Prof. Dr. Günther Dissertori is a Full Professor and Rector of ETH Zurich, where he oversees teaching and academic affairs. His academic journey began at the University of Innsbruck, followed by a doctoral position at CERN, and he joined ETH Zurich as an Assistant Professor in 2001 before becoming a Full Professor in 2007. Academic Role: Full Professor of Particle Physics Institutional Leadership: Rector of ETH Zurich (since 2022) Contact: guenther.dissertori@sl.ethz.ch Research Interests: Dissertori's work spans Particle Physics and Experimental Physics , notably contributing to the CMS experiment at CERN, which was instrumental in the Higgs boson discovery. His group also developed cost-effective PET devices, leading to the spin-off Positrigo AG . Research keywords include Detector Development , Medical Imaging , and Quantum Physics . Teaching Excellence: Recognized with multiple Golden Owl awards (2005–2020) and the Credit Suisse Award for Best Teaching (2013), Dissertori is celebrated for his pedagogical impact in the Department of Particle Physics. Scientific Contributions: His publications include advancements in CMOS technology, quantum dynamics, and medical applications, reflecting interdisciplinary expertise in high-speed electronics, environmental science, and architectural history.
Robert MacCurdy is an Assistant Professor at the Department of Mechanical Engineering, University of Colorado Boulder . He leads the Matter Assembly Computation Lab (MACLab) focused on automating robot design and fabrication. His research bridges computational design and advanced manufacturing to create "robots that walk out of the printer." The lab develops tools like OpenVCAD , an open-source volumetric multi-material geometry compiler.
Achuta Kadambi, Ph.D., is an Associate Professor at UCLA in Electrical Engineering and Computer Science, leading an interdisciplinary research group focused on AI, computational imaging, and bias mitigation in medical technologies. He recruits PhD students from EE, CS, and Bioengineering departments and has commercialized research through two California-based companies. His research investigates the intersection of physics and artificial intelligence, with a focus on unbiased low-level vision systems. Current projects explore how light transport interacts with human skin variations to identify and correct imaging biases in facial recognition and medical devices. His work has produced over 70 patents, with 30+ issued, and a textbook Computational Imaging (MIT Press, 2022). NSF CAREER Award (2021) for light transport bias research DARPA Young Faculty Award (2021) for AI and medical imaging innovations ARO Young Investigator Program (2021) for computational sensing IEEE-HKN Under 35 Award (2022) for inclusive EECS inventions Forbes 30 Under 30 recognition His recent publications focus on polarization imaging, 3D Gaussian splatting, synthetic data generation for healthcare, and bias mitigation in machine learning. Collaborations with UCLA medical school faculty, including Dr. Laleh Jalilian, aim to deploy these innovations in clinical settings. Current teaching includes ECE 149: Foundations of Computer Vision (Fall 2024, Spring 2025) and ECE 102: Signals and Systems (Winter 2024).
Professor Simon Godsill MA PhD FIET FIEEE is a University Professor of Statistical Signal Processing in the Department of Engineering at the University of Cambridge. He heads a research team specializing in statistical signal processing, digital audio restoration, and Bayesian inference. His work addresses the processing and analysis of digital speech, audio, tracking systems, and financial datasets, with a focus on probabilistic modeling and computational methods. Research interests include statistical signal processing , degraded signal restoration , and Bayesian computational methods . Recent publications emphasize Gaussian processes, variational inference, and multi-object tracking for applications in audio enhancement and financial data analysis. He co-founded the audio remastering company CEDAR Audio Ltd in 1988. Scientific awards: Fellow of the Institution of Engineering and Technology (FIET) Fellow of the Institute of Electrical and Electronics Engineers (FIEEE) Outside academia, he enjoys singing, cricket, piano/organ playing, and running. His team at Cambridge's Engineering department focuses on robust tracking algorithms and signal enhancement techniques.
Prof. Jean-Philippe Thiran is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), where he serves as Director of the Signal Processing Laboratory (LTS5) and Director of the Institute of Electrical and Micro Engineering. He also maintains a part-time Associate Professor position with the Department of Radiology of the University Hospital Center (CHUV) and University of Lausanne (UNIL). Born in Namur, Belgium in 1970, he received his Electrical Engineering degree and PhD from the Université catholique de Louvain (UCL), Belgium, in 1993 and 1997 respectively. He joined EPFL in 1998 and has established himself as a leading researcher in computational imaging. His research focuses on computational imaging , with significant contributions to medical image analysis (particularly diffusion MRI, ultrasound imaging, and digital pathology) and computer vision . His recent work integrates advanced modeling, simulation, and machine learning techniques to extract microscopic tissue information from macroscopic MRI signals. This approach combines hyper-realistic synthetic tissue models, advanced Monte-Carlo simulations, and ML-based estimation techniques for brain microstructure analysis with potential applications to other tissues. Senior Member of IEEE Fellow of the European Association for Signal Processing (EURASIP) Prof. Thiran has authored or co-authored 1 book, 9 book chapters, 250 journal papers and over 270 peer-reviewed conference papers, and holds 12 international patents. He previously served as Co-Editor-in-Chief of the Signal Processing journal (2001-2005) and associate editor of IEEE Transactions on Image Processing. He has chaired major conferences including EUSIPCO 2008 and IEEE ICIP 2015. His laboratory at EPFL brings together interdisciplinary researchers to develop innovative imaging techniques that bridge macroscopic measurements and microscopic tissue properties, with significant potential for medical diagnostics and treatment planning applications.
