Hilary Bart-Smith is a Professor in the Department of Mechanical and Aerospace Engineering at the University of Virginia. She founded the Multifunctional Materials and Structures Laboratory and the Bio-inspired Engineering Research Laboratory, emphasizing biomimetic designs and advanced mechanical systems. B.S., Mechanical Engineering, University of Glasgow Ph.D., Engineering Sciences, Harvard University Research Interests: Bio-inspired systems, Biotechnology and Biomolecular Engineering, Biomolecular Design, and Cellular and Molecular Bioengineering. Her work spans underwater robotics, deployable aerospace structures, and electro-active polymers with applications in artificial muscles and sensing technology. Publications (2025–2021): Focus on bio-inspired underwater propulsion, tuna and manta ray robotics, flexible foils, hydrodynamic efficiency, and deployable aerospace structures. Keywords include Bio-inspired Robotics, Computational Fluid Dynamics, and Electro-active Polymers. Labs: Multifunctional Materials and Structures Laboratory and Bio-inspired Engineering Research Laboratory at UVA.
Seyed Jalaleddin Mousavirad (Jalal) serves as a Postdoctoral researcher at Mid Sweden University in Sundsvall, Sweden, within the Department of Computer and Electrical Engineering (DET) and affiliated with the STC Research Centre. His research focuses on advancing AI-driven solutions for sustainable technologies and complex optimization problems. He earned his PhD in Computer Engineering specializing in Artificial Intelligence from the University of Kashan, Iran. Previous academic appointments include Assistant Professor at Hakim Sabzevari University (Iran), instructor roles at the University of Tehran (2018-2019) and Azad University (2019-2020), and a Research Fellow position at the University of Beira Interior (Portugal) where he contributed to the European GreenStamp project on sustainable Android applications. Dr. Mousavirad's research spans Image Processing and Computer Vision, Machine Learning, Evolutionary Computation, and Applied Artificial Intelligence, with significant contributions in pattern recognition, metaheuristic algorithms, and neural network optimization. His work demonstrates strong interdisciplinary applications in healthcare diagnostics, power systems, and medical imaging. Recent publications reveal a pronounced trend toward federated learning frameworks for privacy-preserving medical analysis, adversarial robustness in diffusion models, and hybrid optimization techniques for ECG classification and brain tumor detection. This reflects a strategic focus on translating AI innovations into practical healthcare and sustainability solutions. He actively contributes to the academic community as a guest editor for journals including Computational Intelligence and Neuroscience, Entropy, and Mathematical Biosciences and Engineering. His editorial leadership extends to organizing special sessions at IEEE CEC and EvoApplications conferences. Dr. Mousavirad maintains extensive peer-review commitments across 50+ prestigious venues including IEEE Transactions on Evolutionary Computation and IEEE Transactions on Cybernetics. His collaborative research includes international engagements at Xi'an Jiaotong-Liverpool University (China) and current work within Mid Sweden University's STC Research Centre on energy-aware computing and neural network optimization.
Marta Vivar Garcia serves as a Contracted Professor within the Department of Electronic and Automatic Engineering at the University of Jaén, actively contributing to the Center for Advanced Studies in Earth Sciences, Energy. Her work centers on the Research and Development in Solar Energy group, where she pioneers hybrid photovoltaic-water treatment technologies with global sustainability applications. She earned her PhD from Universidad Politécnica de Madrid in 2009 with a dissertation on Optimization of Euclidean Concentration Photovoltaic Technology , supervised by Dr. Gabriel Sala Pano. Her academic foundation integrates electronics engineering with renewable energy systems. Vivar Garcia's research focuses on solving critical water-energy challenges through innovations like the SolWat system, which simultaneously generates electricity and disinfects water using photovoltaic modules. Her work spans solar disinfection kinetics, hybrid system optimization, IoT-based monitoring for remote installations, and practical implementations in arid regions and refugee camps. She emphasizes scalable solutions for developing communities while addressing environmental and economic viability. Analysis of her 15 most recent publications reveals three dominant trends: (1) Evolution from basic SolWat prototypes to grid-integrated wastewater treatment systems compliant with EU regulations; (2) Increasing sophistication in pathogen-specific disinfection modeling using UV-LEDs and solar optics; (3) Strategic expansion into IoT-enabled mass monitoring for off-grid solar systems in resource-constrained settings. Her work consistently bridges fundamental engineering principles with urgent global sustainability needs. As leader of the Research and Development in Solar Energy group, she directs projects focused on photovoltaic-water synergy, with field trials spanning Mexico's rural communities to Saharawi refugee camps. Her team specializes in converting theoretical solar energy concepts into field-deployable technologies that address both electricity access and water safety challenges.
