Claudia Plant is a Professor in the Faculty of Computer Science , leading the Research Group Data Mining and Machine Learning . Her research focuses on clustering algorithms, data mining, and machine learning applications in areas like biomedical data, wind energy, and causality inference. She has contributed to projects such as Knowledge-infused Deep Learning for Natural Language Processing (2020–2028) and Hybrid Computational Sciences (2021–2021). Plant has authored over 160 publications, with recent work emphasizing deep learning, anomaly detection, and GPU-optimized algorithms. She actively engages in academic activities, including talks on clustering methods and interdisciplinary projects like Governing Algorithms: The Politics of Data and Decision-Making . Her research interests span clustering algorithms , graph neural networks , causality discovery , and ethical digital transformation . Notable projects include causal analysis of wind farm dynamics and AI-enhanced education tools. Plant’s work bridges computational methods with societal challenges, such as empowering marginalized communities through ethical technology adoption.
Sheryl Grace is an Associate Professor of Mechanical Engineering at Boston University, leading the Unsteady Fluid Mechanics & Acoustics Laboratory (UFMAL). Her primary appointment is in the Department of Mechanical Engineering within the College of Engineering. She holds a PhD from the University of Notre Dame. Her research focuses on unsteady aerodynamics, aeroacoustics, and fluid-structure interactions, with applications in aerospace systems, propulsion technologies, and biological acoustics. Notable projects include NASA-funded work on quieter vertical lift vehicles and computational modeling of gerbil hearing mechanics. Professor Grace’s research interests span aerodynamics, fluid dynamics, and acoustics. She develops analytical and computational models to predict sound and vibration generated by unsteady flows interacting with solid structures. Recent studies include noise reduction in aircraft wings, turbine blade fatigue analysis, and acoustic scattering in gerbil ears. Her work bridges theoretical models with practical engineering solutions, emphasizing cost-effective predictive tools for next-generation systems. Her publications highlight advancements in shock-droplet interactions, cavitation modeling, and machine learning applications in aeroacoustics. Collaborative projects include multi-institutional efforts to address urban air vehicle noise challenges. While no explicit awards are listed, her contributions to computational acoustics and fluid dynamics are recognized through extensive peer-reviewed output. Advising and grants: Professor Grace leads the UFMAL lab and has secured funding from agencies like NASA. Her research integrates fluid mechanics, acoustics, and computational methods to address industrial and environmental noise issues. She collaborates across disciplines, including mechanical engineering, aerospace, and biomedical acoustics.
Liu Lili is a Lecturer (Educator Track) in the Department of Computer Science at the School of Computing, National University of Singapore. She holds a Ph.D. from Nanyang Technological University and a Master's in Computer Science from Shanghai University. Prior to NUS, she served as a Senior Research Scientist at Singapore Polytechnic and a Scientist at A*STAR's Institute of High-Performance Computing. Her research focuses on Machine Learning, Computer Vision, and Multi-modal Learning, with applications in FinTech, Social Media Analysis, and Algorithms & Theory. Notable projects include AI-driven coating inspection systems for marine assets and behavioral competency assessment tools for navigational safety. She has contributed to robotics for construction quality assessment and interactive virtual environments for rehabilitation. Liu's publications span AI applications in finance, robotics, and material science, reflecting her expertise in bridging theoretical computer science with practical industrial solutions. Her work emphasizes automation, anomaly detection, and multi-modal data integration.