Nasir Memon is a Professor of Computer Science and Engineering at the New York University Tandon School of Engineering and concurrently serves as the Dean of Engineering at NYU Shanghai. He has been a faculty member at NYU Tandon since September 1998. Memon is a co-founder of NYU's Center for Cyber Security (CCS) and NYU Abu Dhabi, and the founder of key initiatives such as the OSIRIS Lab, CyberSecurity Awareness Week (CSAW), the NYU Tandon Bridge program, and the Cyber Fellows program. His work focuses on advancing cybersecurity education and addressing systemic biases in AI-driven systems. Education: Ph.D., Computer Science, University of Nebraska Master of Science, Mathematics, Birla Institute of Technology and Science (BITS), Pilani Bachelor of Engineering, Chemical Engineering, BITS, Pilani Research Interests: Media Forensics and Authentication Biometric Security and Privacy Data Compression and Privacy-Preserving Techniques Network Security and Incident Response AI Ethics and Fairness in Machine Learning Cybersecurity Education and Workforce Development Awards and Honors: IEEE Fellow (2010) SPIE Fellow (2014) Jacobs Excellence in Education Award (2002) NSF CAREER Award (1997) Advising and Grants: Advises Ph.D. students like Anubhav Jain and Govind Mittal, and mentors Master’s students such as Rishit Dholakia. Recipient of NSF grants and funding from NYU Abu Dhabi and Indiana University Bloomington for projects like computational tools for fact-checking and AI-driven bias mitigation. Labs and Teams: Directs the OSIRIS Lab, a leading research group in cybersecurity and AI. Leads initiatives at the NYU Center for Cybersecurity (CCS) and collaborates with NYU Abu Dhabi’s Center for Cyber Security.
Gert Cauwenberghs is a Professor of Bioengineering at the University of California San Diego (UCSD), affiliated with the Jacobs School of Engineering. He co-directs the Institute for Neural Computation and holds a visiting professorship at MIT. His research focuses on neuromorphic engineering, energy-efficient neural interfaces, and wearable biosensors. Key contributions include silicon-based adaptive neural circuits, implantable neural recording systems, and in-ear biosensing devices. Education: M.Eng. in Applied Physics (University of Brussels, 1988), M.S. and Ph.D. in Electrical Engineering (Caltech, 1989–1994). Prior roles include Professorships at Johns Hopkins University and Visiting Professor at MIT. Research Interests: Biomedical integrated circuits, neuromorphic computing, brain-machine interfaces, and energy-efficient neural systems. His work bridges neuroengineering and clinical applications, emphasizing adaptive intelligence and low-power designs. Recent Work: Development of femtojoule-efficient neural chips, high-density neural interfaces, and closed-loop wearable systems. Projects include neurobench benchmarking frameworks and RRAM-based neuromorphic hardware. Awards: NSF Career Award (1997), ONR Young Investigator (1999), PECASE (2000), IEEE Distinguished Lecturer (2003–2004). Grants & Labs: Active in NIH and DoD-funded projects, co-directs the UCSD Institute for Neural Computation. Collaborates with industry on neural interface technologies. Labs/Teams: Cauwenberghs Lab at UCSD focuses on integrated neuroengineering systems, including neural recording systems and neuromorphic computing architectures.
Prof. Dr. Dennis Säring is a faculty member at the University of Applied Sciences Wedel , specifically affiliated with the School of Engineering. His academic and research activities focus on Deep Learning , Medical Image Analysis , and applications of Artificial Intelligence in healthcare and biomedical imaging. He has led seminars on Deep Learning topics and supervised student projects in Autonomous Driving at Audi's AADC 2018 competition. Research Highlights : Cardiovascular imaging, forensic age estimation via MRI, neural network-based bone segmentation, and cerebrovascular aneurysm analysis. Technical Expertise : Cardiac MRI, 3D/4D image processing, parametric mapping, and spatiotemporal data fusion. His recent publications (2018-2023) emphasize 3D MR segmentation for age assessment, CMR strain analysis in athletes, and T1/T2 mapping for myocarditis. Key collaborations include institutions like the University Medical Center Hamburg-Eppendorf and Wedler Hochschulbund, with funding for autonomous vehicle research. While no explicit scientific awards are listed, his work spans clinical cardiology, forensic radiology, and AI-driven medical diagnostics.
