Granger Morgan is the Hamerschlag University Professor of Engineering at Carnegie Mellon University, holding joint appointments in the Department of Electrical and Computer Engineering, the Department of Engineering and Public Policy, and the H. John Heinz III College. His research focuses on science, technology, and public policy, particularly energy systems, climate change, risk analysis, and regulatory frameworks. He co-directs the NSF Center for Climate and Energy Decision Making and the Electricity Industry Center. Education: Ph.D., Applied Physics and Information Science, University of California, San Diego (1969) M.S., Astronomy and Space Science, Cornell University (1965) B.A., Physics, Harvard College (1963) Research Interests: Energy decarbonization and electric power resilience Climate change mitigation and adaptation strategies Risk assessment and policy analysis Hydrogen and nuclear energy systems Global technology adoption dynamics Awards and Affiliations: FAS Public Service Award (2016) Member, National Academy of Sciences Fellow, AAAS, IEEE, and Society for Risk Analysis National Academies Report Review Committee Co-Chair Advisory roles at DOE, PNNL, and international energy councils Advisory and Grants: Leadership in national studies on electric grid resilience and hydrogen infrastructure Recipient of NSF and industry-funded research grants Guidance on global energy policy and regulatory frameworks Labs and Teams: NSF Center for Climate and Energy Decision Making (co-director) Carnegie Mellon Electricity Industry Center Interdisciplinary energy policy research groups
Vijay Raghunathan is a Professor in the Department of Electrical and Computer Engineering at Purdue University's College of Engineering. His work focuses on hardware and software architectures for embedded systems, wireless sensors for IoT, and wearable/implantable electronics with emphasis on low power design, energy harvesting, emerging memory technologies, and secure system design. Academic Rank: Professor Department: Electrical and Computer Engineering University: Purdue University Research Focus: Energy-efficient embedded systems, IoT, wearable devices His research explores low power design at both board-level and system-on-chip scales, micro-scale energy harvesting , and reliable/secure system design for medical devices. Recent work focuses on Processing-in-Sensor/Memory for battery-free AIoT devices, state space models for neural processing units, and security coprocessor integration in autonomous systems. Analysis of his publications reveals trends in energy-efficient neural network acceleration , approximate computing for edge inference , and compute-in-memory architectures . Key subfields include collaborative edge-cloud partitioning , sparse DNN accelerators , and security frameworks for medical devices. Vijay's work also addresses energy-accuracy tradeoffs in multimodal cognitive systems and intermittent computing using non-volatile memory technologies. His contributions span from microcontroller energy management to security protocols for implantable electronics.
Ronald McGarvey is a Full Professor at IÉSEG School of Management since 2022, with prior roles including Associate Professor with Tenure at the University of Missouri (2013-2022) and Senior Operations Researcher at RAND Corporation (2002-2022). He holds a Ph.D. in Industrial Engineering and Operations Research from Pennsylvania State University and an H.D.R. in Industrial Engineering from the University of Paul Sabatier, France. Education : H.D.R. (2024), Industrial Engineering, University of Paul Sabatier Ph.D. (2002), Industrial Engineering and Operations Research, Pennsylvania State University His research focuses on Operations Research and Robust Optimization applied to diverse domains: Healthcare Logistics : Modeling access disparities in rural obstetric care for American Indian populations Environmental Sustainability : Analyzing biomass energy systems, forest carbon impacts, and waste management frameworks Network Design : Developing optimization models for supply chain resilience, military logistics, and urban transit safety Policy Analysis : Evaluating multi-state environmental collaborations and localized food systems His publications demonstrate strong interdisciplinary applications of mathematical programming and spatial optimization to real-world challenges in healthcare access, energy sustainability, and transportation systems. Key Collaborations : Working with researchers in public health (Thorsen, Noble), environmental science (Aguilar), and engineering (Mirzaee, Gutierrez-Lopez)
Mario Berges is an Associate Professor in the Department of Civil and Environmental Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in Electrical and Computer Engineering. He holds leadership roles as Co-Director of the IBM Smart Infrastructure Analytics Lab and Director of the Intelligent Infrastructure Research Lab (INFERLab). His work focuses on applying information/communication technologies to enhance the operational efficiency and resilience of built environments amid evolving resource constraints and climate changes. Education: PhD in Civil & Environmental Engineering from CMU (2010). Research Interests: Berges' research integrates smart infrastructure systems, energy efficiency, and machine learning. Key areas include non-intrusive load monitoring (NILM), structural health monitoring of pipelines, building automation systems, and urban heat risk modeling. He develops data-driven frameworks for energy disaggregation, sensor placement optimization, and real-time infrastructure diagnostics. Awards: Recognized with the 2010 FIATECH Outstanding Early Career Researcher Award and 2015 Dean’s Early Career Fellowship from CMU. Grants & Labs: Leads INFERLab, collaborating with IBM on smart infrastructure projects. His work spans academic-industry partnerships focused on building analytics, smart grid technologies, and sensor networks. Future Directions: Expanding research into AI-driven energy systems, resilient urban infrastructure, and cross-disciplinary solutions for climate adaptation.
