Jungsang Kim is the Schiciano Family Distinguished Professor of Electrical and Computer Engineering and Professor of Physics at Duke University. He serves as Associate Director of the Duke Quantum Center and leads the Multifunctional Integrated Systems Technology group. Quantum Computing with Trapped Ions Quantum Information Science Photonic Device Development Quantum Communication Networks His research focuses on scalable quantum information processors using trapped atomic ions and advanced photonic technologies. Key innovations include microfabricated ion traps, optical MEMS, and cryogenic systems for quantum integration. Recent publications highlight trapped ion quantum simulation, high-fidelity gate design, and photonic error mitigation. His group develops practical quantum hardware and co-founded IonQ, the first publicly traded pure-play quantum computing company. Fellow, American Physics Society (2021) Stansell Family Distinguished Research Award (2016) Fellow, National Academy of Inventors Fellow, Optica (formerly OSA) Kim's work bridges quantum physics and engineering, with over 80 patents and leadership in Duke's quantum computing initiatives. He recently stepped down as IonQ's CTO while maintaining active research and strategic roles at Duke.
Affiliation & Education Scott Hauck is a Professor at the University of Washington's Department of Electrical & Computer Engineering and an Adjunct Professor in Computer Science & Engineering. He leads the Adaptive Computing Machines and Emulators (ACME) Lab . He earned his BS in EECS from UC Berkeley (1990), and MS/PhD in CSE from the University of Washington (1992/1995). Research Focus Dr. Hauck specializes in FPGA-based reconfigurable computing with applications in: Quantum Computing: FPGA controllers for trapped-ion quantum systems enabling precise laser control and quantum state readout. Medical Imaging: Portable radiation sensors for personalized cancer therapy and PET scanner enhancements. High-Energy Physics: FPGA readout systems for ATLAS pixel detectors at CERN's Large Hadron Collider. AI Acceleration: Real-time machine learning inference for scientific applications via projects like hls4ml. His work bridges hardware innovation with computational physics, emphasizing real-time processing and low-latency systems. Publication Trends Recent research focuses on FPGA-accelerated machine learning for particle physics (e.g., transformer networks for LHC trigger systems) and quantum computing instrumentation. Earlier work established foundations in reconfigurable computing architectures and medical imaging electronics. Awards & Recognition Distinguished Teaching Award, University of Washington (2010) Advising & Funding Leads the ACME Lab with extensive funding from NSF, DARPA, NIH, DOE, and industry partners including Intel, Xilinx, and Microsoft. Mentored over 30 MS/PhD students in VLSI, reconfigurable systems, and scientific computing. Collaborations & Labs Directs the ACME Lab (EE1-307), collaborating with UW Radiology (Prof. Robert Miyaoka), UW Physics (Prof. Shih-Chieh Hsu), and Drexel University (Prof. Josh Agar). Projects include quantum control systems, LHC readout electronics, and medical sensor networks.
Soheil Salehi is a tenure-track Assistant Professor in the Department of Electrical and Computer Engineering at the University of Arizona, with a joint appointment in Systems and Industrial Engineering. He is the Director of the Privacy-preserving, Intelligent, and Secure Computing (PRISM) Lab, established in August 2022. Prior to this, he was an NSF-Sponsored Computing Innovation Fellow and Postdoctoral Research Fellow at the University of California, Davis. Ph.D., Electrical and Computer Engineering, University of Central Florida, 2020 M.S., Electrical and Computer Engineering, University of Central Florida, 2016 B.S., Isfahan University of Technology, Iran, 2014 Dr. Salehi's research focuses on the intersection of hardware, AI, and security. His work spans hardware and AI-enabled security in IoT , Generative AI for hardware design and security , neuromorphic and biologically-inspired AI hardware , emerging spin-based devices , reconfigurable architectures , low-power VLSI circuits , and digital twins and mixed reality for semiconductor workforce development . He also explores the application of Generative AI in personalized education . His recent publications, spanning 2023–2025, reveal a strong trend toward integrating AI and machine learning into hardware security and design. Key themes include automated secure IC design flows , AI-driven hardware obfuscation , firmware and side-channel attack analysis , security in neuromorphic and spiking neural networks , and educational frameworks using digital twins and generative models . His work appears in top venues like DAC, ICCAD, USENIX Security, IEEE