Tijay Chung is an Associate Professor at the College of Engineering , Virginia Tech , specializing in Internet Security and Internet Measurement . His work bridges theoretical and applied aspects of cybersecurity, focusing on secure communication protocols and infrastructure. Education Ph.D., Computer Science and Engineering, Seoul National University (2015) B.S., Computer Science and Engineering, Pohang University of Science and Technology (2009) Research Interests Chung's research centers on improving certificate revocation mechanisms, DNSSEC, and TLS security. He explores vulnerabilities in web encryption, develops decentralized cryptographic solutions, and analyzes internet governance protocols like BGP and RPKI. His work also extends to privacy in contact-tracing technologies and understanding content distribution dynamics in peer-to-peer systems. Recent publications highlight trends in : Enhancing TLS and DNSSEC operational security Decentralized cryptographic accumulators for revocation Longitudinal studies of PKI and certificate ecosystems Privacy guarantees in Bluetooth Low Energy (BLE) systems Advising No student names were explicitly listed in the provided materials.
Heikki Handroos is a Full Professor of Mechanical Engineering at LUT University, leading the Laboratory of Intelligent Machines since 1993. He holds a DSc (Technology) from Tampere University of Technology and has served as Vice-Dean of the Faculty of Technology (2007-2009) and currently chairs the Collegiate Body of LUT University. His research focuses on mechatronics, robotics, control systems, and fluid power, with over 300 publications and 2,400+ citations. He has supervised 34 doctoral theses and 150+ MSc projects, managed R&D projects exceeding €20M, and co-founded four tech startups. His work spans industrial collaborations, digital twin applications, and innovative robotics for nuclear energy (e.g., DEMO reactor maintenance systems). He has held visiting professorships in the U.S., Japan, and Russia, and actively contributes to academic editorial roles and professional societies like ASME and IEEE.
Dr. Anna Raffoni serves as a Senior Lecturer in Accounting and Finance at Loughborough Business School, Loughborough University, and holds the strategic role of Programme Lead for Social Science Research (Business and Management Studies). She joined the institution in January 2015 after accumulating academic experience at the University of East Anglia, Cranfield University School of Management, and the University of Bologna, establishing herself as a key contributor to the Accounting and Finance research group. Her academic foundation includes a PhD in Management Accounting (specializing in customer value management) awarded by the University of Florence in 2009, which continues to inform her interdisciplinary research trajectory. Raffoni's scholarly work centers on performance management, business analytics, and strategic management accounting, with publications appearing in premier journals including the European Journal of Operational Research, British Accounting Review, Production, Planning & Control, and Omega. Her research uniquely bridges quantitative operations research methods with accounting frameworks, particularly examining how data analytics transforms traditional performance measurement in banking and service sectors through techniques like machine learning and data envelopment analysis. Analysis of her 15 most recent publications (2012-2024) reveals a clear evolution toward integrating advanced analytics with performance management systems. She has pioneered multidimensional efficiency measurement in banking branches, explored total cost of ownership in supply chains, and investigated strategic performance measurement adoption, consistently demonstrating how operational research methods solve real-world accounting challenges while advancing theoretical models. Her scientific recognition features the Dean’s Award for Early Career Teacher of the Year (2017), acknowledging her excellence in undergraduate and postgraduate instruction. In her capacity as Programme Lead, Raffoni shapes research strategy and supports faculty development across Business and Management Studies. While specific supervisees and grant details aren't documented in available materials, her leadership role and active publication record indicate substantial engagement in research mentorship and academic community building. She actively collaborates within Loughborough's Accounting and Finance research group, contributing to interdisciplinary projects that address contemporary challenges in financial management through analytical approaches, with emerging work suggesting increasing focus on artificial intelligence applications in performance systems.