Rakesh Kumar is a Professor and John Bardeen Faculty Scholar in the Electrical and Computer Engineering Department at the University of Illinois at Urbana-Champaign. His work focuses on computer architecture, system-level design automation, and low-power computing. PhD in Computer Engineering from University of California, San Diego BS in Electrical Engineering from IIT Kharagpur His research spans all layers of the computing stack, with key contributions to flexible computer systems , waferscale computing , error-resilient architectures , and approximate computing . He has pioneered work on voltage-reliability tradeoffs and peak power management techniques. Recent publications highlight trends in space microdatacenters , printed microprocessors , and neural graph accelerators . His work on plastic chips was recognized as one of the three biggest semiconductor headlines of 2022 by IEEE Spectrum. IEEE Fellow (2024) ISCA Influential Paper Award MICRO Test-of-Time Award ICCAD Ten Year Retrospective Most Influential Paper Award Best Paper Awards at CASES, SELSE, HPCA He has received teaching accolades including the Stanley H. Pierce Faculty Award and Ronald W. Pratt Outstanding Teaching Award . His research group explores hardware-software co-design for emerging applications in AI, IoT, and sustainable computing.
Sara Stymne is a Senior Lecturer in Computational Linguistics at the Department of Linguistics and Philology, Uppsala University, where she has been working since 2012. She initially joined as a post-doc (2012-2015), then worked as a researcher (2015-2017), and served as an assistant professor (2017-2023) before her current position as Senior Lecturer. Prior to Uppsala, she was a researcher at Linköping University's Department of Computer and Information Science. Dr. Stymne earned her PhD in Computational Linguistics from Linköping University in 2012 with the thesis 'Text Harmonization Strategies for Phrase-Based Statistical Machine Translation,' following a Licentiate degree in Computational Linguistics (2009) and a Master's degree in Cognitive Science (2006), both also from Linköping University. During her doctoral studies, she spent the autumn of 2010 and spring of 2009 at Xerox Research Centre Europe in Grenoble, France. Her primary research interests focus on cross-lingual natural language processing and digital humanities, with particular emphasis on multilingual dependency parsing. Dr. Stymne is passionate about applying computational linguistics to solve research questions in other fields, including language history, literary analysis, and political science. Her earlier work concentrated on machine translation, with specific interests in discourse-aware translation, compound processing, and error analysis. She has made significant contributions to the development of language technology tools for analyzing dialogue, narrative, and stylistic features in literature. Analysis of Dr. Stymne's recent publications reveals a strong focus on cross-lingual and cross-domain natural language processing. Her work spans multiple subfields including dependency parsing across genres and topics, discourse relation analysis in low-resource languages like Egyptian Arabic, direct speech identification in Swedish literature, and causality detection in governmental documents. A notable trend is her application of NLP techniques to digital humanities problems, particularly in analyzing literary texts and historical language change. Her research often involves creating and utilizing specialized datasets for specific linguistic phenomena across multiple languages. Dr. Stymne actively supervises graduate students, having guided numerous master's and bachelor's theses on topics ranging from speech recognition to multilingual parsing and causality detection. She leads or participates in several research projects including 'Fictional prose and language change' (funded by VR, 2021-2023) and 'Enabling climate-resilient development' (funded by Marianne and Marcus Wallenberg Foundation, 2023-2027), demonstrating her commitment to interdisciplinary research with practical applications. Her work has resulted in several notable software resources including uuPronPred for cross-lingual pronoun prediction, uuparser for dependency parsing, and Docent for document-level machine translation. Within the Computational Linguistics and Language Technology group at Uppsala University, Dr. Stymne contributes to multiple research initiatives focused on developing language technology tools for digital humanities applications. Her team works closely with literary scholars and historians to create computational methods for analyzing large corpora of literary texts, particularly focusing on Swedish literature across different historical periods. Her research bridges the gap between theoretical computational linguistics and practical applications in the humanities, creating new methodologies for quantitative analysis of literary and historical texts.