TCAS-I, and ISCAS. Outstanding Reviewer Award, IEEE/ACM Design Automation Conference (DAC), 2023 Best Presentation of the Symposium Award, UC Davis Postdoctoral Research Symposium, 2021 UCF Excellence by a Graduate Teaching Assistant (University-Level), 2016 Nominated for 30-under-30 Award, UCF, 2020 Nominated for Postdoctoral Research Excellence Award, UC Davis, 2022 Dr. Salehi has secured significant research funding as PI and Co-PI, including a $300K NSF SaTC EAGER grant on Generative AI-based Personalized Cybersecurity Tutor, a $174,000 University of Arizona PIF Award, and multiple RII grants totaling over $198K. He has also received industry funding from CHEST. He actively mentors students and leads the PRISM Lab, which focuses on privacy-preserving and intelligent secure computing. His service includes roles as Technical Program Committee (TPC) Member and Session Chair at premier conferences such as DAC, ICCAD, CCS, NDSS, and GLSVLSI. The PRISM Lab, under his direction, conducts cutting-edge research in secure and intelligent hardware systems, with applications in IoT, edge computing, and workforce development. The lab emphasizes interdisciplinary collaboration and innovation in both research and education.
Mauro Conti is a Full Professor at the University of Padua, Italy, where he serves as Editor-in-chief of IEEE TIFS, UniPD Academic Advisor for Entrepreneurship Development, Study Program Coordinator of the MSc degree in Cybersecurity, Head of the SPRITZ Security and Privacy Research Group, and Director of the UniPD node of CINI Cybersecurity National Lab. He also maintains affiliations with TU Delft (NL) and the University of Washington (USA). Additionally, he is the CEO and co-founder of CHISITO and co-founder of DYALOGHI. His research focuses on security and privacy for wireless resource-constrained mobile devices (WSNs, RFIDs, and smartphones), computer system security, computer forensics, access control, and distributed and networked systems. Professor Conti has published extensively in top security venues including ACM CCS, IEEE S&P, NDSS, and USENIX Security, with recent work covering topics such as battery authentication, federated learning privacy, private set intersections, USB peripheral fingerprinting, and ATM PIN inference. He has received numerous prestigious awards including IEEE Fellow, Young Academy of Europe Fellow, EU Marie Curie Fellow, and DAAD Fellow. Professor Conti has advised over 100 students at various levels including PhD, MSc, and BSc, many of whom have gone on to successful careers in academia and industry. His research has been supported by multiple European Commission projects, university grants, and industry collaborations with companies like Cisco and Intel.
Christian Rossow is Faculty at CISPA – Helmholtz Center for Information Security in Dortmund, Germany, where he leads the System Security research group. He holds dual academic appointments as a professor in the Computer Science department at Saarland University and as an honorary professor at TU Dortmund University. His research spans systems, software, and network security, with a focus on cyber attacks, defenses, and privacy. Research Interests: His primary research areas include software and system security (e.g., exploitation techniques, compiler-assisted defenses, AI-assisted (in)security), network security (e.g., DDoS mitigation, attack attribution, traffic analysis), and cybercrime (e.g., malware analysis, data-driven studies). He emphasizes foundational research with practical applications. Publication Trends: His recent work (2023–2025) shows a strong focus on microarchitectural attacks (e.g., cache side-channels, prefetcher analysis), browser and web security (e.g., sandbox escapes, CSS fingerprinting), network protocol vulnerabilities (e.g., TCP spoofing, infinite loops), and applied cryptography (e.g., ISA extensions for key management). His research consistently targets top-tier venues like IEEE S&P, USENIX Security, ACM CCS, and NDSS. Distinguished Paper Award at IEEE EuroS&P 2021 Best Student Paper Award at MIT Spam Conference 2010 Advising and Grants: He actively supervises PhD students and postdoctoral researchers, with alumni placed in industry (NVIDIA, Crowdstrike, Continental) and academia. His research is supported by major grants including EU H2020 SISSDEN, BMBF-funded BOB, DFG-funded anonymous communication, and RAMSES. He regularly serves in leadership roles in the community, including PC Chair for RAID 2022/2023 and USENIX WOOT 2018, and Track Chair for ACM CCS 2026. Labs and Teams: He leads the System Security research group at CISPA, a world-leading institution for security and privacy. The group comprises talented full-time researchers and focuses on cutting-edge research with strong individual supervision and worldwide collaborations.
