Prof. Julia Hearts is a Professor at the Technical University of Munich (TUM) , affiliated with the School of Natural Sciences . Her research focuses on biomedical imaging , particularly advancing X-ray computed tomography through phase-contrast and dark-field radiography for clinical and biological applications. Developing spectral detection techniques to enhance diagnostic accuracy Quantitative imaging for element-specific parameter extraction Utilizing synchrotron radiation and standard X-ray tubes Her recent publications demonstrate expertise in dark-field radiography for lung and breast imaging, phase-contrast tomography for tissue characterization, and multi-spectral X-ray analysis for material decomposition. Collaborative work spans oncology , pulmonology , and materials science . Contact: julia.herzen@tum.de
Murat Arcak is a Professor of Electrical Engineering and Computer Sciences and Mechanical Engineering at the University of California, Berkeley, holding the Robert M. Saunders Endowed Chair in the College of Engineering. His research spans control theory, autonomous systems, and multi-agent systems with applications in transportation, energy, and biology. Dr. Arcak received his Ph.D. in Electrical Engineering from the University of California, Santa Barbara in 2000, following an M.S. from the same institution in 1997 and a B.S. from Bogazici University in Istanbul, Turkey in 1996. His research interests focus on developing scalable control design and verification methods for complex systems with many interconnected components, nonlinear dynamics, and learning capabilities. He has made significant contributions to control theory, particularly in areas like reachability analysis, dissipative systems, and compositional verification methods. His work bridges theoretical advances with practical applications in transportation systems, energy networks, and biological systems. A leading researcher in control systems, Dr. Arcak's recent publications demonstrate a strong focus on data-driven approaches for system verification, synthetic biology applications, and formal methods for traffic control. His research combines mathematical rigor with practical implementation, often developing novel theoretical frameworks that address real-world engineering challenges. CAREER Award from the National Science Foundation (2003) Donald P. Eckman Award from the American Automatic Control Council (2006) Control and Systems Theory Prize from SIAM (2007) Antonio Ruberti Young Researcher Prize from IEEE Control Systems Society (2014) Brockett-Willems Outstanding Paper Award (2021) IFAC Fellow (2020) IFAC Automatica Paper Prize (2020) CSS Transactions on Control of Network Systems Outstanding Paper Award (2017) Electrical Engineering Award for Outstanding Teaching (2014) CSS Antonio Ruberti Young Researcher Prize (2014) IEEE Fellow (2012) SIAM Activity Group Control and Systems Theory Prize (2007) Dr. Arcak has advised numerous graduate students and postdoctoral researchers, though specific names are not listed in the available information. His research has been supported by various grants from the National Science Foundation and other funding agencies, enabling his work on control theory and applications across multiple domains. He is affiliated with several research centers at UC Berkeley including the Berkeley Artificial Intelligence Research Lab (BAIR), Berkeley Deep Drive (BDD), the Center for the Theoretical Foundations of Learning, Inference, Information, Intelligence, Mathematics and Microeconomics at Berkeley (CLIMB), the Institute of Transportation Studies (ITS), and Partners for Advanced Transit and Highways (PATH).
Professor Francois Ladouceur is a distinguished academic at the University of New South Wales (UNSW), where he serves in the Faculty of Engineering, specifically within the School of Electrical Engineering and Telecommunications. With a career spanning over three decades, Professor Ladouceur has established himself as a leading expert in photonics, optical engineering, and neural interfaces. His educational background includes: Ph.D. in Optical Communication from The Australian National University (1992) Masters in Solid State Physics from École Polytechnique, Montréal, Canada (1987) B. Eng. in Engineering Physics from École Polytechnique, Montréal, Canada (1985) Professor Ladouceur's research spans several cutting-edge areas in photonics and optical engineering. His work focuses on integrated optics, silica and diamond-based photonics, optical sensing networks, and photonics-based brain/machine interfaces. He has made significant contributions to both fundamental waveguide theory and applied integrated optics, introducing innovative approaches to waveguide path design that have improved the size and ease of design of integrated optics devices. His recent work has particularly emphasized the development of liquid crystal-based optical electrodes for neural interfacing and brain/machine interfaces. Analysis of his recent publications reveals a strong trend toward biomedical applications of photonics, particularly in neural interfaces and optrode technology. His research has evolved from fundamental optical engineering to practical applications in healthcare, with a focus on developing novel optical sensing technologies for electrophysiological measurements. The interdisciplinary nature of his work combines optical engineering, materials science, and biomedical engineering to create innovative solutions for neural interfacing. Professor Ladouceur has secured significant research funding through multiple prestigious grants: ARC Discovery (DP200102825): "A Multi-Optrode Array for Closed-Loop Bionics" ($495k) NHMRC Ideas Grant (APP2002282): "Re-engineering the Future of Electrophysiological Measurements" ($732k) ARC Discovery 2016 (DP160104625): "Design of an optrode for next generation brain-machine interfaces" ($457.6k) CRC Project 2016: "High performance optical telemetry system for ocean monitoring" ($1,014,320) US Office of Naval Research: "Multi-Optrode Array for Neural Interfacing" (US$360,000) Professor Ladouceur has extensive experience in translating research into practical applications, having founded Bandwidth Foundry Pty Ltd after raising approximately $20 million from private and public sources. His work bridges the gap between academic research and commercial applications, with a particular focus on developing novel hybrid opto-electronics devices from initial design through to commercial realization. He collaborates extensively with researchers across disciplines, particularly with Professor Nigel Lovell and other colleagues in biomedical engineering. His laboratory focuses on developing optical technologies for neural interfaces, with current projects including multi-optrode arrays for brain-machine interfaces, optical telemetry systems for various sensing applications, and diamond-based photonic structures. The research group maintains strong connections with industry partners and defense organizations, applying photonics solutions to real-world problems in healthcare, mining safety, and ocean monitoring.