Anoosheh Heidarzadeh is an Assistant Professor in the Department of Electrical and Computer Engineering at Santa Clara University's School of Engineering. He holds a Ph.D. in Electrical and Computer Engineering from Carleton University (2012) and previously served as a Visiting Assistant Professor at Texas A&M University (2018-2022) and Associate Research Scientist at the same institution (2015-2017). His postdoctoral research was conducted at the California Institute of Technology (2013-2014). His research focuses on: Information and coding theory : Fundamental limits of data transmission and storage systems Private and secure computing : Protocols for confidential data processing in networked environments Fault-tolerant distributed systems : Resilient computation frameworks for large-scale applications Distributed machine learning : Scalable algorithms for collaborative learning architectures Recent publications (2021-2022) demonstrate strong emphasis on privacy-preserving computation (covering 73% of articles) and distributed coding techniques (67% of articles), with innovations in private information retrieval, matrix operations, and group testing methodologies. Theoretical contributions dominate (87%), while 13% address applied challenges like COVID-19 screening.
Samir Dani is a Professor of Operations and Supply Chain Management at Keele University’s Keele Business School. He holds Chartered Manager status and is a Fellow of multiple professional bodies, including the Higher Education Academy and Chartered Institute of Logistics and Transport. Prior to academia, he worked in India’s automotive industry. His research focuses on supply chain resilience, sustainability, food logistics, and Industry 4.0 technologies like AI and Blockchain. Affiliations: Keele University (current), University of Huddersfield (2014–2019), Loughborough University (2005–2008) Leadership: Former Head of Logistics, Marketing, Hospitality, and Analytics Department at University of Huddersfield Industry Engagement: £5M Leeds City Region LEP Supply Chain Program, UK-India trade advisory roles Research Interests: Supply chain risk and resilience Food supply chain sustainability AI, IoT, and Blockchain applications Industry 4.0 transformations Recent Article Trends: Focus on climate action impacts, blockchain trust mechanisms, and SME net-zero strategies. His work bridges academic theory with industry challenges, emphasizing technology adoption and sustainability. Awards: Prix des Associations (2015), UK Top 100 Logistics Professional (2017/18) Grants: £800K+ from EPSRC, IMCRC, and KTP Advisory Roles: Editorial Board member of Supply Chain Management: An International Journal, Academic Review Board member of International Journal of Operations and Production Management.
Ceren Budak is an Associate Professor at the University of Michigan School of Information and holds a joint appointment as Associate Professor of Electrical Engineering and Computer Science in the College of Engineering. Her work bridges computer science, statistics, and social sciences through computational social science approaches. Her educational background includes a PhD in Computer Science from the University of California, Santa Barbara (2012) and a Bachelors degree in Computer Science from Bilkent University in Turkey (2007). Prior to joining the University of Michigan faculty, she was a Postdoctoral Researcher at Microsoft Research New York. Professor Budak's research centers on computational social science, with particular emphasis on analyzing large-scale datasets to address questions with social, political, and policy implications. Her work spans several interconnected domains: News Media Production & Consumption (examining bias in news outlets and reader preferences), Social Movements & Media (using social media data to study collective action), Social Networks (understanding information diffusion processes), and Measuring and Promoting the Quality of Online Discussions (developing tools to improve online conversations). She teaches SI 608 (Networks) and SI 618 (Data Manipulation and Analysis) at the School of Information. Her publication record demonstrates consistent contributions to understanding how online information ecosystems operate, with recent work focusing on AI-human collaboration, misinformation dynamics, social movement framing, and the application of computational methods to political communication. Her research shows a clear trajectory from foundational work on social network diffusion to increasingly sophisticated analyses of contemporary information challenges. Among her service activities, she has served as Registration chair for COSN (ACM Conference on Online Social Networks) 2015 and as Program Committee Member for numerous prestigious conferences including WWW, ICWSM, WebSci, AAAI, and others. She has also been involved in organizing the MSR NYC Data Science Seminar Series and instructing the Microsoft Research Data Science Summer School.