Saurabh Bagchi is a Professor at Purdue University, West Lafayette, USA. He holds a PhD in Computer Science from the University of Illinois Urbana-Champaign (2001). His research focuses on distributed systems security, networking, and embedded systems. Key areas include IoT security, cyber-physical systems resilience, and machine learning applications in edge computing. Bagchi's work spans theoretical and applied domains, addressing challenges in distributed algorithms, fault tolerance, and secure communication protocols. His contributions to firmware analysis, serverless computing optimization, and anomaly detection in industrial IoT systems have been widely recognized. He has published over 300 papers in top-tier conferences and journals such as IEEE Transactions on Dependable and Secure Computing, ACM Transactions on Sensor Networks, and CVPR. He collaborates with researchers in academia and industry to advance resilient networked systems, including projects funded by NSF and industrial partnerships. His lab explores cutting-edge topics like federated learning security, edge computing architectures, and game-theoretic approaches to cyber defense.
Associate Professor Dan Dongseong Kim is Deputy Director of UQ Cybersecurity and an Associate Professor at The University of Queensland (UQ), Australia. Previously, he held permanent academic positions at The University of Canterbury (UC), New Zealand (2011-2018) as a Senior Lecturer and Lecturer. His research focuses on Cybersecurity and Dependability for AI, IoT, Autonomous Vehicles, Cloud Computing, and Moving Target Defenses (MTD). Doctor of Philosophy in Computer Engineering from Korea Aerospace University Postdoctoral Research at Duke University (2008-2011) Visiting Scholar at University of Maryland (2007) Dan's work explores Graphical Security Models , Moving Target Defense for proactive resilience, and AI-Driven Cybersecurity with emphasis on adversarial robustness and interpretable models. His recent publications (2024-2025) span journals like IEEE Transactions on Dependable and Secure Computing and conferences such as DSN , addressing automated defense, evolving attacks, and hardware-aware security frameworks. He has advised 15 Ph.D. graduates, including researchers now at institutions like RMIT University, La Trobe University, and CSIRO's Data61. Current supervision includes projects on Automated Penetration Testing , AI-Based Intrusion Response , and Moving Target Defense . Dan's research is funded by agencies including the Republic of Korea's Agency for Defence Development and US Army Research Lab . His professional roles include Associate Editor for IEEE Communications Surveys and Tutorials and Steering Committee Chair for IEEE PRDC .
Dr. Chutima Boonthum-Denecke is a Professor in the Department of Computer Science at Hampton University's School of Science. She joined Hampton University in 2006 as an Assistant Professor and now serves as Director of the Information Assurance and Cyber Security Center (IAC@HU). She leads the NSF CyberCorps Scholarship for Service program and has contributed to NSF initiatives like ARTSI and STARS Alliances. Her educational background includes a Ph.D. in Computer Science from Old Dominion University (2007), an MS in Applied Computer Science from Illinois State University (2000), and a BS in Computer Science from Srinakharinwirot University (1997). Dr. Boonthum-Denecke's research integrates artificial intelligence, natural language processing, and cybersecurity. Key interests include: Developing intelligent tutoring systems and educational games Secure coding practices for software engineering NLP applications in information retrieval and assessment tools Cyber-physical security for IoT and robotics Her recent publications (2016-2021) focus on machine learning applications in cybersecurity, including sentiment analysis for threat detection, blockchain-enhanced IoT security, and vulnerability assessments of emerging technologies. Collaborative work with students frequently addresses privacy ethics in AI assistants, RFID implants, and cloud systems. She mentors students through the IAC@HU lab, resulting in award-winning conference presentations on cybersecurity topics. As Principal Investigator of NSF CyberCorps, she oversees scholarship programs that bridge academic research with national security needs.
