Vittorio Solina is a Researcher at the Department of Mechanical, Energy and Management Engineering (DIMEG) of the University of Calabria, specializing in industrial systems simulation and digital twin technologies. His work spans Industry 4.0/5.0 applications, supply chain optimization, and human-robot collaboration. Affiliation: University of Calabria Academic Role: Researcher (Legge 240/10) Research Focus: Digital twins, simulation modeling, sustainable manufacturing His research emphasizes advanced simulation tools for decision support, including applications in Industry 4.0 , Smart Manufacturing , and Agri-Food Supply Chains . Recent work explores adaptive simulation optimization for Industry 5.0 and 5G-enabled robotics. Key publication trends include: (1) Digital twin integration for supply chain resilience (2024-2025), (2) Simulation automation methodologies (2025), and (3) Human-robot collaboration frameworks (2024).
Matthew Louis Mauriello is an Assistant Professor in the Department of Computer and Information Sciences at the University of Delaware , where he directs the Sensify Lab . He holds a PhD in Computer Science from the University of Maryland (2018) and completed postdoctoral work at Stanford University (School of Medicine, 2020; School of Public Policy & Environmental Engineering Department, 2019). Research interests span Human-Computer Interaction (HCI), Ubiquitous Computing, and User-Centered Design with applications in: Sustainability Human-Building Interaction Wearable Technology Personal Informatics Educational Game Design Mental Health Interventions Recent publications highlight trends in stress monitoring (skin-like biosensors, workplace wellbeing), energy auditing (thermography systems), and educational technology (block-based programming tools for teachers). His work appears in ACM CHI, ACM Human-Computer Interaction, and Building and Environment. Scientific awards include: Best Paper Honorable Mention, CHI 2016 Best Paper Honorable Mention, CHI 2015 Best of WebSci'18 Teaching at University of Delaware encompasses courses like Educational Game Design Operating Systems Advanced Web Technologies Computing for Social Good with a focus on project-based learning and systems thinking.
Dawn Song is a Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley, affiliated with multiple research centers including the Berkeley Artificial Intelligence Research Lab (BAIR) and the Berkeley Center for Responsible, Decentralized Intelligence (RDI). She holds leadership roles in AI safety, cybersecurity, and blockchain research. Her work bridges machine learning, security, and distributed systems, with notable contributions to formal verification, privacy-preserving technologies, and AI governance. Education: Ph.D. (2002) and M.S. (1999) in Computer Science from UC Berkeley and Carnegie Mellon University, respectively. She previously served as an Assistant Professor at Carnegie Mellon University before joining UC Berkeley in 2007. Research Interests: Dawn's work focuses on AI safety, cybersecurity, and the ethical implications of frontier AI. She explores topics such as large language model vulnerabilities, zero-knowledge proofs, blockchain security, and policy frameworks for AI governance. Her research combines theoretical rigor with practical applications, addressing challenges in secure systems, adversarial machine learning, and privacy-preserving computation. Publications: Her recent work includes groundbreaking studies on LLM memorization, smart contract decompilation, and AI agent cybersecurity evaluation. She also leads initiatives like the Singapore Consensus and California Report on AI safety priorities, emphasizing global collaboration in risk mitigation. Notable Awards: MacArthur Fellowship (2010), ACM Fellow (2019), IEEE Fellow (2019) Advising & Grants: She advises projects on AI policy and cybersecurity, securing grants from NSF, DARPA, and industry collaborations. Her lab develops tools like CyberGym for evaluating AI agents and zkPyTorch for secure machine learning. Labs & Teams: Her research groups at UC Berkeley focus on cutting-edge projects in AI safety, blockchain, and cybersecurity, collaborating with industry leaders and policymakers to advance both technical and ethical standards.
Christina Antonie Reh is a Lecturer at the Lucerne School of Business (HSLU), affiliated with the Institute of Communication and Marketing (IKM MM). Her roles include academic teaching and research in digital marketing and sustainability. She holds a PhD from WHU - Otto Beisheim School of Management and has professional experience in data science and marketing at companies like LOréal and SevenVentures. Education: PhD (tbc 2024), WHU; M.Sc. (2016), LMU Munich; B.Sc. (2013), LMU Munich Her research focuses on digital marketing effectiveness , sustainability in advertising , and consumer behavior . Notable projects include studies on long-term brand equity and sustainable product messaging. Recent work explores the impact of climate pledges on consumer trust. Publications highlight her contributions to media measurement modeling and online coupon strategies. Key awards include the Amazon Research Awards (ARA 2023) and MassChallenge recognition (2024). Advising: No formal students listed; however, co-founded baybies GmbH and Aiko Pet Foods GmbH. Grants: $28,000+ from Amazon Research Awards. Labs/Teams: Co-founder of startups baybies and Aiko Pet Foods, focusing on sustainable consumer products and pet food innovation.
