architectures Sustainable resource allocation models Teaching encompasses bio-inspired computing, neural networks, scientific computing, electromagnetics, and computer architecture. His interdisciplinary work bridges electrical engineering with computational sustainability, supported by funding from NSF, ONR, and USDA.

Yuksel CelikView profile

Part-Time Lecturer

• Artificial Intelligence
• Cyber Security
• Optimization Algorithms
• +3 more

Dr. Yuksel Celik is an Adjunct Lecturer at the University at Albany's Massry School of Business and an Associate Professor at Karabuk University (Turkey). He holds a PhD in Computer Engineering from Selcuk University (2013) and completed postdoctoral research in Information Security and Digital Forensics at SUNY Albany. Research Focus: His work spans artificial intelligence, cybersecurity, and optimization algorithms, with applications in healthcare, genomics, and agriculture. Key methodologies include deep learning, bio-inspired computing, and computer vision for solving complex real-world problems. Publication Trends: Recent articles (2023-2025) demonstrate strong emphasis on hybrid AI models, security applications, agricultural technology, and medical diagnostics. Common themes include optimization techniques, anomaly detection, and multimodal learning approaches. Awards & Honors: Senior Member of IEEE Academic Contributions: Actively mentors graduate students and leads research projects funded by grants including the EU Erasmus+ program. Teaches courses in cybersecurity, data structures, and mobile application development.

Tianyu ZhuView profile

Assistant Professor

• Polymer Synthesis
• Ceramic Engineering
• Coating Technology
• +7 more

Tianyu Zhu is an Assistant Professor in the Department of Materials Science and Engineering at Clemson University. He holds a Ph.D. in Chemistry from the University of South Carolina (2019) and a B.S. from Nanjing University (2015). His research focuses on synthesizing and processing soft materials and ceramics for energy storage applications, particularly in battery electrodes, polymer-ceramic composites, and sustainable manufacturing. Prior to Clemson, he worked at Quantumscape Inc. (2022-2023) and the Lawrence Berkeley National Laboratory (2020-2022). His work addresses challenges in energy frontiers, including battery recyclability, electrode stability, and green manufacturing. He has published over 50 peer-reviewed articles and holds 4 patents. Education: Ph.D., Chemistry, University of South Carolina, 2019 B.S., Nanjing University, 2015 Research Interests: Development of bio-based and recyclable polymers for sustainable materials Advanced manufacturing of battery components (electrodes, binders, electrolytes) Design of ceramic and composite materials for high-performance energy storage Optimization of lithium-ion and solid-state battery chemistries His recent publications highlight innovations in conductive polymer coatings, fluorine-free binders, and bio-inspired materials. His lab emphasizes green chemistry principles and cross-disciplinary approaches to energy storage challenges. No awards or grants are explicitly listed in the provided text.

• Cybersecurity
• AI/Machine Learning
• Wireless Networking
• +9 more

Dr. Danda B. Rawat is an Associate Dean for Research & Graduate Studies and Full Professor in the Department of Electrical Engineering & Computer Science at Howard University's College of Engineering and Architecture (CEA). He leads several initiatives, including the Howard University Data Science & Cybersecurity Center and the DoD Center of Excellence in AI/ML. His research focuses on cybersecurity, machine learning, and wireless networking for emerging systems like IoT, smart cities, and tactical autonomy. Dr. Rawat has secured over $110M in research funding and graduated 39 PhD students, many from underrepresented groups. He holds numerous awards, including the NSF CAREER Award and DHS Scientific Leadership Award. Education : PhD in Computer Science from Old Dominion University. Research Interests : Cybersecurity, AI/ML, wireless networking, tactical autonomy, federated learning, and quantum computing. His work addresses challenges in secure autonomous systems, edge intelligence, and ethical AI. Awards : Includes NSF CAREER, DHS Leadership Award, Presidents’ Medal (Howard University), and IEEE recognitions. He is a Fellow of the IET and ACM/IEEE Distinguished Lecturer. Labs & Teams : Directs the CWiNs Lab, DoD CoE-AIML, and RITA (UARC). Active in federal consortia linking HBCUs to defense innovation. Grants : Over $110M as PI, including a historic $90M USAF contract for RITA, the first HBCU-led UARC.