Charalampos Papamanthou is an Associate Professor of Computer Science at Yale University, where he also serves as Co-director of the Yale Applied Cryptography Laboratory and a member of the Yale Institute for Foundations of Data Science. He holds affiliations with the Yale Center for Algorithms, Data, and Market Design. Additionally, he is Chief Scientist at Lagrange Labs. His research focuses on computer security and applied cryptography, particularly verifiable and privacy-preserving computations, leakage-abuse attacks on searchable encryption, and scalable blockchains/cryptocurrencies. He has advised numerous students and postdocs, and his work is supported by NSF, Protocol Labs, and JP Morgan. Research Interests: His primary areas include cryptographic protocols, privacy-preserving systems, blockchain infrastructure, secure cloud computing, and distributed consensus mechanisms. He has pioneered advancements in zero-knowledge proofs, private information retrieval, and dynamic searchable encryption. Awards: He has received prestigious awards such as the CCS Test-of-Time Award (2022), JP Morgan Faculty Research Award (2022), and NSF CAREER Award (2017). His contributions span over 140 publications in top venues like CRYPTO, CCS, and SODA. Teaching: He has taught advanced courses in cryptography, algorithms, and computer systems security at Yale and previously at the University of Maryland and Brown University. Recently, he chairs Yale’s PhD admissions in Computer Science. Labs & Teams: Leads the Yale Applied Cryptography Lab, focusing on real-world applications of cryptographic research. Collaborates with industry partners like Lagrange Labs to develop privacy-preserving technologies.
Prof. Dr. Timothy Roscoe is a Full Professor in the Department of Computer Science at ETH Zurich. His research focuses on operating systems, networking, and distributed systems. He was inducted as an ACM Fellow in 2014 for contributions to these fields. Previously, he worked at Intel Research Berkeley, UC Berkeley (Adjunct Professor), and Sprint Labs. His work includes foundational contributions to systems like PlanetLab, P2 Declarative Networking, and the Nemesis OS. Roscoe holds a PhD from the University of Cambridge and has led projects in cloud computing, wide-area network measurement, and secure systems design. His current research emphasizes hardware-software co-design, formal verification of systems, and scalable memory architectures. Education: PhD in Computer Science, University of Cambridge (1995) Key Roles: Principal Researcher at Intel Berkeley Lab, Visiting Researcher at National ICT Australia Research Highlights: Contributions to distributed systems (PlanetLab), declarative networking (P2), and secure microkernels (seL4 integration). Current projects address challenges in disaggregated memory systems, coherent interconnects, and trustworthy embedded systems. Awards: ACM Fellow (2014), numerous grants and industry collaborations. Labs/Teams: Systems Group at ETH Zurich, focusing on OS design, hardware architectures, and formal methods.
Prof. Dr. Gonzalo Guillén Gosálbez is a Full Professor at the Department of Chemistry and Applied Biosciences , ETH Zürich. He holds a PhD in Process Systems Engineering (UPC, 2005) and has held academic positions at Imperial College London (Reader), University of Manchester (Senior Lecturer), and Universitat Rovira i Virgili (Assistant/Associate Professor). His research focuses on Sustainable Chemical Processes , integrating life cycle assessment, optimization techniques, and planetary boundary analysis to evaluate and design low-carbon technologies. Current position: Full Professor, ETH Zürich (2019–present) Prior roles: Imperial College London (2016–2019), University of Manchester (2014–2016), URV Spain (2008–2014) Education: PhD (UPC, 2005), MEng/BEng (University of Murcia) His research explores CO2 valorization , green methanol synthesis , circular marine fuels , and planetary boundary compliance in energy and chemical systems. Recent work emphasizes machine learning for process modeling, single-atom catalysis , and decentralized ammonia production . Scientific contributions include 15+ peer-reviewed articles (2023–2025) in journals like Nature Chemical Engineering , ACS Sustainable Chemistry & Engineering , and Energy & Environmental Science . Key themes: Optimization of hybrid fossil/renewable carbon systems Environmental impacts of energy transitions Catalyst design for sustainable chemistry Life cycle assessment of emerging technologies Awarded UPC Top Doctoral Student Award and Top National Student Award , he combines process systems engineering with sustainability metrics to address global challenges in chemical and energy systems.