Prof. Hedan Bai is an Assistant Professor at the Department of Materials, ETH Zürich, specializing in robotics materials, bio-inspired systems, and soft robotics. Their research focuses on developing advanced materials for sensing, energy-efficient systems, and biomedical applications. Notable projects include the SmartSuit architecture for space exploration and self-healing optical sensors for soft robots. Research interests span bioelectronics, stretchable sensors, haptic interfaces, and biomimetic materials. Bai's work integrates material science with robotics to create adaptive, sustainable, and intelligent systems. Key areas include wireless implants for neuromodulation, environmental-responsive textiles, and energy-harvesting devices. Publications highlight innovations in optical waveguides, self-healing materials, and wearable technologies. Their interdisciplinary approach bridges robotics, biomedical engineering, and aerospace applications. No formal awards are listed, but contributions to next-gen materials for robotics are prominent. Advising and grants are not detailed in the text, but Bai's lab focuses on projects like SmartSuit for extravehicular activities and synthetic afferent neural networks. Collaborations likely involve aerospace and biomedical sectors.
Sheng Shen is a Professor in the Mechanical Engineering Department at Carnegie Mellon University (CMU) , with courtesy appointments in the Departments of Electrical and Computer Engineering and Materials Science and Engineering . He earned his Ph.D. in Mechanical Engineering (Minor in Electrical Engineering) from Massachusetts Institute of Technology (MIT) , and his B.S. and M.S. from Huazhong University of Science and Technology in China. Prior to joining CMU in 2011, he conducted postdoctoral research at UC-Berkeley . Education: Ph.D., Mechanical Engineering, MIT (2010) B.S. & M.S., Power Engineering & Engineering Thermophysics, Huazhong University of Science and Technology (2000 & 2003) Research interests include nanophotonics , nanoscale energy transport and conversion , nanofabrication , and advanced manufacturing , with applications in thermal management , light sources and devices , thermal emission control , solar energy conversion , infrared sensing , and multifunctional materials . His work leverages interdisciplinary expertise in thermal and optical measurements , material synthesis , device fabrication , and theoretical modeling . Recent publications highlight advancements in infrared radiation control , thermal interface materials , metasurface engineering , and graphene-based nanosystems . His scientific awards include: NSF CAREER Award DARPA Director's Fellowship DARPA Young Faculty Award Elsevier/JQSRT Raymond Viskanta Award CMU Dean's Early Career Fellowship Philomathia Foundation Research Fellowship Hewlett-Packard Best Paper Award Best Paper Award, Julius Springer Forum Advising spans Ph.D. and postdoctoral researchers in nanoscale energy systems, with alumni contributing to solar energy conversion , infrared sensing , and flexible electronics . His lab receives funding from ARL, DARPA, DOE, DTRA, NASA, NSF, and ONR , and recently secured a DURIP award for instrumentation.
Prof. Walter Leal Filho is a distinguished academic and researcher holding professorial positions at Hamburg University of Applied Sciences (Germany) and Manchester Metropolitan University (UK). He is the founding director of the European School of Sustainability Science and Research (ESSSR) and the Inter-University Sustainable Development Research Programme (IUSDRP). With over 30 years of editorial experience, he has authored over 500 publications, focusing on sustainability, climate change, and environmental management. His research interests span Climate Change, Urban Resilience, Natural Resource Management, and Sustainability Education. He emphasizes interdisciplinary approaches to address global challenges, such as space debris mitigation and bio-based materials for sustainable packaging. His work bridges policy, education, and practical solutions for sustainable development. Prof. Leal Filho’s recent articles highlight trends in sustainable urban planning, space sustainability, and ecosystem conservation in the Amazon. He has been recognized as a Top Cited Scholar 2024, reflecting his impactful contributions. With 1,200+ co-authors and a global network, he collaborates widely, fostering international research and education initiatives. As director of ESSSR and IUSDRP, he leads programs advancing sustainability science and interdisciplinary research. His academic leadership and prolific publications underscore his role as a pivotal figure in global sustainability efforts.
Bobak Mortazavi is an Associate Professor in the Department of Computer Science & Engineering at Texas A&M University. His research focuses on medical analytics, machine learning, wearable sensors, and cyber-physical systems. He leads interdisciplinary projects in healthcare technology, including AI-driven diagnostics and predictive modeling for cardiovascular diseases. He has received notable awards such as the Best Demonstration Award at IEEE EMBS 2012 and the Best Paper Award at the Fourth International Conference on Data Analytics 2015. His work bridges machine learning with clinical applications, emphasizing practical solutions for healthcare challenges. Recent research includes developing AI tools for aortic stenosis detection, electrolyte estimation via ECG, and real-time patient monitoring systems. He collaborates with industry and academic partners to advance telemedicine and wearable health technologies. Key contributions include the SMART-LV project for smartphone-based cardiac diagnostics and the ArterialNet framework for blood pressure reconstruction using wearable sensors. His work is published in top journals like IEEE Journal of Biomedical and Health Informatics and Elsevier's Pervasive and Mobile Computing.