Giancarlo FortinoView profile

Professor

• Internet of Things
• Wearable Computing
• Distributed Systems
• +2 more

Giancarlo Fortino is a Full Professor of Computer Engineering at the University of Calabria, where he directs the SPEME lab and serves as Rector's delegate to International Relations. He holds a PhD in Computer Engineering from the University of Calabria and has held distinguished positions at Wuhan University of Technology and Huazhong Agricultural University. His research spans wearable computing systems, Internet of Things, e-Health, and distributed systems. He leads development of open-source frameworks including SPINE for body sensor networks and BodyCloud for cloud-assisted healthcare systems. His work consistently addresses real-world challenges in IoT and edge computing. Professor Fortino has received numerous honors including IEEE Fellow (2022), Highly Cited Researcher recognition (2020-2022), and best paper awards at premier conferences. He has authored over 600 publications and leads multiple EU-funded projects on IoT systems. He co-founded SenSysCal and BigTech spin-offs, serves on editorial boards of premier journals, and has graduated 10 PhD students who now hold academic and industry positions worldwide.

Riccardo CantiniView profile

Assistant Professor

• Deep Learning
• Large Language Models
• Sustainable AI
• +3 more

Riccardo Cantini is an Assistant Professor (RTDA) at the Department of Computer Science, Modeling, Electronics and Systems Engineering (DIMES), University of Calabria. He holds a European Ph.D. in Information and Communication Technologies (2023) and has been a visiting researcher at the Barcelona Supercomputing Center (BSC-CNS, 2021-2022). His research focuses on deep learning (Large Language Models, sustainable AI) and big social data analysis targeting politically polarized data and high-performance distributed systems. Education: B.Sc. (2016), M.Sc. (2019), and Ph.D. (2023) in Computer Engineering from the University of Calabria. Research interests include: Large Language Models and their ethical deployment Sustainable AI and energy-efficient edge computing Political polarization analysis using social media data Optimization of data-intensive workflows in distributed environments Key projects include the FAIR initiative (Green-Aware AI), eFlows4HPC (HPC workflows), and ASPIDE (Exascale data processing). He has authored/co-authored over 30 publications, including works on bias detection in LLMs and explainable AI in healthcare. Awards: 2024 Top 3 Best PhD Thesis in Big Data & Data Science (CINI), 2022 Editor's Choice article in Big Data and Cognitive Computing . Teaching roles include courses on Business Intelligence, High-Performance Computing, and Operating Systems. He has advised over 40 theses in AI, NLP, and big data. Professional services: Guest Editor for Big Data and Cognitive Computing , Program Chair of Green-Aware AI workshops, and reviewer for top journals/conferences (ICLR, IEEE BigData, etc.).

Alessandro Di StefanoView profile

Senior Lecturer

• Game Theory
• Network Science
• Machine Learning
• +4 more

Dr. Alessandro Di Stefano is a Senior Lecturer in Computer Science at Teesside University's Department of Computing & Games within the School of Computing, Engineering & Digital Technologies. He holds a PhD in Systems Engineering from the University of Catania (2015) and has held academic and research positions at King’s College London, the University of Cambridge, and the University of Catania. His research focuses on interdisciplinary methodologies combining game theory, network science, and machine learning to study socio-technological systems, human cooperation, and complex dynamics. Education: BSc (2009) and MSc (2012) in Telecommunications Engineering from the University of Catania; PhD in Systems Engineering (2015). Professional Qualifications: Postgraduate Certificates in Learning & Teaching in Higher Education (FHEA, 2022). Research Interests: Game Theory, Network Science, Machine Learning, Human Cooperation, Social Dynamics, Homophily, Epidemic Spreading. He collaborates globally, including with the University of Cambridge, Missouri S&T, and King’s College London. Grants/Projects: Lead PI on projects such as KTP - TaperedPlus (AI-driven design systems) and KTP - CSX Carbon (peatland restoration via deep learning). Active in conferences like CCS, ALIFE, and IJCAI, and serves as a reviewer for top journals (IEEE Transactions, Nature Scientific Reports). Labs/Teams: Part of the Interpretable & Beneficial AI group at Teesside, focusing on AI ethics, regulatory frameworks, and complex network modeling. Collaborates with industry partners on AI applications in construction, healthcare, and environmental monitoring.