Supratik Guha is a Professor at the Pritzker School of Molecular Engineering and Senior Advisor to Argonne National Laboratory's Physical Sciences and Engineering directorate. His work bridges industrial R&D with academic and national lab research, focusing on quantum computing , semiconductor materials , and sensor networks for water and soil monitoring. Guha leads Argonne’s quantum information science strategy and serves as Faculty Director for the University of Chicago Center in Delhi. Education: PhD in Materials Science (USC, 1991), BTech in Engineering Physics (IIT Kharagpur, 1985) Research interests span multiple domains: Quantum technologies focusing on erbium-doped oxides for quantum memory and quantum interconnects Sensor networks for soil and water quality monitoring using cyberphysical systems Nanofabrication techniques including controlled spalling for heterogeneous material integration Advanced memory technologies exploring ferroelectric and optically addressable memory at atomic scales Scientific awards include: Election to National Academy of Engineering (2015) APS Prize for Industrial Applications of Physics (2015) Vannevar Bush Faculty Fellow (2018) Fellow of Materials Research Society and American Physical Society IBM Corporate Award (2013) Advising notable students like Manish Kumar Singh (co-founder memQ ), Cheng Ji (now at Intel), and Vamsi Nittala (now at Micron Technology). His group contributes to major DOE , NSF , and USDA funded projects including: Q-NEXT - DOE National Quantum Information Center AIFARMS - NSF/USDA AI for Agriculture Institute Thoreau Project - Geospatial sensor networks Labs and teams operate across University of Chicago and Argonne National Lab , with facilities for molecular beam epitaxy , nanofabrication , and optical/electrical characterization . The group has spawned startups like memQ (quantum networking) and K1 Semiconductors (wide-bandgap material transfer).
Michael McAlpine is a Professor in the Mechanical Engineering department at the University of Minnesota . He also holds affiliations with the Biomedical Engineering and Electrical and Computer Engineering departments. His research focuses on 3D printing functional materials & devices , Nanoscale inks , Biomedical devices , Bioelectronics , and Flexible Microsystems . Research Interests : 3D Printing, Biomedical Engineering, Nanotechnology, Flexible Electronics, Microfluidics Labs : ME 361/363 Contact : mcalpine@umn.edu , (612) 626-3303, ME 117 Recent Research Trends include 3D Printed Biomedical Devices , Flexible Electronics , and Bioprinting Applications . His work spans from Spinal Organoid Formation to Programmable Drug Release Capsules . Scientific Award : Circulation Research 2020 Best Manuscript Award
Dr. Mo Adda is a Principal Lecturer at the University of Portsmouth's School of Computing, part of the Faculty of Technology. He holds a PhD in Distributed Systems and Parallel Processing from the University of Surrey. His research focuses on network security, distributed systems, wireless networks, and cybercrime prevention. He leads projects in the Centre for Cybercrime and Economic Crime, exploring fault management in networks, blockchain applications, and IoT forensics. With 16 supervised theses, he advises on topics like energy-efficient cloud systems and machine learning for environmental modeling. His work bridges academia and industry, addressing challenges in software-defined networks, traffic control, and secure data sharing in social networks. Education: PhD in Distributed Systems (University of Surrey) Affiliations: Centre of Excellence in Defence, Risk & Resilience; Portsmouth Centre for Advanced Materials and Manufacturing Research Interests Dr. Adda's research spans: Network security and fault detection mechanisms Blockchain applications in IoT and forensics Energy-efficient cloud data center optimization Machine learning for climate modeling Self-organizing network protocols Grants & Collaborations His projects include collaborations with industry partners on secure data leakage detection in cloud systems and resilient wireless protocols for harsh environments. He has pioneered fault classification systems using clustering algorithms and fuzzy logic. Labs & Teams He contributes to the Centre for Cybercrime and Economic Crime, focusing on digital forensics and network intrusion analysis. His team develops frameworks for privacy management in social networks and proactive routing in software-defined networks.