David Kazmer is a Professor in the Department of Plastics Engineering at the University of Massachusetts Lowell's Francis College of Engineering. With a Ph.D. from Stanford University (1995) and prior roles in industry (GE Research & Development, GE Plastics), he specializes in advanced manufacturing processes, particularly polymer processing, additive manufacturing, and intelligent process control. Education: BS (Cornell, 1990); MS (Rensselaer Polytechnic, 1991); PhD (Stanford, 1995). His research focuses on plastics product and process design , additive manufacturing , polymer rheology , and multivariate process control , with over 300 publications and 20 patents. Key contributions include innovations in injection molding sensors, fused deposition modeling, and sustainable polymer processing. Recent Google Scholar publications (2025-2024) highlight advancements in shell deposition additive manufacturing , co-extrusion for graded foams , thermal contact resistance modeling , and recycled polyolefin processing . These works span polymer blends, composite materials, and energy-efficient manufacturing systems. Scientific awards include: Fellow, Society of Plastics Engineers (2011) ASME Kos Ishii-Toshiba Award (2012) Office of Naval Research Career Award (1997) Multiple Best Paper Awards (ASME, SPE) As an Associate Research Professor in Mechanical & Industrial Engineering at UMass Amherst, he bridges interdisciplinary research. His industry experience with GE and Synventive Molding Solutions informs practical process development. Current projects involve self-powered sensors, machine learning for extrusion optimization, and community-focused engineering education initiatives.
Hans Georg Beyer is an Affiliated Professor in Energy Engineering at the Faculty of Science and Technology, The University of the Faroe Islands. His work focuses on sustainable energy systems with emphasis on renewable energy integration and meteorological aspects of power generation. With extensive publication history spanning over three decades, he has established himself as a leading researcher in renewable energy systems analysis. Professor Beyer's research interests center on sustainable energy supply systems based on renewables, with special emphasis on relating system performance characteristics to meteorological conditions. His work in Energy Meteorology covers analysis and modeling of spatial and temporal statistics of wind and irradiance fields, including forecasting methods for wind speed and solar irradiance with horizons of 6-35 hours and near now-casts in minute time scales. In Renewable Energy Systems, he investigates layout, dimensioning, modeling and performance analysis of grid-connected and stand-alone solar, wind and hybrid systems. His research bridges meteorological science with practical energy engineering applications, particularly for island and remote communities. His publication record shows consistent research activity with 55 research outputs documented, including significant contributions to solar and wind energy forecasting, hybrid system design, and grid integration challenges. Notable work includes the development of methods for satellite-derived irradiance data applications in PV system monitoring and performance assessment. Solar Energy Best Paper Award, ISES 1999 Solar World Congress, Jerusalem Professor Beyer has been instrumental in several major collaborative projects including PVSAT-2 (satellite-based PV system performance monitoring), SWERA (UNEP solar resource assessment), and various European initiatives focused on renewable energy integration. His work demonstrates strong international collaboration, particularly with German, Brazilian, and other European research institutions. While specific grant details aren't provided in the source material, his extensive publication record in high-impact journals suggests substantial research funding support throughout his career.
Brad Karp is a Professor of Computer Systems and Networks at University College London (UCL) , holding this position since 2005. His career spans multiple institutions and roles, including a Senior Lecturer (2005-2014) and Reader (2007-2014) at UCL, Adjunct Assistant Professor at Carnegie Mellon University , and Senior Staff Researcher at Intel Research Pittsburgh . He earned his PhD in Computer Science from Harvard University (2000) , preceded by an M.Sc. (1995) and B.Sc. (1992) in the same field from Harvard and Yale respectively. Research Interests : Systems security (operating systems, web browsers, application security) Wireless networking (multi-antenna capacity, interference management) Network routing (robustness, low-latency protocols) Distributed systems (DHTs, sensor networks) Scientific Contributions focus on optimizing network performance, enhancing security architectures, and developing practical routing algorithms. His work on gradient compression (2024) and low-latency routing topologies (2018) demonstrates continued relevance in network design. Earlier publications like OpenDHT (2005) and Polygraph (2005) established foundational contributions in distributed systems and security. Awards & Recognition : Royal Society-Wolfson Research Merit Award (2005-2010) Best Paper Award (Usenix 2014) Professional Activities include program committee roles for ACM SIGCOMM (2009, 2011-2017), HotNets (2008-2017), and NSF review panels. He has examined PhD theses at the University of Cambridge (2010) and contributed to the HotNets Steering Committee (2009-2014).