• Thermal Engineering
• Nuclear Fuels
• Microgravity Fluid Dynamics
• +4 more

Troy Munro is an Associate Professor in the Department of Mechanical Engineering at Brigham Young University (BYU), part of the College of Engineering. His research focuses on thermal engineering, advanced materials, and microfluidics, with applications in nuclear energy, microgravity fluid dynamics, and biomedical systems. He holds a joint PhD in Mechanical Engineering and Physics from Katholieke Universiteit Leuven (KU Leuven) and Utah State University (2016), and has led research initiatives in thermal property measurement, friction stir welding, and quantum dot-based temperature sensors. Education includes: PhD (2016): Joint program at KU Leuven and Utah State University MS (2012): Mechanical Engineering, Utah State University BS (2012): Mechanical Engineering, Utah State University Research interests emphasize interdisciplinary approaches to thermal systems, including: Development of novel thermal measurement techniques (e.g., 3D-printable microscopes, needle probes) Thermal behavior of nuclear fuels and molten salts Microfluidic device design and temperature control Material characterization of bio-inspired fibers and composites His work integrates machine learning for data analysis, such as neural networks applied to quantum dot thermometry and microfluidic temperature reconstruction. He has contributed to over 30 peer-reviewed publications and has been an Assistant Professor at BYU since 2016. Advising and grants include leading the BYU Mechanical Engineering Graduate Research Program and collaborations with institutions like the U.S. Department of Energy on nuclear fuel research. His lab develops innovative solutions for thermal challenges in energy, aerospace, and biomedical fields.

• Dynamics and Control
• Robotics
• Autonomous Systems
• +3 more

Animesh Chakravarthy is a Professor in the Department of Mechanical and Aerospace Engineering at The University of Texas at Arlington (UTA). He holds a PhD in Aeronautics and Astronautics from MIT (2007). His research focuses on Dynamics and Control, Robotics, Autonomous Systems, and Cyber-physical Systems, with notable contributions to UAV collision avoidance, swarm intelligence, and cyber-resilient networks. He has led over $5M in federal grants from NSF, NASA, and DOD, including a NSF CAREER Award (2014). His work has been featured in journals like IEEE Transactions and AIAA Journals, and news articles highlight innovations in drone safety and autonomous flight systems. Chakravarthy advises numerous graduate students and has supervised 20+ theses/dissertations. He is a Fellow of AIAA (2020), Member of the National Academy of Inventors (2021), and serves on editorial boards for major conferences (e.g., American Control Conference). His lab develops cutting-edge solutions for UAV swarms, morphing aircraft, and cyber-physical security.

• Structural Integrity
• Composite Materials
• Fracture Mechanics
• +3 more

Dr. Shiyao Lin is an Assistant Professor in Mechanical and Aerospace Engineering at the University of Texas at Arlington and member of the Institute for Predictive Performance Methodologies. He holds a PhD from University of Michigan and BS/MS from Huazhong University of Science and Technology, with prior industry experience at Intel and postdoctoral research at University of Michigan. His lab (LIRAM) investigates structural integrity challenges across multiple scales, including progressive failure in composites, semiconductor reliability, bio-inspired 3D printed materials, and impact damage. Research employs experimental characterization, computational modeling, and data-driven approaches to enhance material performance and reliability. Recent grants include DURIP funding for composite damage characterization systems ($183K, AFOSR) and a UTA seed grant for biomimetic composites ($12K). Awards: Rising STARs award (2023), AIAA Structures Paper Awards (2020, 2021), ASC Scholarship (2020), NSF Travel Grant (2024).

Barry TrimmerView profile

Professor

• Neuromechanics of Locomotion
• Modulation of Nociception
• Soft Robotics
• +7 more