Elsa A. Olivetti is the Jerry McAfee (1940) Professor in Engineering and Professor of Materials Science and Engineering at MIT, and a MacVicar Faculty Fellow. She leads the Olivetti Group, focusing on sustainable materials design, recycling strategies, and computational models for environmental and economic impact assessment. Her work bridges materials science with sustainability, emphasizing circular economy principles and decarbonization. Education: B.S. in Engineering Science from University of Virginia (2000); Ph.D. in Materials Science and Engineering from MIT (2007). Her doctoral research centered on lithium-ion battery electrode materials. She joined MIT’s Department of Materials Science and Engineering (DMSE) in 2014 as an Assistant Professor, later advancing to full Professor. She co-directs the MIT Climate & Sustainability Consortium and chairs the MIT Climate Nucleus. Research interests include: sustainable materials systems, recycling-friendly material design, waste mining, and AI-driven materials discovery. She develops models for cost prediction, environmental impact analysis, and policy-relevant supply chain dynamics. Notable contributions include high-throughput zeolite design and battery recycling frameworks. Awards include the Bose Teaching Award (2021), NSF Early Career Award (2018), and Minerals, Metals & Materials Society Early Career Fellowship (2019). Her work emphasizes education and curriculum development, including courses for MIT’s Climate Scholars program. Labs/Teams: Olivetti Group (MIT), MIT Climate & Sustainability Consortium. Active in global sustainability initiatives, focusing on materials for energy transition and climate resilience.
Christopher J. Stein is an Associate Professor of Theoretical Chemistry at the Technical University of Munich (TUM), part of the TUM School of Natural Sciences. His research focuses on theoretical (electro-)catalysis, developing electronic-structure models and solvation/embedding methods to understand and optimize catalytic processes. He leads the Stein Group, which integrates computational chemistry with high-throughput simulations to advance energy materials and battery technologies. His work emphasizes realistic modeling of catalyst behavior under operational conditions and has contributed to advancements in quantum embedding and automated reaction mechanism exploration. Education and Career: Earned his PhD in Theoretical Chemistry, with postdoctoral research at Caltech (2017-2020). Became an Associate Professor at TU Munich in 2023. He previously held roles at Karlsruhe Institute of Technology and contributed to projects like the BIG-MAP Materials Acceleration Platform. Research Interests: Theoretical chemistry, electrochemical interfaces, battery materials, high-throughput computational methods, and machine learning integration. His group explores topics like solid electrolyte interphases, charge transfer mechanisms, and automated workflows for materials discovery. Awards: While no explicit awards are listed, his contributions to materials acceleration platforms and theoretical catalysis have been widely recognized in the field. His work has been featured in journals like Journal of Chemical Physics , Chemical Science , and Angewandte Chemie . Labs/Teams: Leads the Stein Group at TUM, collaborating with institutions like the Munich Data Science Institute and MIRMI. His lab focuses on computational tools for accelerating energy material development, including quantum embedding and cloud-based simulations.
Helena Roco Taboada is an Interim Lecturer in the Department of Pharmacology, Pharmacy and Pharmaceutical Technology at the University of Santiago de Compostela. She holds a PhD from the same institution for her thesis on 'Quality-by-design approach for the development of lipid-based nanosystems for anti-mycobacterial therapy' (2021), supervised by Dr. Mariana Landín Pérez and Dr. Carmen Remuñán López. She is affiliated with the Faculty of Sciences and is part of the Strategic Grouping in Materials (AEMAT) and the ID-FARMA research group focusing on dosage forms and drug release systems. Her research interests center on pharmaceutical technology, drug delivery systems, and nanomedicine, with a focus on applications in anti-mycobacterial therapy, osteoporosis treatment, and bone regeneration. Her work integrates lipid-based nanosystems, targeted drug delivery, and AI-driven formulation strategies. Recent projects include developing lipid nanoparticles for clofazimine delivery and thermosensitive hydrogels for osteoarthritis management. Her publications span topics like nanoparticle functionalization, cryoprotectant optimization in lyophilization, and AI tools for nanostructured lipid carrier design. She is active in interdisciplinary collaborations within materials science and biomedical engineering.
Mitra Taheri is a Professor in the Department of Materials Science and Engineering at Johns Hopkins University, serving as Director of the Materials Characterization and Processing (MCP) facility and a member of the Hopkins Extreme Materials Institute. She holds affiliations with the Pacific Northwest National Laboratory and the Ralph O’Connor Sustainable Energy Institute. Her research focuses on electron microscopy, particularly in-situ and operando techniques, combined with artificial intelligence to study materials under extreme conditions (e.g., high temperatures, radiation, and oxidation). She aims to accelerate materials discovery by integrating AI with microscopy for real-time analysis. Dr. Taheri earned her BS, MSE, and PhD in Materials Science and Engineering from Carnegie Mellon University. Her work spans corrosion-resistant alloys, additive manufacturing, quantum materials, and biomaterials. Research sponsors include PNNL, JHU, NSF, ARPA-E, and ONR. She leads the Dynamic Characterization Group (DCG), which develops autonomous platforms for materials analysis and explores applications in energy, aerospace, and medical systems. Key research areas include: Design of corrosion-resistant multi-principal element alloys AI-driven microscopy for real-time material behavior insights Additive manufacturing of soft magnetic composites for electric vehicles Biomedical hydrogels for tissue engineering Her team develops novel materials and tools to probe structural, functional, and biological systems across scales, with an emphasis on sustainability and extreme environment applications.