Mohsen Sharifpur is a Professor at the University of Pretoria, South Africa, within the Faculty of Engineering, Built Environment and Information Technology, Department of Mechanical and Aeronautical Engineering. He additionally holds appointments at China Medical University (Taiwan), Duy Tan University (Vietnam), and the University of Science and Culture in Tehran, reflecting a truly global academic footprint. His educational background is not explicitly detailed in the provided text, but his extensive publication record and affiliations suggest advanced degrees in mechanical or thermal engineering. Research Focus Thermal Engineering & Heat Transfer: Investigating fundamental and applied aspects of heat transfer enhancement, phase change phenomena, and energy conversion systems. Nanofluids & Advanced Materials: Exploring the synthesis, characterization, and application of nanoparticle-enhanced fluids for improved thermal performance in diverse engineering systems. Computational & Experimental Fluid Dynamics: Employing CFD, molecular dynamics, and experimental techniques to model complex multiphase flows and optimize energy systems. Sustainable Energy Technologies: Addressing contemporary challenges in energy efficiency, renewable energy forecasting, and environmentally friendly fuels such as biodiesel. Across more than 300 peer-reviewed publications, Prof. Sharifpur’s work demonstrates a consistent trajectory toward enhancing energy efficiency through nanotechnology, advanced computational methods, and sustainable engineering practices. His recent studies integrate machine-learning techniques (e.g., LSTM networks) for solar power forecasting, highlighting an interdisciplinary approach that bridges mechanical engineering and data science. Scientific Awards & Funding Sponsored research supported by the National Research Foundation (South Africa) National Institutes of Health (USA) National Natural Science Foundation of China King Saud University, Taif University, King Faisal University, and numerous other international agencies Collaborations & Teams Prof. Sharifpur leads or participates in multiple international research collaborations, evidenced by a co-authorship network spanning 272 institutions and 99.6 % of his papers being co-authored. These collaborations integrate expertise from mechanical engineering, materials science, energy policy, and computational sciences to deliver impactful technological solutions.
Thomas Hodgson serves as an Assistant Professor in the Department of Musicology and Music Industry at the University of California, Los Angeles. His interdisciplinary research bridges ethnomusicology, digital studies, and the global music industry, with concentrated focus on Pakistan, Kashmiri diaspora communities, and the Global South. Hodgson's scholarship pioneers the ethnomusicology of algorithms and artificial intelligence, examining how music streaming technologies flow from corporate platforms to local creative ecosystems. His current book project Journeys of Love: Kashmiris, Music, and the Poetics of Migration (University of Chicago Press) investigates music's role in shaping migration memories and belonging among Kashmiri musicians across Azad Kashmir, the UK, and Persian Gulf. As co-founder of the peer-reviewed journal Music and Data , he advances humanistic analysis of technological infrastructures in sound cultures. His scientific recognition includes: Hellman Fellow 2024-25 supporting tenure-track research at UCLA Shortlisting for the 2019 RMA Tippett Medal for the pandemic-response album Aenigmata Hodgson's Hellman Fellowship enables critical examination of power dynamics in music technology, while his industry engagement manifests through Tigmus—a data-driven platform optimizing performance opportunities for 4,000+ artists. His academic mentorship extends through curriculum development in music industry studies and ethnomusicology. Technological innovation and artistic practice converge in Hodgson's work through co-founding Tigmus (representing 900+ venues) and performing as trumpet/keyboards instrumentalist in Stornoway—the indie folk band behind three UK top-20 albums including recent release Dig the Mountain .