Shweta Shinde is an Assistant Professor in the Department of Computer Science at ETH Zurich where she leads the Secure & Trustworthy Systems (SECTRS) research group. She is also a member of the Institute of Information Security and the ZISC Center at ETH Zurich. Her work bridges theoretical foundations with practical implementations in hardware and system security. Dr. Shinde's research focuses on the intersection of trusted computing, system security, and program analysis. Her group investigates both foundational aspects of security to protect phones, servers, and accelerators, as well as practical aspects of realizing these solutions through large-scale system building. Her work spans hardware security primitives, trusted execution environments, confidential computing, and secure system design across multiple platforms including mobile devices, cloud infrastructure, and blockchain systems. Her publication record demonstrates significant impact in the field, with numerous papers in top security venues including IEEE S&P, USENIX Security, CCS, and NDSS. Her research has uncovered critical vulnerabilities in major hardware security technologies like Intel SGX and AMD SEV-SNP while also proposing novel frameworks for building more secure systems. The work spans multiple domains including hardware security, cloud security, mobile security, and blockchain security, with a consistent thread of identifying and addressing fundamental security challenges in trusted computing. Among her notable achievements are multiple best paper awards including at SysTEX 2025 and nominations at DATE 2025, a Distinguished Paper Award at IEEE S&P 2024, and recognition as a Most Innovative Research Pwnie Award Nominee in 2024. Her work on WeSee received particular attention for breaking AMD SEV-SNP through novel interrupt-based attacks. Dr. Shinde actively mentors PhD students including Mark Kuhne, Supraja Sridhara, Mélisande Zonta-Roudes, Benedict Schlüter, Andrin Bertschi, and others. She teaches courses on Systems Security, Information Security Lab, Seminar on Systems Security, and Current Topics in Information Security at ETH Zurich. Her service to the community includes extensive program committee work for major security conferences including Oakland (S&P), NDSS, USENIX Security, and CCS, where she has served as track co-chair and program co-chair for several workshops.
Blase Ur is an Associate Professor of Computer Science at the University of Chicago, leading the UChicago SUPERgroup (Security, Usability, & Privacy Education & Research group). His research focuses on data-driven methods to improve online security, privacy, and usability of complex systems. He holds a PhD from Carnegie Mellon University and an AB from Harvard University. Education: PhD in Societal Computing, Carnegie Mellon University (2016) AB in Computer Science, Harvard University Research Interests: Blase's work spans computer security, privacy, HCI, and ethical AI. He develops tools like password meters, privacy transparency systems, and IoT security solutions. His SUPERgroup emphasizes interdisciplinary collaboration, with projects addressing data-driven decision-making and usability challenges in AI and IoT. Articles Trends: Recent work includes studies on ad transparency systems, user perceptions of privacy in AI, and barriers to passwordless authentication. Research often combines empirical user studies with technical implementations to bridge gaps between security mechanisms and user needs. Awards: NSF CAREER Award (2021) Quantrell Award for Teaching (2021) SIGCHI Outstanding Dissertation Award (2018) Advising & Grants: Advisor to PhD students like Kevin Bryson. Secured grants from NSF, Mozilla, and Meta. Active in outreach to broaden CS participation, including K-12 programs. Labs & Teams: Co-director of the SUPERgroup and affiliated with the Systems Group and CERES Center for Unstoppable Computing at UChicago.
Lutz Schubert is a researcher at the Institute of Computer Science , University of Cologne. He focuses on efficient distributed and parallel execution environments for heterogeneous systems, notably the MyThOS operating system in collaboration with Brandenburg University of Technology, Cottbus-Senftenberg. His interdisciplinary work bridges computer science and digital archaeology , addressing modeling of non-deterministic events from sparse excavation data and exploring human behavior constraints in archaeological contexts. Research Interests Design of modular, scalable operating systems for distributed systems Optimization of execution environments for heterogeneous hardware Application of complex systems modeling to digital archaeology Statistical and probabilistic methods for archaeological interpretation Autonomic resource distribution and adaptation in computing Publication Trends : His work spans operating systems , parallel computing , and digital humanities , with recent emphasis on probabilistic reasoning in archaeology and adaptive OS design for multicore architectures. Labs & Collaborations : He collaborates with Brandenburg University of Technology on MyThOS and leads research in computational archaeology as chair of Computer Applications and Quantitative Methods in Archaeology (CAA) , Germany.