Ram Samudrala is a Professor and Chief of the Division of Bioinformatics at the University at Buffalo Jacobs School of Medicine and Biomedical Sciences . His research focuses on multiscale computational biology , integrating protein structure prediction , drug discovery , and translational science to address medical challenges. He leads the development of the CANDO platform for therapeutic drug discovery and co-directs the Informatics Core at the Clinical and Translational Sciences Institute. PhD in Computational Biology (University of Maryland, 1997) BA in Computing Science and Genetics (Ohio Wesleyan University, 1993) Postdoctoral Fellowship in Protein Folding (Stanford University, 1997-2001) His work spans structural biology , genomics , and computational drug design , with applications in dentistry , infectious diseases , and cancer . He has received prestigious awards including the NIH Director's Pioneer Award (2010) and multiple Wiki Science Prizes . Samudrala's group collaborates globally, emphasizing in silico methods followed by in vitro and in vivo validation. Key grants include $1.22M NIH NCATS ASPIRE Reduction-to-Practice Award and $4.5M NIH/NLM BRIGHT Training Grant . 2023 Finalist, Clinical and Translational Sciences Institute Clinical Research Achievement Awards 2016 MacArthur Foundation 100&Change Top 50 2008 Alberta Heritage Foundation Visiting Scientist Award 2005 NSF CAREER Award He directs the BRIGHT Short-Term Training Program and serves on multiple editorial boards and review panels. Samudrala's group maintains a Protinfo web server for structural predictions and the Bioverse framework for systems-level analyses.
Dr. Huadong Mo is a Senior Lecturer at the School of Systems and Computing, University of New South Wales (UNSW) Canberra, Australia. He holds a B.E. degree in automation from the University of Science and Technology of China (2012) and a Ph.D. in systems engineering and engineering management from the City University of Hong Kong (2016). Prior to his current position, he was a research associate at ETH Zurich's Reliability and Risk Engineering Lab (2016-2019) and a Lecturer at UNSW Canberra (2019-2021). Dr. Mo's educational background includes a strong foundation in systems engineering with international experience across China, Switzerland, and Australia. His career trajectory demonstrates a progression from academic research to faculty positions with increasing responsibilities in teaching and research leadership. His research focuses on enhancing the resilience, performance, and security of complex systems using learning-based algorithms, primarily in power and energy systems, cyber-physical systems, and manufacturing systems. He applies data analytics to understand system evolution under uncertainties, with particular emphasis on prognostics and health management, sustainable transportation, robust operation of power systems under extreme events, and reinforcement learning-based asset management. His work bridges theoretical advances with practical applications in critical infrastructure. Analysis of Dr. Mo's recent publications reveals a strong focus on energy systems, particularly in the integration of machine learning with power grid management, battery storage systems, and resilience against cyber threats. His research shows a clear trajectory toward increasingly complex system integration, with growing emphasis on multi-vector energy communities, cross-domain prediction, and uncertainty-aware energy management. The interdisciplinary nature of his work spans electrical engineering, computer science, and operations research. 2024 IEEE SMC Early Career Award 2023 Visiting Research Fellowship (Jean d'Alembert Pour Fellowship) Gold Medal in 2024 China International College Student Innovation Competition (as supervisor) Arc PGC Supervisor Award (2021) IEEE SMC Outstanding Chapter Award (2021) Alumni Achievement Award from City University of Hong Kong (2019) Dr. Mo actively supervises numerous HDR students working on cutting-edge research topics including battery health monitoring, quantum control, reinforcement learning for power systems, and explainable AI for energy management. He leads multiple significant research grants totaling over 3 million AUD, including projects funded by ARC, Energy Innovation Fund, and international collaborations with institutions like ETH Zurich, Cambridge, and Tsinghua University. His research group maintains strong international connections, facilitating student exchanges and collaborative research. As Postgraduate Course Coordinator of Systems Engineering and Chair of IEEE SMC ACT Chapter, Dr. Mo plays a significant role in academic leadership and professional community building. His research team collaborates with industry partners on practical implementations of their theoretical work, particularly in the energy sector.