Sarma V. Pisupati is a Professor of Energy and Mineral Engineering and Chemical Engineering at Penn State University's College of Earth and Mineral Sciences. He holds the John T. Ryan, Jr. Faculty Fellowship and serves as Director of the Center for Critical Minerals (C2M) and co-director of the Coal Science and Technology Program at the EMS Energy Institute. With over forty years of experience in energy and environmental research and education, Dr. Pisupati established the first undergraduate Energy Engineering degree program in the US and led it through ABET accreditation. Dr. Pisupati earned his B.Tech. and M.Tech. in Chemical Engineering from Osmania University and IIT Kharagpur, respectively, followed by a Ph.D. in Fuel Science from Penn State University. Prior to his academic career, he worked in industry for five years, bringing practical experience to his research and teaching. Ph.D. (Fuel Science), The Pennsylvania State University M.Tech. (Chemical Engineering), Indian Institute of Technology B.Tech. (Chemical Engineering), Osmania University His research spans numerical modeling of combustion systems for emissions reduction, advanced power generation methods including oxy-fuel and chemical looping combustion, coal and biomass gasification processes, and the extraction of critical and rare earth elements from secondary sources like acid mine drainage and coal byproducts. His work addresses fundamental challenges in energy production while developing sustainable solutions for critical material supply chains. Analysis of Dr. Pisupati's recent publications reveals a strong focus on critical mineral recovery from unconventional sources, particularly acid mine drainage and coal byproducts. His work combines fundamental research on slag chemistry, ash behavior, and reaction mechanisms with practical applications for resource recovery and environmental remediation. This research trajectory reflects the growing importance of securing domestic supplies of critical materials essential for clean energy technologies. Dr. Pisupati has received numerous prestigious awards recognizing his contributions to engineering education and research: George W. Atherton Award for Excellence in Undergraduate Education (Penn State's highest teaching award) Elected Fellow of the American Chemical Society Elected Fellow of the Indian Institute of Chemical Engineers RA Mashelkar Medal for Innovators and Science Leaders Multiple Best Paper Awards from professional societies e-Education Faculty Fellowship for online teaching innovations As Principal Investigator or co-PI, Dr. Pisupati has secured approximately $10 million in research funding from diverse sources including the Department of Energy, industrial partners, and national laboratories. His current projects focus on critical mineral extraction from coal-based resources, acid mine drainage remediation, and advanced combustion technologies. He has mentored numerous students and postdoctoral researchers, contributing significantly to workforce development in energy and mineral engineering fields. Dr. Pisupati leads the Center for Critical Minerals, which focuses on developing innovative extraction methods for critical minerals from unconventional domestic sources. His work addresses national security concerns related to supply chain vulnerabilities for materials essential to clean energy technologies, defense applications, and advanced manufacturing.
Kangwei Xu is a researcher at the Chair of Design Automation (Lehrstuhl für Entwurfsautomatisierung) under Prof. Ulf Schlichtmann at the Technical University of Munich (TUM), actively advancing Electronic Design Automation through AI-driven methodologies. His core research interests include: Electronic Design Automation (EDA) High-Level Synthesis Machine Learning for EDA Neural Network Accelerators Timing Analysis Hardware Reliability Analysis of his 2024-2025 publications reveals a decisive trend in leveraging Large Language Models to revolutionize hardware design flows. Key innovations span automated C/C++ code refactoring (HLSRewriter), behavioral discrepancy testing (HLSTester), and neural network logic optimization, demonstrating how AI integration significantly enhances efficiency and accuracy in EDA toolchains while addressing longstanding challenges in synthesis and verification. Scientific Awards: No awards documented in available sources. Advising and Grants: Public records indicate no formal student advisement roles or individually attributed research grants; his work operates within the broader funded projects of TUM's Design Automation chair. Labs and Teams: Xu contributes to TUM's interdisciplinary Design Automation research group, which spans Analog EDA, Electronic System Level design, Emerging Technologies, Microfluidics, Optical NoC, Novel Microfabrication, Timing Analysis, Neural Networks and Accelerators, and Reliability, maintaining strong industry collaborations and cutting-edge experimental facilities.
Juan Antonio Leñero Bardallo is a Professor at the University of Seville, Faculty of Physics, Department of Electronics and Electromagnetism. His research focuses on bio-inspired microelectronics, event-driven vision sensors, and CMOS integration techniques. Research Group: MICROELECTRÓNICA ANALÓGICA Y DE SEÑAL MIXTA Key Projects: SAMANTA2 (robotic vision), CAVIAR (event-based vision), VULCANO (event-driven imaging) His work spans asynchronous image sensors, thermography for medical diagnostics, stacked diodes for energy harvesting, and neuromorphic engineering. Recent publications highlight low-power sun sensors, self-powered imaging systems, and thermographic applications in dermatology. He has contributed to books on analog electronics and radiation detection. Patents include solar position sensors and electron energy detectors for scanning electron microscopy. His teaching subjects cover experimental techniques, integrated sensor design, and bio-inspired algorithms.