Anette Mikes is an Associate Professor of Accounting at the University of Oxford’s Saïd Business School and a Hertford College Fellow. She specializes in risk management, corporate governance, and sustainability, with a focus on the intersection of ethics and organizational control systems. Her research explores how risk frameworks shape corporate decision-making, particularly in climate change and decarbonization contexts. Education: PhD in Accounting from the London School of Economics (2005) Pre-doctoral work in the City of London (2006–2007) studying Chief Risk Officer roles Research Interests: Behavioral approaches to risk management Management control systems for sustainability Ethics in corporate governance Decarbonization strategies in heavy industries Her 2012 Harvard Business Review article (with Robert Kaplan) on risk frameworks remains influential, while her documentary on the Kursk submarine disaster highlights crisis management failures. Awards: 2025 Honorary Doctorate from Uppsala University 2017 ACA Prize for Risk Management Contributions 2014 Global Risk Forum Film Award Key Contributions: Co-developed Harvard’s Risk Management executive program Leads research on ‘Values at Risk’ and corporate purpose Published widely on climate risk governance and ethical leadership Her recent work emphasizes decarbonization strategies and moral accountability in business, bridging accounting practices with environmental and ethical imperatives.
Halil Ali is a Lecturer in Data Science (Education Focused) at the School of Computing Technologies, RMIT University. His research spans privacy-preserving machine learning, blockchain technologies, and cybersecurity. Key research areas include federated learning , quantum-enhanced AI , secure biometrics , edge unlearning , and privacy in healthcare data . His recent publications focus on resilient AI systems , blockchain applications , and ethical data handling in emerging technologies. His work demonstrates expertise in integrating machine learning with blockchain security across domains like IoT, smart grids, and metaverse healthcare. He contributes to practical frameworks for zero-trust architectures , lightweight consensus protocols , and quantum-classical hybrid models .
Gary Fedder is the Howard M. Wilkoff Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU), with courtesy appointments in Biomedical Engineering, Mechanical Engineering, and Robotics. He serves as Faculty Director of the Manufacturing Futures Institute (MFI) and previously held roles such as Vice Provost for Research and Interim CEO of the Advanced Robotics for Manufacturing (ARM) Institute. Fedder’s research focuses on MEMS, advanced manufacturing, and implantable microsystems. He earned his B.S., M.S., and Ph.D. in EECS from MIT and UC Berkeley, respectively. Education: Ph.D., Electrical Engineering and Computer Science, UC Berkeley (1994) M.S., Electrical Engineering and Computer Science, MIT (1984) B.S., Electrical Engineering and Computer Science, MIT (1982) Research Interests: Microelectromechanical systems (MEMS), digital twins, aerosol jet printing, stretchable electronics, and manufacturing innovation. His work integrates MEMS with CMOS processes, emphasizing low-cost, high-performance systems. Key Contributions: Co-founded the ARM Institute; developed MEMS-based sensors and actuators; pioneered methods for manufacturing innovation through projects like America Makes. His research spans over 300 publications and 21 patents. Awards: IEEE Fellow (2007), Ross Tucker Award (1993), NSF CAREER Award (1996), and leadership roles in Manufacturing USA initiatives. Leadership & Outreach: Directed the Institute for Complex Engineered Systems and led national initiatives to advance U.S. manufacturing competitiveness. Active in editorial roles for journals like IoP Journal of Micromechanics .
Dr. Amin Keramati is an Assistant Professor of Supply Chain Management at Widener University’s School of Business Administration. He holds a PhD in Transportation & Logistics from North Dakota State University and previously served as a graduate research assistant at the Upper Great Plains Transportation Institute. His work includes federally funded projects like the Mountain-Plains Consortium’s MPC-550 project, focusing on highway-rail grade crossing safety. Dr. Keramati teaches courses in enterprise resource planning, decision analytics, database management, transportation/logistics, project management, and data analytics. Education: PhD in Transportation & Logistics, North Dakota State University Graduate Research Assistant at Upper Great Plains Transportation Institute Research Focus: Dr. Keramati develops mathematical, statistical, and machine learning approaches to solve complex problems in transportation, supply chain, and logistics. Key areas include data mining, big data decision support, transportation network analytics, project scheduling, smart manufacturing, and accident analysis. His interdisciplinary work bridges supply chain optimization with emerging technologies like blockchain for healthcare and clinical trials. Awards & Recognition: Student Paper Award, American Association of State Highway and Transportation Officials (2017) Grants & Projects: Lead researcher on the Mountain-Plains Consortium’s MPC-550 project, which expanded his dissertation work on safety systems for highway-rail crossings. Collaborates on federally funded transportation safety initiatives and supply chain optimization for bioethanol and pharmaceutical industries. Labs/Teams: Active in Widener’s School of Business research groups focusing on supply chain innovation and interdisciplinary projects combining logistics with emerging technologies.