Aldo Mozzanica is a Researcher at the Paul Scherrer Institute (PSI) in Switzerland, affiliated with the Laboratory for X-ray Nanoscience and Technologies. He holds a degree in Physics from Insubria University and a Ph.D. from the University of Milan, where his doctoral work focused on scintillating fiber vertex detectors for CERN's Antiproton Decelerator facility. At PSI, he leads detector development projects for synchrotron and free-electron laser applications. His research centers on advancing X-ray detector technology, including: Developing next-generation integrating pixel/strip detectors (JUNGFRAU, GOTTHARD) Improving frame rates, noise performance, and radiation hardness Exploring novel detector concepts for XFEL/synchrotron applications Enabling new experimental capabilities in structural biology and materials science Mozzanica's 135+ publications focus on X-ray detector innovation, with recent work emphasizing: Hybrid pixel detector optimization for 4th-generation light sources On-chip digitization and charge transport modeling High-speed data acquisition systems Applications in crystallography, spectroscopy, and phase-contrast imaging As principal developer of the JUNGFRAU detector, he oversees: ASIC design, testing, and characterization Readout electronics and firmware development Module production and supply chain management Commissioning at SwissFEL endstations
Cheng Zhang is an Associate Professor (with Tenure) in Information Science and a Field Member in Computer Science at Cornell University. He directs the Smart Computer Interfaces for Future Interaction (SciFi) Lab , focusing on integrating human-centered AI with advanced sensing technologies to empower everyday wearables. Ph.D. in Computer Science, Georgia Institute of Technology (2020) M.S. in Software Engineering, Chinese Academy of Sciences B.S. in Software Engineering, Nankai University His research examines how to solicit information on and around the human body to address real-world challenges in interaction, health sensing, and activity recognition. He builds novel sensing systems spanning hardware prototypes, algorithm design (machine learning and physics-based modeling), and high-impact applications in accessibility and health. Article Trends : His recent work includes low-power, minimally intrusive wearables (e.g., EchoForce for muscle activity tracking, Ring-a-Pose for hand poses, SeamFit for smart clothing) using acoustic sensing and machine learning. The 15 most recent articles span 2025–2023, with applications in silent speech, authentication, and pose estimation. Scientific Awards : NSF CAREER Award Ubicomp 10-Year Impact Award Best Paper Honorable Mentions at ISWC’24 and ISWC’23 Advising : Mentored Ph.D. students like Ruidong Zhang (Qualcomm Fellowship recipient) and Ke Li, with research featured in Cornell Chronicle and IEEE Spectrum .
Aravind Machiry is an Assistant Professor at Purdue University's Electrical and Computer Engineering Department and a founding member of the Purdue Systems and Software Security (PurS3) Lab . His research focuses on system security, particularly vulnerability detection, prevention, and secure system development using static/dynamic program analysis, fuzzing, type systems, and machine learning. Designing practical solutions for software and embedded system security Recipient of NSF CAREER and Amazon Research awards Active participant in SPLASH 2025 as OOPSLA Review Committee member His recent work includes automated vulnerability detection in embedded software, spatial memory safety enhancements, and security analysis of GitHub workflows. He has received recognition for his research through multiple distinguished paper awards and industry funding. Selected scientific awards include NSF CAREER Award (2024) Amazon Research Award (2022) Test of Time Award at FSE 2023 for DynoDroid Distinguished Paper Award at OOPSLA 2022 for 3c Qualcomm Innovation Fellowship (2025) His research team has developed frameworks like ARGUS for taint analysis of CI/CD workflows and FuzzUEr for UEFI interface fuzzing, discovering hundreds of critical vulnerabilities in open-source projects and thousands of command injection flaws in GitHub repositories.
