Sridhar R. Tayur is the Ford Distinguished Research Chair and University Professor of Operations Management at Carnegie Mellon University’s Tepper School of Business. He holds a Ph.D. in Operations Research from Cornell University and a B.Tech. in Mechanical Engineering from IIT Madras. His research focuses on quantum computing applications in operations research, healthcare systems optimization, and supply chain management. He has held visiting roles at MIT, Stanford, and Cornell, and founded companies like SmartOps and OrganJet. His recent work spans quantum-inspired optimization algorithms, healthcare decision support systems, and fair resource allocation policies. He has contributed to over 110 publications, including high-impact papers in Management Science , Operations Research , and IEEE Transactions . Awards include INFORMS Fellow and NAE membership. He teaches courses in quantum integer programming, healthcare operations, and service management at the Tepper School. Education: Ph.D. (Cornell), B.Tech. (IIT Madras) Research Labs: Quantum Technology Group, OrganJet Key Awards: INFORMS Fellow, NAE Member, MSOM Distinguished Fellow Teaching: MBA Operations Management, PhD Quantum Optimization, Healthcare Systems His interdisciplinary work bridges quantum computing, healthcare policy, and logistics, supported by collaborations with industry and government institutions.
Massimo Mischi is a Full Professor at the Faculty of Electrical Engineering of the Eindhoven University of Technology (TU/e) and chairs the Signal Processing Systems (SPS) Division , the largest division at TU/e with over 250 researchers. He founded the Biomedical Diagnostics (BM/d) Lab in 2012, which now includes 180 researchers and clinical/industrial advisors, focusing on biomedical signal processing for diagnostics and monitoring.
Prof. Liam Murphy is a Full Professor of Computer Science & Informatics at University College Dublin (UCD) and Director of the Performance Engineering Laboratory. He holds a B.E. from UCD, M.Sc. and Ph.D. from UC Berkeley. His research focuses on performance engineering of networks, software systems, and multimedia transmissions. He has published over 150 peer-reviewed papers and is an IEEE member and Fellow of the Irish Computer Society. Education: B.E. in Electrical Engineering, UCD (1985) M.Sc. & Ph.D. in Electrical Engineering & Computer Sciences, UC Berkeley (1988, 1992) Research Interests: Dynamic resource allocation in networks Cloud computing efficiency Software performance engineering Wireless multimedia systems Quality of Service (QoS) optimization Recent work emphasizes energy-efficient cloud workflows, multi-objective data center optimization, and decentralized traffic simulation. Grants & Awards: Fellow of the Irish Computer Society (2007) Conference Paper Awards (2004, 2002, 2001) Principal Investigator in multiple funded projects (e.g., EU-funded traffic simulation, cloud resource allocation) Advising & Labs: Directed 24 Ph.D. and 8 M.Sc. students. Leads the Performance Engineering Laboratory (PEL), focusing on distributed systems, cloud efficiency, and network performance. Collaborates on industry-relevant projects like crovan (UCD/DCU campus company). Teaching: Coordinates courses on computer science fundamentals, distributed systems performance, and software engineering at UCD.
Prof. Martin Haenggi is the Frank M. Freimann Professor of Electrical Engineering and Concurrent Professor in the Department of Applied and Computational Mathematics and Statistics at the University of Notre Dame. He holds a Dr.sc.techn. (Ph.D.) from ETH Zurich and has been at Notre Dame since 2000. His research focuses on stochastic geometry and wireless networks, including cellular, heterogeneous, vehicular, and millimeter-wave systems. He has held sabbaticals at UCSD (2007–2008), EPFL (2014–2015), and ETH Zurich (2021–2022). Education: Dipl.-Ing. (M.Sc.), ETH Zurich, 1995 Dr.sc.techn. (Ph.D.), ETH Zurich, 1999 Research interests emphasize stochastic geometry for analyzing network performance, including coverage, interference, and reliability in wireless systems. Key areas include meta distributions, spatial-temporal analysis, and network optimization. His work has been recognized with IEEE Fellow status, Clarivate Highly Cited Researcher distinction, and NSF CAREER Award (2005). Grants and Awards: NSF Award (Deep Stochastic Geometry: 2020–2023) NSF Award (Toward a Stochastic Geometry for Cellular Systems: 2015–2019) Rice Prize (2017), Best Survey Paper Award (2017), and Best Tutorial Paper Award (2010) from IEEE Communications Society Teaching includes advanced courses on stochastic geometry, wireless networks, and signal processing. His lab focuses on theoretical and applied aspects of network modeling, with collaborations in industry and academia.