Barry Trimmer is the Henry Bromfield Pearson Professor of Natural Science in the Department of Biology at Tufts University, with additional appointments as Professor of Biomedical Engineering and Assistant Professor of Neuroscience. He leads the Neuromechanics and Biomimetic Devices Laboratory (BDL), where he studies the neurobiology of soft-bodied locomotion using the tobacco hornworm Manduca sexta as a model system. His research spans multiple interdisciplinary areas including neuromechanics of locomotion, nociception modulation, soft robotics development, and tissue engineering. Dr. Trimmer's work bridges fundamental biological research with engineering applications, particularly in creating bio-inspired soft robots and exploring cellular agriculture applications. The recent publications reflect a strong trend toward applying biological principles to robotics and sustainable food production. His work increasingly focuses on translating insights from insect neurobiology into soft robotics design, while expanding into cellular agriculture applications using insect cell cultures. This represents a growing interdisciplinary convergence between neurobiology, robotics, and sustainable food technology. Professional Distinctions: Distinguished Visiting Fellow at Scottish Informatics and Computer Science Alliance, University of Edinburgh (2018) Benjamin Meaker Visiting Professor at University of Bristol (2017) Nominated for IEEE EMBS Distinguished Lecturer (2019) Dr. Trimmer advises multiple PhD students including Gayathri Kondakath (studying nociception circuits) and Naya McCartney (investigating muscle development). His laboratory collaborates extensively with Professors Kaplan and Levin on tissue engineering projects. The lab maintains active grant funding from NSF, NIH, and DARPA for research on soft-bodied locomotion, biocomponent devices, and soft robotics. The Neuromechanics and Biomimetic Devices Laboratory focuses on three major research thrusts: understanding neuromechanical control systems in soft animals, developing SoftWorm robot platforms, and engineering novel biological devices through tissue engineering approaches. The lab combines neurobiological studies with advanced fabrication techniques including multi-material 3D printing.

Reuth MirskyView profile

Assistant Professor

• Artificial Intelligence
• Robotics
• Human-Computer Interaction
• +5 more

Reuth Mirsky is an Assistant Professor in the Department of Computer Science at Tufts University's School of Engineering. She holds a PhD from Ben Gurion University (2019). Her research focuses on artificial intelligence, robotics, and human-robot interaction, with particular emphasis on goal recognition, multi-agent systems, and ethical AI. She has taught courses including Special Topics in Data Analysis, Multi-Agent Systems, and Dissertation Research. Her work explores themes like collaborative control, social navigation, and the theory of mind in AI systems. Education: PhD in Computer Science from Ben Gurion University (2019) Research interests include advancing AI's ability to recognize and adapt to human goals, particularly in dynamic and exploratory environments. Key areas include developing robust algorithms for real-time goal recognition and improving trust in AI through ethical design principles. Recent work addresses challenges in human-AI teamwork, including intelligent disobedience and perception of robotic teammates. Her publications highlight contributions to social robot navigation, ad hoc teamwork, and the ethical implications of AI agency. She actively contributes to interdisciplinary research, co-editing special issues on AI-HRI and organizing workshops on human-interactive robot learning (HIRL).

Thomas WennekersView profile

Associate Professor

• Neural Networks
• Cognitive Modeling
• Computational Neuroscience
• +2 more

Thomas Wennekers is an Honorary Associate Professor at the University of Plymouth's School of Engineering, Computing and Mathematics. His research focuses on developing biologically constrained neural network models to understand cognitive functions such as language processing, memory formation, and sensory integration. He specializes in hierarchical temporal memory systems and spiking neural networks. Wennekers investigates neural mechanisms underlying semantic processing, cognitive impairments like dementia, and cross-modal plasticity in sensory systems. His work combines computational neuroscience with robotics to create bio-inspired cognitive systems, examining how neural constraints shape learning and perception. His publications explore neurobiological models of language, visual processing, and memory, with applications in neuromorphic computing and cognitive robotics. Recent work simulates neural reorganization in blind individuals and models cognitive disorders using brain-constrained architectures.

Alex AzizView profile

Lecturer

• Computational Materials Science
• Energy Storage
• Defective Graphene
• +2 more

Dr. Alex Aziz is a Lecturer in Materials/Physical Chemistry at Manchester Metropolitan University’s Joint Education Institute with Hubei University. He holds a PhD in computational chemistry (University of Reading) and completed postdocs at CICEnergiGUNE (Spain), Tohoku University (JSPS fellowship, Japan), and University of Bath. Research employs density functional theory (DFT) and molecular dynamics to optimize materials for energy storage/generation, especially defective graphene supercapacitors and battery systems. Collaborates internationally on photovoltaic and thermoelectric materials. Recent articles (2021-2024) focus on computational design of carbon nanomaterials, battery cathodes, and biomimetic hybrids, with emerging work in AI for materials discovery. Teaches thermodynamics, kinetics, and materials characterization at undergraduate/postgraduate levels. Member of Royal Society of Chemistry and JSPS Alumni. Reviews for Scientific Reports and ACS journals.