Andrea Continella is an Associate Professor at the Faculty of Electrical Engineering, Mathematics and Computer Science of the University of Twente, where he contributes to the International Secure Systems Lab (iSecLab). His research focuses on systems security, particularly embedded firmware security, Android app security, malware detection, and program analysis techniques for vulnerability discovery. Ph.D. in Computer Science and Engineering, Politecnico di Milano (cum laude) Postdoctoral Researcher, Computer Science Department, UC Santa Barbara Visiting Researcher, School of Computer Science, University of Sydney Key research contributions include: Developing automated analysis techniques for embedded firmware (KARONTE, ShieldFS) Creating privacy leak detection mechanisms for mobile applications Designing ransomware defense systems using self-healing filesystems Advancing IoT security through misconfiguration detection (S3 buckets) and protocol analysis Pioneering semi-supervised methods for network traffic fingerprinting (FlowPrint) Scientific awards: Dutch Cyber Security Best Research Paper Award 2024 Runner-up USENIX Security Distinguished Reviewer Award 2024 Professional activities: Keynote speaker on firmware security (2024) Member of IPN Cyber Security Special Interest Group Oral presentations on automated vulnerability research (2023)
Professor Carsten Rudolph serves as Deputy Dean at Monash University's Faculty of Information Technology and directs the Oceania Cyber Security Centre (OCSC). He holds a PhD in Information Security from Queensland University of Technology (2002) and a Diplom in Computer Science from Goethe University Frankfurt (1997). His interdisciplinary research focuses on cybersecurity foundations, including cryptographic protocols, AI-driven security, human factors, and national cybersecurity policy. Key areas include securing smart grids, digital health systems, and transnational energy networks. Notable contributions include establishing the OCSC, leading Pacific region cybersecurity maturity reviews with Oxford University, and advancing frameworks for firmware security in virtual power plants. He chairs major projects like RAI4IoE (Responsible AI for Energy) and Post-Quantum Cryptography initiatives. Teaching responsibilities include cybersecurity modules like FIT3173 and FIT3168. Rudolph's research outputs (137+ publications) emphasize phishing detection via AI, blockchain-based energy trading, and resilient smart grid systems. He collaborates internationally on policy development and has advised 12 major research projects funded by agencies like the U.S. Bureau of East Asia and Pacific Affairs.
Lianying Zhao is an Associate Professor in the School of Computer Science at Carleton University and serves as a Director of the Carleton Computer Security Lab (CCSL). His research focuses on low-level platform security, including hardware, firmware, hypervisor, and operating systems, with an emphasis on trusted computing, authentication, privacy preservation, and security metrics. He leads the CCSL research group, collaborating with interdisciplinary teams to address critical security challenges in IoT, cloud systems, and web applications. Education: Not explicitly listed in provided texts. Roles: CCSL Director, Research Supervisor, and Graduate Program Advisor. Dr. Zhao’s work spans hardware security improvements, firmware vulnerability analysis, and user-centric security metrics. Recent research highlights include studies on router configuration habits, tracker detection in web browsers, and CVSS score discrepancies. He has supervised numerous graduate students in cybersecurity domains, contributing to over 30 peer-reviewed publications since 2013. His lab affiliations include CCSL and CISL, where he collaborates on projects such as secure deletion frameworks, TLS validation vulnerabilities, and hybrid decision-making models for cloud security. Current research also explores cross-regional login throttling mechanisms and AI-driven vulnerability detection in embedded systems.
Professor Ahmed Hemani is a faculty member at the Division of Electronics and Embedded Systems, KTH Royal Institute of Technology, affiliated with the Digital Futures Faculty. He holds the role of PI for the project 'New Chip Architectures for Industrial Vision' and leads research in reconfigurable computing, memristor-based systems, and hardware acceleration for AI and edge computing. His work bridges theoretical computer science with practical VLSI design and embedded systems development. He actively contributes to cross-disciplinary initiatives at Digital Futures, a joint center with Stockholm University and RISE Research Institutes of Sweden focused on digital innovation. His research emphasizes scalable FPGA/HPC architectures, low-power neuromorphic systems, and optimization techniques for custom silicon solutions. Current projects include a Lego-inspired edge AI framework and memristor-driven MIMO acceleration. Teaching responsibilities span advanced courses in SOC design, digital system verification, and embedded systems. He supervises advanced-level degree projects across computer engineering and ICT innovation specializations, emphasizing hands-on hardware-software co-design methodologies. Recent publications highlight innovations in memristor applications, FPGA-based acceleration, and reconfigurable architectures for neural networks and bioinformatics. His work addresses challenges in dark silicon utilization, energy-efficient computation, and high-performance embedded systems.