Professor Peter F. Driessen is a faculty member in the Department of Electrical and Computer Engineering at the University of Victoria, with a cross-appointment in the School of Music. He holds a BSc and PhD from the University of Victoria and is a Professional Engineer (PEng). His research focuses on communication systems, signal processing, control, and interdisciplinary projects in computer music and wireless technologies. Key areas include audio/video signal processing, radio propagation, sound recording, and multimedia systems. He leads the University of Victoria Propagation Laboratory, which explores radio wave propagation and Amateur radio integration with engineering education. His work spans theoretical research and applied projects like ECOSat satellite systems, software-defined radio (SDR), and innovative musical instruments such as the Radio Drum. He supervises undergraduate and graduate projects in these domains through ELEC 499 courses. Notable contributions include the APEGBC Editorial Board Award for Best Paper (2002) and patents in wireless networking and signal processing. His teaching includes courses in signal analysis and electromagnetics, and he collaborates on interdisciplinary programs like the Music/Computer Science degree. Education: BSc in Electrical Engineering, University of Victoria PhD in Electrical Engineering, University of Victoria Research Interests: Audio and video signal processing for music and media Software-defined radio and Amateur radio technologies Satellite communication and ground station development Gesture-based interfaces and musical instrument design Error mitigation in streaming audio/video Optical and microwave-photonic systems Labs & Collaborations: Propagation Laboratory (radio wave research) UVic Experimental Radio Group (Amateur radio club) UVic Satellite Design Team (ECOSat projects) UVic Centre for Aerospace Research Grants & Awards: APEGBC Editorial Board Award (2002) Multiple US patents in wireless systems and signal processing
Marco Di Renzo is a CNRS Research Director (Professor) and Head of the iPhyCom group at the Laboratory of Signals and Systems (L2S) at Paris-Saclay University, France. He is affiliated with both CNRS and CentraleSupélec. His roles include: Member of L2S Management Committee and Board Council Member of the Ph.D. School Admission Committee Academic Vice Chair, ETSI Industry Specification Group on RIS Editorial and leadership roles in IEEE communications journals Education: Laurea (cum laude) and Ph.D. in Electrical Engineering from University of L’Aquila (2003, 2007) Habilitation à Diriger des Recherches from Paris-Saclay University (2013) Research focuses on 6G networks , reconfigurable intelligent surfaces (RIS) , and integrated sensing and communications (ISAC) . He explores electromagnetic theory, machine learning applications, and energy-efficient wireless systems. His work addresses challenges in near-field communications, multi-user MIMO, and holographic beamforming. He advocates for physics-driven design principles in next-gen networks. Key awards include IEEE/IEE Fellowships, the Michel Monpetit Prize, and multiple IEEE Best Paper Awards. He holds international visiting professorships at institutions like the University of Oulu (Finland) and Nanyang Technological University (Singapore). Active in standardization via ETSI ISG RIS and contributes to global initiatives like the ITU 6G Vision. His research bridges theoretical models with practical implementations, emphasizing interdisciplinary collaboration between physics, signal processing, and AI.
Andrea C. Ferrari is a Professor of Nanotechnology at the Department of Engineering, University of Cambridge, UK. He holds multiple leadership roles, including Director of the Cambridge Graphene Centre and EPSRC Centre for Doctoral Training in Graphene Technology, and serves as Science and Technology Officer for the EU Graphene Flagship. Education: PhD, University of Cambridge (2001) Laurea in Nuclear Engineering, Politecnico di Milano (1997) Ferrari’s research focuses on graphene, 2D materials, and their applications in nanotechnology, photonics, optoelectronics, and Raman spectroscopy. His work bridges fundamental studies and industrial translation, emphasizing scalable synthesis and characterization techniques. His publications span over 390 peer-reviewed articles, including groundbreaking studies on graphene photonics, quantum emitters, and advanced optoelectronic devices. These works are highly cited, with an H-index of 115 and over 116,000 total citations. Scientific Awards: IMR-Lee Hsun Lecture Award (2018) Nanosmat Award (2017) Knight Officer of the Order of the Star of Italy (2017) ERC Synergy Grant (2013) EU-40 Materials Prize (2011) Royal Society Wolfson Research Merit Award (2010) ERC Starting Grant (2008) Philip Leverhulme Prize (2005) Ferrari has secured over £60M in research funding, including leadership roles in the EU Graphene Flagship and the EU Quantum Technology Flagship. He is a Fellow of the Optical Society, Materials Research Society, Institute of Physics, and American Physical Society.