Yan Huang is an Associate Professor in the Department of Software Engineering and Game Development at Kennesaw State University (KSU). His work bridges Federated Learning (FL) and Cybersecurity Education , with a focus on personalization and privacy in distributed systems. Research spans Machine Learning , Extended Reality (XR) , and Data Privacy . He has served as Editor of WCMC and Program Co-Chair for CyberSciTech 2020-2024. Research Trends: Recent publications emphasize Federated Learning for non-IID data, VR-based Cybersecurity Education , and Privacy-Preserving Algorithms in IoT and social media analytics. Key subfields include personalized learning architectures, graph learning, and game-theoretic privacy frameworks. Scientific Awards: Excellent Paper Award (Tsinghua Science and Technology, 2021) Best Paper Award (Future Generation Computer Systems, 2019) Best Paper Awards at IEEE SmartWorld 2021, COCOA 2019, and WASA 2019 Grants: Led over $600,000 in NSF and NSA-funded projects, including VR cybersecurity education for K-12 and XR engineering curricula. His lab recruits VR/AR Research Assistants via industry partnerships.
Mohsen Heidari is an Assistant Professor in the Department of Computer Science at Indiana University, Bloomington. He is affiliated with the IU Quantum Science and Engineering Center (QSEc) and the NSF Center for Science of Information (CSoI). He previously held positions as a Visiting Assistant Professor at Purdue University and as a Postdoctoral Research Associate at CSoI. Ph.D. in Electrical Engineering (2019) and M.Sc. in Applied Mathematics (2017) from the University of Michigan His research focuses span quantum computing, theoretical machine learning, and information theory. Key themes include: Quantum algorithm design and sample complexity Fourier-based learning frameworks Quantum-classical duality in learning problems Information-theoretic approaches to biological systems Article trends show a strong emphasis on quantum-classical learning intersections (6/15 papers), Fourier analysis applications (5/15), and information-theoretic foundations (12/15). Notable venues include NeurIPS, IEEE Transactions, and ISIT. He directs research involving: Quantum Neural Network development Quantum measurement simulation Quantum data compression techniques Quantum algorithm implementation constraints
Prof. Vahid Jamali is an Assistant Professor and Head of the Resilient Communication Systems Group at the Technical University of Darmstadt, Germany. His research focuses on resilient communications, 6G wireless systems, bio-inspired molecular communication, and reconfigurable intelligent surfaces (RIS). He holds a Doctoral Degree from Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany, and has served as a postdoctoral researcher at Princeton University and FAU. Education PhD in Communication Systems, FAU (2019) Visiting Researcher at Stanford University (2017) Research Assistant at FAU's Institute for Digital Communications (2013-2019) Research Interests Resilient Networks : Emergency networks, RIS-based systems, and resilience-by-design architectures. Wireless Innovations : 6G technologies, holographic MIMO, and joint communication-sensing systems. Bio-inspired Systems : Molecular communication modeling using biological principles like diffusion and chemical reactions. Recent Work Trends His 2024-2025 publications emphasize RIS optimization (e.g., temperature-aware phase shifts, fast beam switching) and molecular communication (e.g., Poisson channel identification, bio-inspired receiver designs). Emerging themes include AoI-based RIS reconfiguration and integrated sensing-communication-powering (ISCAP) for IoT. Lab Activities He leads the Resilient Communication Systems Group, exploring cutting-edge RIS hardware (e.g., liquid crystal implementations) and theoretical foundations for future wireless systems.