Lenan Zhang is an Assistant Professor in the Sibley School of Mechanical and Aerospace Engineering at Cornell University, joining in July 2024. He directs the Energy Research Laboratory (ERL), focusing on energy sustainability through advanced materials and metrology tools. His research spans thermal and fluid transport phenomena at extreme scales, and he has developed innovative solutions for clean energy and water production. Education: B.S., Mechanical Engineering, Shanghai Jiao Tong University and Purdue University (2016) M.S. and Ph.D., Mechanical Engineering, Massachusetts Institute of Technology (2018 and 2022) Research Interests: Advanced Materials, Computational Fluid Dynamics, Sustainable Energy Systems, and Thermal Systems. His work integrates mechanistic modeling and high-resolution spectroscopy to address global challenges in energy and environment. Publications: Recent work emphasizes solar desalination, energy-efficient systems, and electrochemical processes. Key trends include optimizing thermal localization, developing novel materials for desalination, and advancing renewable energy applications. Awards: Best Inventions of 2023 (TIME Magazine) Wunsch Foundation Silent Hoist and Crane Award (2022) Luis de Florez Award in Science (2021) Martin Family Fellowship for Sustainability (2020) Advising and Labs: Leads the Energy Research Laboratory (ERL) at Cornell. Prior roles include Research Scientist at MIT’s Mechanical Engineering Department. Collaborates across disciplines to advance clean energy solutions.
Dr. Mark Bissett is Reader in Nanomaterials at the University of Manchester's Department of Materials Engineering. He holds a PhD in Nanotechnology from Flinders University and was Research Assistant Professor at Kyushu University before joining Manchester. He directs the Advanced Nanomaterials Group focusing on 2D material applications. His research integrates graphene, carbon nanotubes, and transition metal dichalcogenides into electrochemical energy storage devices and polymer nanocomposites. Key areas include: Supercapacitor and battery electrode design Tribological coatings for industrial applications Multifunctional structural composites Publications span electrodeposition techniques, composite reinforcement strategies, and nanomaterial synthesis. Recent work shows strong emphasis on graphene-enhanced composites, MXene applications, and energy storage innovations. He teaches nanotechnology and composites courses, and leads the Nanotechnology unit coordination. Industrial collaborations include his role as CSO at MOLYMEM Limited. Laboratory facilities at the National Graphene Institute support his group's experimental work.
Dr. Sonja Pullen is a Visiting Professor at the University of Amsterdam's Faculty of Science, affiliated with the Van 't Hoff Institute for Molecular Sciences. Her research focuses on photocatalysis, coordination chemistry, and supramolecular systems, with particular emphasis on developing sustainable energy conversion technologies. Key areas include molecular catalyst design, confined-space catalysis, and light-driven chemical transformations. Her work integrates advanced spectroscopic techniques (e.g., ultrafast spectroscopy) to study catalytic mechanisms, particularly in systems like diiron complexes and metal-organic frameworks (MOFs). Recent projects explore oxygen-tolerant catalysts, substrate-binding effects in photocatalytic dehalogenation, and the role of hydrogen bonding in catalytic activity. She also investigates functional materials such as coordination cages for artificial photosynthesis. Dr. Pullen’s publications highlight breakthroughs in catalyst stability, reaction selectivity, and energy-efficient processes. Her interdisciplinary approach bridges organic/inorganic chemistry, materials science, and renewable energy applications. Current trends in her work emphasize environmental sustainability and scalable photocatalytic systems for hydrogen production and CO2 conversion. Her lab at the Van 't Hoff Institute collaborates widely on topics like molecular encapsulation, MOF functionalization, and bioinspired catalysts. Ongoing projects aim to enhance photocatalytic efficiency through structural design and confinement strategies.
Paolo Samorì is a full-time Professor at the Université de Strasbourg , where he serves as Director of the Nanochemistry Laboratory and Emeritus Director of the Institut de Science et d'Ingénierie Supramoléculaires (ISIS) . He is affiliated with multiple prestigious academies, including the German National Academy of Science and Engineering (ACATECH) , Royal Society of Chemistry (FRSC) , and European Academy of Sciences (EURASC) . Education: Laurea (MSc) in Industrial Chemistry (University of Bologna, 1995), PhD in Chemistry (Humboldt University Berlin, 2000, summa cum laude). His research focuses on Nanochemistry , 2D materials , and supramolecular systems at interfaces , with applications in organic electronics , optoelectronics , and sensing . He pioneered methods for scanning probe microscopies and photoresponsive nanodevices , including graphene-based systems and diarylethene molecular switches. His scientific awards include the ERC Advanced Grant (2019) , Blaise Pascal Medal (2018) , and Catalán-Sabatier Prize (2017) , among 20+ honors. He has trained over 130 students and researchers , including 34 professors now active globally.