Dalibor Radovanović is a researcher at Singidunum University , affiliated with the Faculty of Business Informatics . His work spans cybersecurity, blockchain technologies, and their applications in business and IoT systems. Education: Doctoral Dissertation (2016, Singidunum University) Master's & Basic Studies (Faculty of Business Informatics) Secondary Education: ETŠ Nikola Tesla Research Interests include: Security frameworks for IoT and blockchain integration Smart card and wireless network vulnerabilities E-governance and corporate IT audit methodologies Machine learning applications in cybersecurity Environmental performance optimization in agribusiness Publication Trends reveal a focus on blockchain (2022), cybersecurity (2009-2022), and IT governance (2010-2017). His work bridges theoretical analysis with practical implementations in Serbia's digital economy. Collaborations with scholars like Marko Šarac and Saša Adamović highlight interdisciplinary approaches to securing financial systems, educational institutions, and industrial IoT applications.
Hailong Jiao is an Assistant Professor in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e) and an Associate Professor at Peking University Shenzhen Graduate School's School of Electronic and Computer Engineering. He is also a Visiting Assistant Professor with TU/e's Electronic Systems group. His research focuses on low-power and variations-resilient VLSI circuit and system design , including error-resilient systems, approximate computing, machine learning in VLSI, ultra-low voltage circuits, and emerging devices like 3D integration and carbon electronics. Education : BSc (highest honor, 2004, Shandong University), MSc (2008, Institute of Microelectronics, Chinese Academy of Sciences), PhD (2012, HKUST). Collaborations : BrainWave project (TU/e and Radboud University Nijmegen) developing wearable brainwave processing for epilepsy/Parkinson's healthcare. Editorial Roles : Associate Editor for Elsevier Microelectronics Journal and World Scientific Journal of Circuits, Systems, and Computers. Committee Memberships : HiPEAC, MemoCiS, ACM/SIGDA, and six IEEE committees. Research Trends : Recent articles emphasize energy-efficient IoT networks , voltage stacking , sensitivity control , and scan flip-flop design , aligning with UN SDGs for energy engineering and healthcare innovation. Scientific awards include highest honor at BSc .
Ben Marsden is a Senior Lecturer in History of Science and Technology at the University of Aberdeen's School of Divinity, History, Philosophy and Art History, where he previously served as Head of the Department of History (2018-2023). His administrative roles include Deputy Head of School (2009-2011) and Director of the Centre for the History and Philosophy of Science, Technology and Medicine (2010-2011, 2012-present). Education includes: BA (MA) Hons in Mathematics, University of Cambridge (1987) Certificate of Advanced Study in Mathematics (MMath), University of Cambridge (1988) PhD in History, Philosophy and Social Relations of Science, University of Kent (1992) His research explores the cultural history of science and technology in 18th-19th century Britain, particularly engineering history, science-music relationships, and technological culture. He specializes in historical epistemology of engineering, urban knowledge production, and interdisciplinary studies bridging science with cultural practices. Current projects include a comprehensive biography of engineer W.J.M. Rankine. Publications demonstrate consistent focus on historical epistemology of engineering, Victorian scientific institutions, and technology's cultural impacts. Recent works examine mechanics philosophy, telecommunications history, and urban knowledge systems, showing methodological emphasis on material culture and institutional analysis. Awards and fellowships: British Academy Postdoctoral Fellow (1993-1995) Royal Society-British Academy Fellow in History of Science (1995-2000) Dibner Institute Senior Fellow at MIT/Harvard (2005-2006) He currently accepts PhD students in History and has led AHRC-funded projects on steamship cultural history. Collaborations include ongoing work with National Museum of Scotland. As editor of Notes & Records of the Royal Society (2015-2018), he shaped significant historical scholarship dissemination.