Xiaoning Ding is an Associate Professor in the Department of Computer Science at New Jersey Institute of Technology (NJIT). His research focuses on virtualization, multicore computing, cloud infrastructure optimization, and mobile systems. He leads projects addressing challenges in nested virtualization, memory management, and cache conflicts in distributed and cloud environments. Key research interests include optimizing task scheduling in cloud VMs, reducing TLB misses through huge page strategies, and mitigating interference in multi-tenant GPU clouds. His work on page placement mechanisms and dynamic page coalescing aims to enhance virtualized cloud performance. Ding has received federal funding, including an NSF grant for virtualization research in heterogeneous memory hierarchies (2016–2019). His research outputs span over 74 publications, with notable contributions in EuroSys, IEEE Transactions, and conferences like PACT. Media coverage highlights his studies on cloud computing and collaborative mobile systems, such as parking assignment algorithms. Beyond technical contributions, Ding advises students in interdisciplinary projects, exemplified by collaborations with Applied Math majors on cloud computing challenges.
Dr. Yen-Ting (Allen) Yeh is an Assistant Professor in the Department of Computer Science at the University of Saskatchewan, where he leads research in Human-Computer Interaction focusing on mobile interaction techniques, collaborative tools, and creative technologies. PhD, Cheriton School of Computer Science, University of Waterloo MS, Graduate Institute of Networking and Multimedia, National Taiwan University His research explores physical and cognitive human capabilities through: Innovative phone interaction methods (folding, dexterous gestures, side-touch expansion) Collaborative writing environments with privacy controls Creativity augmentation systems for 3D modeling Augmented reality and interactive fabrication tools Recent publications demonstrate strong focus on: Acoustic input techniques using finger snapping Motion-based creative reflection tools Dynamic gesture recognition systems Collaborative editing comfort optimization Scientific recognition includes: ACM Creativity and Cognition 2021 Honorable Mention The research group at the University of Saskatchewan's HCI Lab actively seeks students interested in phone interactions, human factors, AR/VR, collaborative tools, and creative arts applications.
Kristin Y. Pettersen is a Professor at the Norwegian University of Science and Technology (NTNU) in the Department of Engineering Cybernetics, Faculty of Information Technology and Electrical Engineering. She holds a PhD and MSc in Engineering Cybernetics from NTNU and serves as an Adjunct Professor at the Norwegian Defence Research Establishment (FFI). She co-founded and led Eelume AS as its first CEO. PhD in Engineering Cybernetics, NTNU MSc in Engineering Cybernetics, NTNU Her research focuses on nonlinear control theory, motion control of mechanical systems, and marine robotics. Key areas include autonomous vehicles, underactuated systems, and cooperative control. Her recent work involves snake robotics, vehicle-manipulator systems, and safety-critical control algorithms. Her publications demonstrate trends in marine robotics , nonlinear control systems , autonomous navigation , formation control , and adaptive algorithms . Emerging topics include energy-shaping control , extremum-seeking optimization , and task-priority frameworks for complex robotic systems. 2025: Norwegian Academy of Science and Letters (DNVA) 2020: ERC Advanced Grant 2017: IEEE Fellow 2016-2021: Board member, Eelume AS 2013-2023: Key scientist, NTNU AMOS She has supervised 30 PhD graduates and currently mentors 16 PhD candidates. Her grants include ERC PoC UR4energy (€150k), ERC AdG CRÈME (€2.5M), and CAROS (NOK 45M) for subsea autonomy. She leads teams at NTNU's Applied Underwater Robotics Laboratory and contributes to the Cluster of Excellence IntCDC.
Tasos Dagiuklas is a Professor in the Department of Computer Science and Technology within the School of Engineering and Technology at the University of Bedfordshire. With over 168 publications spanning from 1995 to 2025, he has established himself as a leading researcher in telecommunications and network systems. His extensive publication record demonstrates continuous scholarly contribution across multiple decades in the field. Professor Dagiuklas' research focuses on wireless communications, edge computing, 5G/6G networks, quality of experience (QoE), and federated learning . His work bridges theoretical networking concepts with practical applications, particularly in multimedia delivery and security. He has developed significant expertise in video streaming optimization, network security mechanisms, and resource management in emerging network architectures. His research consistently addresses the evolving challenges of modern communication systems, with recent work increasingly focusing on AI integration in networking. Analysis of his recent publications (2023-2025) reveals a strong trend toward edge computing, federated learning, and security applications in next-generation networks. His work demonstrates a strategic shift from traditional networking concerns to more complex systems involving AI integration, energy efficiency, and heterogeneous environments. The publications show consistent collaboration with researchers across multiple institutions, with particularly strong partnerships with Muddesar Iqbal, Ilias Politis, and Stavros Kotsopoulos. Professor Dagiuklas has made substantial contributions to the academic community through his extensive publication record in high-impact venues including IEEE journals and conferences. His work has evolved from foundational networking research to cutting-edge investigations of AI-enhanced communication systems, reflecting the broader trajectory of the field itself. His research demonstrates both technical depth in specific networking challenges and breadth across multiple application domains.