Saurabh Bagchi is a Professor at Purdue University, West Lafayette, USA. He holds a PhD in Computer Science from the University of Illinois Urbana-Champaign (2001). His research focuses on distributed systems security, networking, and embedded systems. Key areas include IoT security, cyber-physical systems resilience, and machine learning applications in edge computing. Bagchi's work spans theoretical and applied domains, addressing challenges in distributed algorithms, fault tolerance, and secure communication protocols. His contributions to firmware analysis, serverless computing optimization, and anomaly detection in industrial IoT systems have been widely recognized. He has published over 300 papers in top-tier conferences and journals such as IEEE Transactions on Dependable and Secure Computing, ACM Transactions on Sensor Networks, and CVPR. He collaborates with researchers in academia and industry to advance resilient networked systems, including projects funded by NSF and industrial partnerships. His lab explores cutting-edge topics like federated learning security, edge computing architectures, and game-theoretic approaches to cyber defense.
David Blaauw is the Kensall D. Wise Collegiate Professor of Electrical Engineering and Computer Science (EECS) at the University of Michigan. His research focuses on ultra-low-power analog/mixed-signal circuits, mm-scale sensors, neural networks, and biomedical applications. He leads the Blaauw Lab, which has pioneered innovations like the Michigan Micro Mote (M^3) and neural recording probes. His work emphasizes real-world deployability, with applications in environmental monitoring (e.g., monarch butterflies), medical devices, and robotics. Education: B.S. in Physics and Computer Science, Duke University (1986) Ph.D. in Computer Science, University of Illinois Urbana-Champaign (1991) Research Interests: Blaauw’s lab explores ultra-low-power computing, mm-scale systems, RF communication, in-memory computing, and genomics acceleration. Key projects include: Millimeter-scale computers (e.g., 0.04mm³ temperature sensors) Wireless neural interfaces for brain-machine communication Energy-efficient accelerators for edge AI and genomics Micro-robotics with sensing/actuation/computation Awards: IEEE Fellow 2016 SIA-SRC Faculty Award Motorola Innovation Award Best Paper Awards at ISSCC, ISCA, and RFIC Advising & Impact: Over 600 publications, 65 patents, and 4 startup companies spun from his lab. Current research includes genome sequencing accelerators (GenAx) and neural recording dust for brain mapping. He directs the Michigan Integrated Circuits Lab and chairs major conferences like ISSCC and DAC. Labs/Teams: Blaauw Lab (University of Michigan) Michigan Integrated Circuits Lab (MICAL)
Knut Tore Alfredsen is a Professor in the Department of Civil and Environmental Engineering at NTNU. His research focuses on cold climate hydrology, environmental impacts of hydropower, river ice dynamics, and water resource management. He leads projects like Trygg Elv (flood detection tools) and Hydro Connect (climate change mitigation in hydropower). He supervises numerous PhD and master’s students and teaches courses in hydrology, hydropower engineering, and environmental design. His work combines field measurements, data analysis, and advanced modelling, often using LiDAR and remote sensing technologies. Key projects include Sagelva research catchment studies and evaluations of environmental impacts from hydropeaking and reservoir operations. He is an active contributor to international conferences and collaborates with organizations like NVE and the IAHR. Education: Not explicitly stated in the provided text. Affiliations: HydroCen, Center for Renewable Energy (FME), NTNU’s Civil and Environmental Engineering Department. Grants: Involved in projects like HydroFlex (turbine development) and Klima 2050 (runoff estimation). Awards: None explicitly mentioned. Labs/Teams: Leads research groups in ecohydraulics, river modelling, and cold climate hydrology. Research Highlights: Focuses on ice-jam flood hazards, hydropeaking effects on fish, and sustainable hydropower practices. Recent work includes LiDAR-based river bathymetry and historical river development analysis using AI.