Mirjana Stojilovic is a Researcher at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences (IC), specifically within the Institute of Computer Engineering (IINFCOM) and the Parallel Systems Architecture Laboratory (PARSA). She also serves as a Lecturer in the SSC - Teaching department at EPFL. Her office is located at INJ 235, Station 14, 1015 Lausanne, Switzerland. Mirjana Stojilović received her Dipl. Ing. and Ph.D. degrees from the School of Electrical Engineering, University of Belgrade, in 2006 and 2013, respectively. Her academic journey includes collaborating with the Processor Architecture Laboratory at EPFL as a Guest Researcher from 2010 to 2013, working at the University of Applied Sciences Western Switzerland as a senior researcher from 2013 to 2016, and joining the Parallel Systems Architecture Lab at EPFL in October 2016. Dr. Stojilovic's research spans field-programmable technology, electronic design automation (EDA), and electrical-level attacks and countermeasures for reconfigurable hardware. Her work bridges the gap between hardware design and security, with a particular focus on vulnerability analysis and protection mechanisms for FPGA-based systems in cloud environments. She has made significant contributions to understanding side-channel attacks, fault injection techniques, and secure multi-tenancy solutions for shared hardware resources. Her extensive publication record reveals a clear research trajectory from traditional FPGA design and EDA topics toward increasingly security-focused investigations. Recent work demonstrates deep expertise in power analysis attacks, hardware trojans, and countermeasures for cloud-based FPGA systems, reflecting the growing importance of hardware security in distributed computing environments. Scientific Awards and Recognitions: Best Paper Award at 2016 International Symposium on Electromagnetic Compatibility (EMC Europe 2016) Young Scientist Award at 33rd International Conference on Lightning Protection (ICLP2016) Young Author Best Paper Award at the 20th Telecommunication Forum in Belgrade (TELFOR 2012) EPFL School of Computer and Communication Sciences (IC) Teaching Award (2015) Nominated for Best Paper Award at the International Conference on Field-Programmable Technology (FPT) (2020) Dr. Stojilovic has advised numerous PhD students including Coulon Louis, Pirayadi Rouzbeh, and Shrivastava Shashwat, along with past EPFL PhD students Glamocanin Ognjen and Mahmoud Dina. She has supervised dozens of semester and diploma projects focusing on hardware security, FPGAs, design automation, side-channel attacks, and cloud computing. Her service to the academic community includes serving on program committees for FPGA, FCCM, FPL, and DATE conferences, reviewing for multiple IEEE and ACM journals, and acting as associate editor for IEEE ESL and ACM TRETS. As a member of the Parallel Systems Architecture Laboratory at EPFL, Dr. Stojilovic leads research projects investigating security aspects of reconfigurable hardware systems. Her team works at the intersection of computer architecture, electronic design automation, and hardware security, with particular emphasis on vulnerabilities and protections for shared FPGA resources in cloud environments.
Pedro Ferreira is a Full Professor at Carnegie Mellon University (CMU), holding a joint appointment in the School of Information Systems & Management at the Heinz College and the Department of Engineering and Public Policy within the College of Engineering. His research focuses on how technology influences education, media consumption, and peer effects, leveraging large datasets from randomized experiments. Ferreira has been recognized with the 2018 INFORMS Early Career Award and Top 17th worldwide research scholar ranking (2020–2022). He co-founded CMU's Initiative for Teaching and Education Analytics (iTEA) and advises numerous students in areas like AI/ML in education and media analytics. Education: BSc in Computer Science (IST), MSc in Electrical Engineering and Computer Science & Technology Policy (MIT), PhD in Telecommunications Policy (CMU). He has taught at MIT, IST, and invited roles at Católica-Lisbon and the University of Cambridge. Research Interests: Impact of digital technologies on education outcomes (e.g., smartphones in classrooms, video analytics), peer influence in media industries (e.g., binge-watching, recommender systems), and empirical methods using randomized experiments. Current projects include AI-driven education improvement and policy implications of AI/ML technologies. Notable Achievements: Over 15 peer-reviewed articles in top journals like Management Science and MIS Quarterly. Key grants include Gates Foundation funding for video-based education research and Koch Foundation support for online certification studies. He serves as Associate Editor for Management Science and previously for MIS Quarterly. Advising & Grants: Advised 23 PhD students, many now in academia and industry. Current students research facial recognition in education and hybrid recommender systems. Ferreira has led grants totaling millions, including studies on GDPR's impact on piracy tracking and worldwide VoD availability. Professional Service: Organized conferences like the Symposium on Statistical Challenges in eCommerce Research (SCECR). Served on NSF review panels and CMU’s Portugal PhD program steering committee.曾参与葡萄牙知识社会局(UMIC)的国家级政策制定，推动宽带学校项目。