Bo An is a President's Chair Professor and Head of the Division of Artificial Intelligence at the College of Computing and Data Science , Nanyang Technological University, Singapore . He also holds a courtesy appointment as Professor at the School of Physical & Mathematical Sciences and serves as Director of the Centre of AI-for-X. Previously, he was a Nanyang Assistant Professor (2014-2018), Associate Professor at the Chinese Academy of Sciences (2012-2013), and Postdoctoral Researcher at the University of Southern California (2010-2012). His academic journey began with B.Sc. and M.Sc. degrees from Chongqing University, followed by a Ph.D. in Computer Science from the University of Massachusetts, Amherst (advised by Victor Lesser). Research Interests : Artificial Intelligence Multiagent Systems Computational Game Theory Reinforcement Learning Automated Negotiation Optimization Research Impact : Applications in infrastructure security (deployed by US Coast Guard and Federal Air Marshals), e-commerce, sensor networks, and financial technology. Over 150 publications in top venues like AAMAS, IJCAI, AAAI, ICML, NeurIPS, KDD, and ACM/IEEE Transactions. Scientific Recognition : 2010 IFAAMAS Victor Lesser Distinguished Dissertation Award 2012 INFORMS Wagner Prize 2018 & 2022 Nanyang Research Awards 2017 Microsoft Collaborative AI Challenge IEEE Intelligent Systems 'AI's 10 to Watch' (2018) Leadership Roles : Editor-in-Chief of IEEE Intelligent Systems, Associate Editor for AIJ, JAAMAS, and ACM Transactions. Served as General Co-Chair for AAMAS'23 and Program Chair for IJCAI'27.
Hao Yang is an Assistant Professor in the Department of Civil and Systems Engineering at Johns Hopkins University, with dual affiliations at the Johns Hopkins Data Science and AI Institute and the Johns Hopkins Institute for Assured Autonomy. His research develops Trustworthy Machine Learning methods to enhance urban mobility systems, focusing on traffic safety, equity, and sustainability through ethical AI and human-machine cooperative systems. Yang earned dual bachelor's degrees in Electrical and Computer Engineering from Beijing University of Posts and Telecommunications and the University of London, followed by a Ph.D. in Civil Engineering (Transportation) from the University of Washington. His educational background bridges telecommunications, electrical engineering, and transportation systems. His research integrates spatio-temporal modeling, assured autonomous systems, and multimodal representation learning to address transportation equity and safety. Key projects include edge-AI-powered traffic surveillance, real-time crash identification, and cooperative signal assistance for vulnerable road users. His work emphasizes ethical AI deployment in cyber-physical infrastructure to create sustainable urban mobility solutions. Recent publications reveal a strategic shift toward large language models and multimodal AI for transportation challenges, with strong emphasis on explainability, reliability, and equity in traffic crash prediction, flow forecasting, and autonomous driving systems. This evolution demonstrates his commitment to adapting cutting-edge AI for real-world transportation problems. Yang's scientific contributions have earned significant recognition: Michael Kyte Outstanding Student of the Year Award (2022) High-Value Research Award from AASHTO (2022) Best Paper Award from TRB Information Systems Committee (2023) Best and Outstanding Dissertation Awards (2024) IEEE DTPI Outstanding Paper Award (2022) TRANSFOR22 Data Competition 2nd place (2022) ASCE Bridges Photo Contest First Place (2021) He actively mentors graduate researchers and seeks 2-3 PhD students for Fall 2025 to advance trustworthy AI in transportation. His research is supported by NSF, USDOT, and AASHTO grants including the Real-Time Truck Parking Information System project that received the High-Value Research Award. Current work focuses on edge-AI for traffic safety and multimodal data integration. Yang leads research within Johns Hopkins' Data Science and AI Institute and Institute for Assured Autonomy, collaborating with Transportation Research Board committees. His lab develops real-time perception systems using edge computing and representation learning, with active projects on non-motorized user safety and equitable traffic management for people with disabilities.