Sverre Steen is a Professor and Head of the Department of Marine Technology at the Norwegian University of Science and Technology (NTNU). He leads the Kongsberg Maritime University Technology Centre focused on 'Ship Performance and Cyber-physical Systems' and is a member of the standing committee for the Symposium of Marine Propulsors. His research emphasizes ship propulsion, hydrodynamics, and big data analysis of in-service vessel performance. Key interests include seakeeping, high-speed marine vehicles, and model testing techniques. Steen teaches TMR 4217 Hydrodynamics of High-Speed Marine Vehicles , covering cavitation, experimental hydrodynamics, and propulsion systems. He collaborates internationally on projects like the Norwegian Ocean Technology Centre. His recent work explores wave-energy extraction via hydrofoil vessels, resistance modeling for fast ferries, and propulsion efficiency in real sea states. He has contributed to global shipping emission models (MariTEAM) and reliability analysis of structural components under vibration. Steen's publications span propulsion in waves, engine-propeller dynamics, and data-driven methods for ship performance monitoring. His applied research bridges experimental testing and computational modeling to address challenges in sustainable maritime transport and operational safety.
Özer Özkahraman is a postdoctoral researcher at the Division of Robotics, Perception and Learning (RPL) at KTH Royal Institute of Technology. He works under Ivan Stenius and John Folkesson, focusing on underwater mission planning, simulation, and integration of autonomous systems. His email is ozero@kth.se . He completed his PhD at KTH under Petter Ögren, researching large-scale multi-agent coverage planning for autonomous underwater vehicles (AUVs). Current projects include the SMaRCSim multi-domain simulation platform and development of underwater vehicles like LoLo, SAM, and Evolo. Research interests span autonomous underwater systems, multi-agent coordination, control systems, and simulation infrastructure. He emphasizes modular, accessible frameworks for vehicle testing and real-world deployment. His work bridges theoretical methods (e.g., control barrier functions) with practical applications in marine robotics. Publications focus on AUV navigation, environmental sensing, and adaptive control. Projects like Real2Sim aim to align simulation with real-world vehicle dynamics using motion capture data. He collaborates internationally on topics like data-driven damage detection and model compression for resource-constrained robots. No academic awards are explicitly mentioned. He actively seeks collaborators for projects in sonar simulation, flow field modeling, and cyber-physical system integration.
Dr. Hongxing Jiang is a Professor at the Whitacre College of Engineering, Texas Tech University, affiliated with the Department of Electrical & Computer Engineering. He holds the Edward E. Whitacre Jr. Chair and co-directs the Center for Nanophotonics. PhD in Physics, Syracuse University (1986) MS in Physics, Syracuse University (1983) BS in Physics, Fudan University (1981) His research focuses on III-Nitride semiconductors (BN, AlN, GaN, InN) for optoelectronics , photonics , and radiation detection . Key areas include solid-state lighting , energy-conversion devices , MOCVD growth , and micro-emitter arrays . Recent publications highlight advancements in h-BN quasi-bulk crystals , fast neutron detectors , and wide bandgap materials . Themes span crystal growth optimization , doping techniques , and optical characterization . National Academy of Inventors Fellow (2018) American Association for the Advancement of Science Fellow (2016) International Society for Optics and Photonics Fellow (2015) Optica Fellow (2014) American Physical Society Fellow (2010) China-U.S. Physics Examination and Application Fellow (1981) As co-director of the Center for Nanophotonics, Jiang leads research in semiconductor materials for high-energy lasers and neutron detection , emphasizing scalable growth methods like hydride vapor-phase epitaxy .