Erkut Erdem is a Professor in the Department of Computer Engineering at Hacettepe University, where he leads the Computer Vision Laboratory (HUCVL). His research focuses on computer vision and machine learning, particularly on incorporating different kinds of context (spatial, temporal and cross-modal) into visual processing across all levels from low to high-level vision. He received his Ph.D. (2008), M.Sc. (2003), and B.Sc. (2001) from Middle East Technical University. Prior to joining Hacettepe University in 2010, he completed a post-doctoral fellowship at Ecole Nationale Supérieure des Télécommunications (2009-2010) and held visiting researcher positions at UCLA (2007) and Virginia Tech (2004). His current research interests include Visual Saliency Prediction, Automatic Image Description, Video/Photoset Summarization, Image Filtering, and Image Editing. Recent work has focused on multimodal learning with video-language models, diffusion-based image editing, and event-based vision for low-light conditions. His research has been published in top venues including NeurIPS, ICLR, ICCV, SIGGRAPH, and ACL. He has received significant recognition including The Young Researcher Award from Turkish Academy of Sciences and being named a 2022 Outstanding Associate Editor of IEEE Transactions on Multimedia. He has secured multiple research projects funded by TUBITAK and received gift funds from Adobe Research for text-guided image synthesis work. Current Teaching: BBM202: Algorithms, AIN434/BBM444: Fundamentals of Computational Photography Graduate Supervision: 6 current Ph.D. students, numerous recent graduates including Burak Ercan (2024) and Aysun Kocak (2023) Professional Affiliations: Co-affiliated with Koç University and İş Bank AI Center (KUIS AI)
Richard MA Tianbai is an Associate Professor at the School of Computing, National University of Singapore (NUS), and serves as IT Coordinator for Computing Facilities. He holds a B.Sc. (First-Class Honors) and M.Phil. from the Chinese University of Hong Kong, followed by an M.Sc. and Ph.D. from Columbia University, USA. His research focuses on systems & networking, distributed computing, and internet economics, with projects addressing cloud-based big data systems and internet peering agreements. Richard has received multiple awards, including the Best Paper Award Runners-up at ACM Mobihoc 2020 and the Teaching Excellence Award from NUS School of Computing in 2019. His work bridges theoretical models with practical applications in network economics and distributed systems. Education: B.Sc. (First-Class Honors), Computer Science & Engineering, Chinese University of Hong Kong (2002) M.Phil., Computer Science & Engineering, Chinese University of Hong Kong (2004) M.Sc., Columbia University (2008) Ph.D., Columbia University (2010) Research Interests: Cloud-Based Big Data Systems: Innovating serverless paradigms for real-time analytics (e.g., Stream as a Service). Internet Economics: Modeling peering agreements, premium peering dynamics, and regulatory alternatives to net neutrality. Distributed Computing: Auto-scaling frameworks (e.g., Elasticutor, DRS) for real-time stream processing. His research emphasizes performance guarantees and resource optimization in dynamic networked systems. Awards: Best Paper Award Runners-up (ACM Mobihoc 2020) Teaching Excellence Award (School of Computing 2019) Bell Labs Best Paper Award (IEEE SDP 2015) Best Paper Awards at ICNP 2014 and IC2E 2013 Grants & Advising: Recipient of research grants supporting projects like “Testbed for Innovative Inter-Networking Research.” Advises on doctoral projects related to stream processing and network economics. His work is funded by industry collaborations and institutional grants. Labs & Teams: Part of the Distributed Network Analysis (DNA) Research Group and Advanced Networking & Systems Research Group, fostering interdisciplinary collaborations in networking and distributed systems.
Mikko Valkama is a Professor at the Department of Communications Engineering , part of the Faculty of Information Technology and Communication Sciences at Tampere University . His research focuses on advanced wireless communication systems, positioning technologies, and integrated sensing and communication (ISAC). He holds an Orcid ID ( 0000-0003-0361-0800 ) and can be reached at mikko.valkama@tuni.fi . Research interests span 5G/6G networks , RF antenna design , deep learning for signal processing , and millimeter-wave systems . He leads projects on positioning algorithms (e.g., mmWave SLAM, NLOS mitigation), ISAC architectures, and hardware-efficient transmitter linearization. Notable contributions include works on DECT-2020 NR standards, phase-based localization, and RIS-assisted systems. In 2025 alone, his group published over 30 articles on topics such as: Antenna array design for Ka-band and wideband applications Machine learning for power amplifier predistortion Bistatic radio SLAM and mmWave mapping Covert transmission and physical-layer security His work bridges theoretical advancements with practical implementations, often validated through experimental setups (e.g., TUJI1 dataset for indoor localization). No scientific awards were explicitly listed in the provided texts.