Dr. Anna Baldycheva is a Senior Lecturer in Electronic Engineering at the University of Exeter, within the College of Engineering, Mathematics and Physical Sciences. She leads the interdisciplinary STEMM Laboratory, focusing on applied R&D in smart materials, photonics, AI, and IoT. With prior research experience at MIT, Trinity College Dublin, and Tyndall National Institute, she has established herself as an internationally recognized innovator and entrepreneur in emerging technologies. PhD in Electronic and Electrical Engineering, Trinity College Dublin (2008–2012) BSc (Hons) in Physics, St. Petersburg State University (2003–2008) Postgraduate Certificate in Academic Practice, University of Exeter (2016–2017) Postgraduate Certificate in Technology Management, Smurfit Business School (2009–2010) Her research spans Nano-Engineering, Opto-Electronics, Photonics, AI, and IoT , with a strong emphasis on real-world applications. She pioneers work in fluid opto-electronics , graphene nanocoatings , and AI-driven emotion recognition and early cancer detection . Her lab develops smart composite materials for flexible electronics, e-textiles, and structural applications, integrating machine learning into healthcare, education, and communications systems. The recent publications highlight a strong trend toward applied interdisciplinary innovation , combining materials science with AI and photonics for healthcare diagnostics, energy-efficient computing, and educational technology. Her work frequently bridges fundamental physics with commercialization potential, as seen in spin-out technologies like GSurf and the Electronic-Nose for lung cancer detection. Fellow, Royal Microscopical Society (RMS) Fellow, Higher Education Academy (FHEA) Expert, Future and Emerging Technologies, European Commission Featured in Forbes and Forbes Tech Council Editor-in-Chief, InSTEMM Journal Associate Editor, Nature Scientific Reports and Discover Nano Trustee, Royal Microscopical Society Founder, STEMM Global Scientific Society Founder, It’s Her! Women in STEMM Initiative Dr. Baldycheva actively supervises PhD students and has secured industrial collaborations with organizations such as Qinetiq and Lumentum. She leads multiple outreach initiatives, including STEMM Junior for underprivileged children, and serves on the committee for the Jocelyn Bell Brunel PhD Scholarship. She has raised significant research funding through national and international grants, though specific grant names are not listed. She leads the STEMM Laboratory , a multidisciplinary research group with divisions in Smart Composite Materials, Machine Learning & AI, and Opto-Electronics & Photonics. The lab emphasizes industry collaboration and technology transfer, having produced a university spin-out (GSurf) and multiple media-highlighted innovations.
Prof. Dr. Jörg Hackermüller is a computational biologist with expertise in Omics data integration Toxicology Environmental risk assessment Non-coding RNA biology . He serves as Head of the Department of Computational Biology and Chemistry at the Helmholtz Centre for Environmental Research (UFZ) since 2024 and holds a Professorship at the Faculty of Mathematics and Computer Science at Leipzig University since 2021. His research focuses on Developing AI methods for chemical toxicity prediction Multi-omics integration for mechanistic toxicology Data standardization in environmental monitoring Non-coding RNAs as biomarkers in disease and toxicity and has produced 15+ recent publications spanning tools like multiGSEA and deepFPlearn+ . He collaborates with teams across UFZ Leipzig University Novartis Fraunhofer Institute and leads projects like InCeTo and SafePol , integrating exposome research with systems biology.
A. Asadi is an Assistant Professor at the Faculty of Electrical Engineering, Mathematics and Computer Science at TU Delft. He leads the Wireless Communication and Sensing (WISE) Lab within the Embedded Systems Group, focusing on the integration of wireless communication and sensing systems for Beyond-5G and 6G networks. His research leverages machine learning to develop practical solutions for next-generation wireless networks, with strong industrial collaborations from companies such as Nokia, NEC, and National Instruments. Research Themes : Wireless Sensing, 6G Networks, Physical Layer Security, Reconfigurable Intelligent Surfaces (RIS), mmWave Communication Key Collaborations : Industry partnerships with Nokia, National Instruments, and NEC Recent research outputs highlight his work on Reconfigurable Intelligent Surfaces (RIS) for 6G systems, including liquid crystal-based designs for fast beam switching and temperature compensation. His publications emphasize practical implementations in mmWave communication, security protocols, and experimental validation. Scientific Awards : Athene Young Investigator Prize (2017) Educational Fellowship (2025) Asadi contributes to the academic community through committee roles at major conferences like IEEE INFOCOM , IEEE ICNP , and ACM CoNEXT , and his work on D2D communication has been cited as an ESI highly cited paper.