Dr. Yanchao Liu is an Associate Professor at Wayne State University's College of Engineering, Department of Industrial and Systems Engineering. He has received research funding from the National Science Foundation and the State of Michigan, including the NSF Career Award. His academic career spans prior industry roles as a Data Scientist and Manager of Advanced Analytics at Sears Holdings Corporation (2016-2017) and Director of Brand Marketing Analytics at Catalina Marketing Corporation (2017). He teaches courses in data science, IoT, and stochastic processes. B.S. Industrial Engineering, Huazhong University of Science and Technology (2006) M.S. Industrial Engineering, University of Arkansas (2008) Ph.D. Industrial and Systems Engineering, University of Wisconsin-Madison (2014) Dr. Liu's research focuses on mathematical modeling for transportation systems, industrial AI, and data analytics. His work addresses drone traffic management, battery-constrained delivery routing, and optimization algorithms for urban mobility. He has developed novel methods for UAV safety diagnostics, random forest implementations, and fairness-aware path planning in urban air mobility. His publications span journals like Journal of Guidance, Control and Dynamics , Transportation Research Part C , and IEEE Transactions on Intelligent Transportation Systems , with conference contributions at IISE and FAIM. His research combines theoretical advancements with practical applications in smart cities and logistics. NSF Career Award (2020) Faculty Research Excellence Award (2021) IEEE PES Best Conference Paper (2015) IEEE Transactions on Smart Grid Best Reviewer (2015) Hubei Province Distinguished Bachelor’s Thesis Award (2006) Dr. Liu advises PhD students like Zhenyu Zhou and J. Chen. He has contributed to energy market modeling (with M.C. Ferris) and published extensively on drone operations, machine learning algorithms, and stochastic processes. His work includes U.S. patent pending applications for UAV safety systems.
Lara A. Estroff is a Full Professor and the current Chair of the Department of Materials Science and Engineering at Cornell University's College of Engineering. She has been a faculty member since 2005 and served as Director of Graduate Studies from 2015 to 2019. Her academic leadership and research excellence position her at the forefront of bio-inspired materials and biomineralization research. Her educational background includes a B.A. in Chemistry from Swarthmore College (1997) and a Ph.D. in Chemistry from Yale University (2003), followed by an NIH-funded postdoctoral fellowship at Harvard University in the lab of Prof. George M. Whitesides. Dr. Estroff's research centers on the fundamental mechanisms of crystal growth, biomineralization, and pathological mineralization. She investigates how organisms control mineral formation and applies these principles to engineer synthetic materials with complex structures and functionalities. Her work spans biomaterials, tissue engineering, and energy materials—particularly hybrid organic-inorganic perovskites for photovoltaics. She employs advanced characterization techniques and has pioneered in situ methods to monitor crystallization dynamics. Her recent publications reveal a strong trend toward interdisciplinary research, integrating materials science with cancer biology, immunology, and machine learning. The articles emphasize bio-inspired synthesis, mineral-tissue interactions, and the development of functional crystalline materials for medical and energy applications. Faculty Early CAREER Award, National Science Foundation (2009) Fiona Ip Li '78 and Donald Li '75 Excellence in Teaching Award, Cornell College of Engineering (2007) Marilyn Emmons Williams Award, Cornell Undergraduate Research Board (2009) Keynote Speaker, Gordon Research Seminar on Biomineralization (2012) Lawrence Berkeley National Lab Affiliate (2013) Dr. Estroff leads a major DOE-funded project titled “Formulation Engineering of Energy Materials via Multiscale Learning Spirals,” a $3 million, three-year initiative using machine learning to optimize perovskite synthesis for solar cells. She has advised numerous graduate students and postdoctoral researchers, and her lab is known for fostering collaborative, cross-disciplinary research. She has also contributed to educational initiatives at Cornell, particularly in undergraduate research and materials education. Her research group operates at the intersection of chemistry, engineering, and biology, focusing on high-resolution characterization of biominerals, in situ crystal growth studies, and the design of in vitro models for cell-mineral interactions. The lab actively collaborates with institutions including Lawrence Livermore National Laboratory, National Renewable Energy Laboratory, and Johns Hopkins University.