Professor Peter Quinn is a distinguished astrophysicist at the University of Western Australia , serving as Chairman of the Board at the International Space Centre and affiliated with the International Centre for Radio Astronomy Research (ICRAR) and the Office of DVC Research . He received his BSc(Hons) in Mathematics and Physics from the University of Wollongong in 1978 with the University Medal in Physics, and his PhD in astronomy and astrophysics from the Australian National University (ANU) in 1982. His research centers on galaxy formation and evolution , dark matter dynamics , and the Epoch of Reionization . He has pioneered computational astrophysics, particularly through the discovery of the Quinn-Goodman effect and contributions to the MACHO Dark Matter Search Project . He has led major initiatives in the European Southern Observatory (ESO) , including the Very Large Telescope (VLT) data flow system and the Astrophysical Virtual Observatory (AVO) project. His scholarly work spans radio astronomy , supercomputer simulations , and data-intensive science , with a strong focus on the Square Kilometre Array (SKA) and gravitational wave detection . His work has earned him several prestigious accolades including a NASA High Performance Computing Award and a Computerworld 21st Century Achievement Award . He is a Fellow of the Australian Academy of Science (FASA) and a Fellow of the Australian Institute of Physics (FTSE) . His research also extends to large-scale international infrastructure projects and planning for the Square Kilometre Array and gravitational wave observations . He has served as Division Head at ESO and as a Chief Investigator for numerous grants, including the Australian SKA Regional Centre and ICRAR core funding .
Dr. Ioulia Bessa is an Associate Professor at the Leeds University Business School , specializing in flexible work arrangements, non-standard employment, and platform economy precarity. She holds a PhD from Bayes Business School, City University of London, and has been affiliated with the Centre for Employment Relations Innovation and Change (CERIC) since 2015. Research Focus: Labour market insecurity, mental health impacts of precarity, post-BREXIT and post-COVID-19 workforce dynamics, and platform economy protest patterns Key Grants: ESRC-Digital Futures at Work (8m£), International Labour Organisation projects, and Friedrich-Ebert-Stiftung research Supervision: Mentoring PhD students on topics including gender pay gaps, sickness absence management, and single Chinese professional women's work-life experiences External Engagement: Regular media contributor (Financial Times, The Telegraph, CIPD), Higher Education Fellow, and member of CYGNA Women in Academia Network Her work combines quantitative analysis of national/international datasets like UKHLS and European Working Conditions Survey with qualitative insights into worker wellbeing and organizational responses to economic transitions.
Professor Somchai Wongwises at King Mongkut's University of Technology Thonburi is a leading researcher in thermal engineering and fluid dynamics. His work focuses on advanced cooling systems, heat exchangers, and multiphase flow phenomena. Research trends from his recent publications highlight expertise in: microchannel heat sinks, nanofluid applications, two-phase flow modeling, and optimization of condensation heat transfer. Key innovations include dual-vapor thermosyphon designs and topology-optimized heat sinks for electronic cooling. His experimental and numerical studies span refrigeration systems, porous media integration in thermal collectors, and electrohydrodynamic flow simulations. Despite prolific contributions, no specific awards, student lists, or educational history are detailed in the provided data.
Idriss Dagal serves as an Assistant Professor at Beykent University's Department of Electrical and Electronics Engineering. With a PhD and Master's in Electrical Engineering from Yildiz Technical University (2015 and 2023 respectively), and additional academic credentials from Ethiopian Airlines Aviation University and Mongo Polytechnics University, his career bridges academic research with industry experience as a Sales Engineer. PhD: Yildiz Technical University (2015) Master's: Yildiz Technical University (2023), Ethiopian Airlines Aviation University (2008) Bachelor's: Mongo Polytechnics University (2006) His research focuses on renewable energy systems , particularly photovoltaic power optimization using metaheuristic algorithms (Hybrid PSO-Salp Swarm, Gray Wolf Optimization). He also explores control systems for solar energy and aircraft dynamics, including PID and fuzzy logic controllers. Additional work spans machine learning applications in energy and medical diagnostics, along with power electronics for battery charging. Recent publications highlight 15 2025 articles on topics like hybrid energy systems , AI-driven MPPT , and aircraft control frameworks . His work appears in journals such as Scientific Reports , IEEE Access , and International Journal of Aeronautical and Space Sciences . Teaching experience includes courses in Electrical Machines and Information Technologies . Non-university roles at Elektra Electronic Company and Aktif Group Company involved sales engineering, complementing his academic profile with industry insights.