Devin K. Harris is a Professor and Chair of the Department of Civil and Environmental Engineering at the University of Virginia . His work focuses on large-scale infrastructure systems , combining image-based measurement techniques, simulation , visualization , and data analytics to advance structural health monitoring , smart cities , and digital twins . He also investigates reinforced/prestressed concrete behavior and innovative materials in civil infrastructure. Education : Ph.D., M.S., and B.S. in Civil Engineering from Virginia Tech (2007), Virginia Tech (2004), and University of Florida (1999). Research Interests Structures and Mechanics - Sustainable Infrastructure Systems Infrastructure Condition Assessment Structural Health Monitoring Smart Cities Digital Twins Applied Machine Learning Scientific Awards Delmar L. Bloem Distinguished Service Award (2021) IAspire Leadership Academy Fellow (2020–2022) ASCE Journal of Bridge Engineering Outstanding Reviewer (2013) UVA Teaching Resource Center Excellence in Diversity Fellowship (2012–2013) ACI Young Member Award for Professional Achievement (2011) Grants Principal Investigator for EAGER: Adaptive Digital Twinning: An Immersive Visualization Framework for Structural Cyber-Physical Systems (NSF #2136724) and Performance Characteristics of In-Service Bridges (Virginia Transportation Research Council, 2018–2020). Co-led NCHRP 23-16 on Machine Learning applications in transportation agencies. Labs & Teams Leads the Infrastructure Simulation, Sensing and Evaluation Lab (I-S2EE) , equipped with DIC systems , mobile GPR , thermal imaging , and cyber-physical simulation tools. Collaborates with the Omni-Reality & Cognition Lab for AR/VR integration in infrastructure evaluation.
Dr. Ali Kashani is a Senior Lecturer at the University of New South Wales (UNSW) within the School of Civil and Environmental Engineering. His research focuses on sustainable and low-carbon concrete materials, robot-aided construction (particularly 3D printing), and Circular Economy-aligned applications. Leadership in cementitious materials innovation Expertise in 3D printing for construction Advocate for waste valorisation and carbon capture Dr. Kashani has secured approximately $7 million in research funding and holds a patent in lightweight concrete foam. His work spans 70+ publications with 9,000+ citations, including media coverage in the Sydney Morning Herald and The Fifth Estate. He actively contributes to professional organizations such as MECLA, RILEM, and ASTM. Recent research trends include AI and optimization algorithms for sustainable concrete mix design, chloride diffusion modeling, and 3D printing performance analysis. His publications often address waste material integration, durability assessment, and eco-friendly construction practices. Scientific Awards: National and NSW Awards for 'Excellence in Concrete' (Technology and Innovation) from the Concrete Institute of Australia Churchill Fellowship for Digital Construction and 3D Printing sponsored by AVJennings Dr. Kashani serves as Co-Chair of the cement and concrete working group at MECLA and contributes to RILEM and ASTM committees. His email is ali.kashani@unsw.edu.au , and his office is located in the Civil Engineering Building (H20), Level 2, Room CE204, UNSW.
Assoc. Prof. Dr. Yusuf Yaşa is an Associate Professor at Istanbul Technical University, Department of Electrical Engineering, specializing in Electrical Machines, Power Electronics, and Hybrid/Electric Vehicles. He holds a PhD from Yıldız Technical University and has served in academic and administrative roles at Bursa Technical University and Istanbul Technical University. PhD in Electrical Machines and Power Electronics, Yıldız Technical University (2006–2013) Current Vice Dean at Istanbul Technical University (2023–) Founding Partner of Yasa Motor Technologies (2018) and Nardan Power Conversion Systems Ltd. Co. (2023) His research focuses on noise mitigation in switched reluctance machines, battery cooling with graphene-enhanced phase change materials, and efficiency optimization in electric vehicle systems. He has led projects on DC fast-chargers and sensorless control of synchronous reluctance motors. His publications address energy conversion, battery management, and acoustic noise reduction. Recent research trends include advancements in electric vehicle modeling, state-of-charge estimation for Li-ion batteries, and thermal management solutions for battery systems. His work integrates simulation tools like ANSYS and machine learning for efficiency improvements. He has advised PhD and Master’s theses on topics such as battery charge rate estimation, graphene-doped PCM materials, and Kalman filter-based motor control. Collaborations span institutions like The University of Akron and companies in electric propulsion and robotics.