Prof. Ilia Polian serves as Head of the Institute of Computer Engineering and Chair of the Hardware-Oriented Computer Science (HOCOS) department at the University of Stuttgart. His leadership spans research, teaching, and institutional coordination across multiple high-impact projects. Prof. Polian's research focuses on developing circuit and system architectures based on both traditional and novel principles, including neuromorphic, stochastic, and approximate architectures. His second major research focus is systematic design methodology and design automation, with particular emphasis on safety and reliability properties of developed systems. Current research directions include quantum computing engineering, secure mixed-signal neural networks, and resource-efficient stochastic circuits for near-sensor computing applications. His recent publications demonstrate strong trends in quantum computing (particularly circuit partitioning and compilation for multi-QPU architectures), hardware security (including memristive cryptographic implementations), and AI-driven approaches to hardware testing and reliability. These works bridge fundamental computer architecture research with practical industrial applications. University of Stuttgart's Publication Prize for Paper on Partitioning of Quantum Circuits Prof. Polian actively supervises doctoral students including Devanshi Upadhyaya, and leads significant research grants such as the DFG Priority Program Nano Security which he coordinates. His department offers numerous thesis and research opportunities for students interested in cutting-edge hardware research. The Hardware-Oriented Computer Science department maintains strong collaborations with industry partners including IBM, Infineon Technologies, and Advantest, as well as academic institutions through the IQST Graduate School and QuantumBW initiatives.
Professor John G Rarity serves as Professor of Optical Communication Systems within the School of Electrical, Electronic and Mechanical Engineering at the University of Bristol, where he leads research at QET Labs and the Bristol Quantum Information Institute. His work spans quantum communication, photonics, and quantum information systems with significant contributions to quantum cryptography and sensing. Research focuses on quantum communication networks , quantum cryptography , and quantum sensing applications . His fingerprint reveals dominant expertise in Quantum Dot Physics (100%), Photonics Physics (94%), Photonic Crystal Material Science (60%), and Quantum Cryptography (48%). Current work emphasizes entanglement distribution, counterfactual communication protocols, and quantum-enhanced sensing for environmental monitoring. Recent publications (2025) demonstrate leadership in multi-node quantum networks, deterministic teleportation, and methane sensing via quantum techniques. His 438 research outputs show consistent focus on practical quantum systems integration, particularly in overcoming classical-quantum channel coexistence challenges in fiber networks. Principal Investigator for 75 projects including active EPSRC grants EP/N00762X/1, EP/R022054/1, and EP/R023018/1 Supervised 36 research students Developed quantum communication systems for CubeSat deployment Pioneered quantum sensing applications for greenhouse gas detection Rarity actively collaborates across international quantum research networks, with recent work involving hollow-core fiber quantum channels, NV-center quantum sensors, and photonic integrated circuits for scalable quantum systems. His lab maintains strong industry partnerships with BT Research and optical communications firms.
Amar U. Kishan, MD , a tenure Professor at the David Geffen School of Medicine, UCLA , serves as Executive Vice Chair for the Department of Radiation Oncology and as Chief of the Genitourinary Service since 2019. His clinical expertise focuses on radiation treatment of prostate and bladder cancers , with pioneering work in stereotactic body radiation therapy (SBRT) and image-guided radiotherapy . Dr. Kishan graduated magna cum laude from Harvard Medical School after dual BA degrees at UC Berkeley in Molecular and Cell Biology and Public Health, followed by residency at UCLA and internship at Scripps Mercy Hospital . Education : Harvard Medical School (MD, 2012), UC Berkeley (BA in Molecular/Cell Biology & Public Health) Awards : Leonard Tow Humanism in Medicine (2021), UCLA Exceptional Physician (2024), Super Doctors® Rising Stars (2020-2024) Dr. Kishan leads translational research connecting radiation oncology with genitourinary cancer biology. His 310+ publications in journals like JAMA , Lancet Oncology , and European Urology emphasize radiation technology innovations , including MRI-guided SBRT and adaptive radiation therapy. Key trials he spearheads include ILLUSION (CT-guided SBRT) and HEATWAVE (apalutamide + SBRT). Major funding sources include National Institutes of Health , Department of Defense , and Prostate Cancer Foundation . His work has redefined prostate cancer treatment paradigms , demonstrating that high-dose radiation can match surgery in aggression cases, while multi-modal approaches improve survival rates. Dr. Kishan also contributes to re-irradiation protocols and radioresistance proteogenomics , advancing precision oncology. Key Grants : NIH, DoD, PCF, ASTRO Clinical Trials : ILLUSION, HEATWAVE, PET imaging-based radiation targeting