Prof. Raffaello D'Andrea is a Full Professor at ETH Zürich's Department of Mechanical and Process Engineering, affiliated with the Institute for Dynamic Systems and Control. His research focuses on bridging digital and physical worlds through robotics, control systems, and autonomous systems. He has pioneered work in aerial robotics, swarm systems, tactile sensing, and soft robotics. His philosophy emphasizes solving 'easy' problems with scalable, robust solutions, prioritizing simplicity and replicability. Key research areas include UAV navigation, distributed control, tactile sensor design, and fault-tolerant systems. He has founded multiple organizations and led roles as CTO/CEO, emphasizing cross-disciplinary innovation. His work has commercial applications in logistics, healthcare, and automation, driven by a belief in technology's role in improving human life. Notable projects include the Cubli robotic cube, aerial vehicle swarms, and optical tactile sensors for robotics. His lab emphasizes collaboration and team leadership, aiming to translate theoretical insights into practical, scalable technologies. Scientific awards: None explicitly listed in the provided texts. Advising and grants: No students listed in the provided texts; grants information not detailed. Labs/Teams: Leads research at ETH Zurich's Institute for Dynamic Systems and Control, collaborating with industry and academic partners globally.
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.
Michele Zorzi is a Professor of Telecommunications at the School of Engineering, University of Padova, Italy, where he has held a faculty position since 2003. He leads the SIGNET (Signal processing and Networking) Research Group, focusing on cutting-edge wireless networking challenges including mmWave communications and underwater networks. His extensive publication record exceeds 600 papers in top-tier journals and conferences, reflecting significant contributions to the field through both theoretical and experimental work. He received his Laurea Degree (1990) and Ph.D. (1994) in Electrical Engineering from the University of Padova. Prior academic appointments include Politecnico di Milano (1993-1996), University of California San Diego (1995-1998), and University of Ferrara (1998-2003), where he progressed from Associate Professor to full Professor. His educational trajectory demonstrates deep roots in Italian academia with international exposure. Professor Zorzi's research spans wireless communications and networking, with current emphases on mmWave networking for vehicular systems, underwater acoustic/optical communications, non-terrestrial networks, and AI-driven networking solutions. His group conducts experimental validations including at-sea trials for underwater systems and testbeds for vehicular networks. Key projects include PRATA for predictive QoS in autonomous driving and IoT-based environmental monitoring of the Venice Lagoon, demonstrating practical applications of theoretical work. Analysis of his 2022-2025 publications reveals strong trends in applying artificial intelligence to networking challenges across diverse environments. There is significant emphasis on vehicular networks (predictive QoS, teleoperated driving), underwater systems (acoustic/optical communications, AUV swarms), and satellite networks (Starlink integration, NTN security). Experimental validation in real-world scenarios like the Venice Lagoon monitoring project and underwater sea trials characterizes his applied research approach. His scientific accolades include: IEEE Fellow (2007) IEEE Communications Society Best Tutorial Paper Award (2008, 2019) Stephen O. Rice Best Paper Award (2018) Multiple best paper awards at IEEE conferences (2005-2020) As principal investigator for numerous European and US research projects plus 20+ industry-funded initiatives, Professor Zorzi has mentored over 35 PhD students and post-docs. Graduates now hold prominent positions at institutions including Stanford, UCSD, CTTC, and Huawei. His SIGNET group maintains active international collaborations and contributes to open-source networking tools via GitHub, demonstrating commitment to community engagement. The SIGNET Research Group, housed within the Department of Information Engineering, operates specialized experimental facilities for mmWave and underwater communications. Current initiatives include AI-based predictive QoS frameworks for vehicular networks, underwater optical communication systems using ultraviolet light, and large-scale IoT deployments for environmental monitoring. The group's GitHub presence indicates strong open-science practices, while recent sea trials confirm hands-on experimental capabilities beyond theoretical work.
Jae Eun Chung is a Professor in the Department of Communication Studies at Howard University's School of Communications. Her research focuses on new media technologies, their psychosocial impacts, and health communication, with a particular emphasis on community engagement and digital discourse. Ph.D. in Communication from the University of Southern California M.A. in Telecommunications from Indiana University at Bloomington Dr. Chung's work explores the intersection of social media and health, analyzing how digital platforms influence public health perceptions, patient-doctor interactions, and health equity. She has published extensively in journals like Journal of Communication , Computers in Human Behavior , and Health Communication , often employing community-based participatory research (CBPR) to address disparities in asthma care, maternal health, and HPV-associated cancer awareness. Recent publications highlight trends in leveraging social media for health interventions, examining misinformation dynamics during crises like the COVID-19 pandemic, and analyzing digital ecosystems. Her methodological approaches include network analysis, narrative studies, and assessments of digital engagement metrics. Howard University RCMI Grant: Enhancing recruitment of African-Americans and Hispanics in health research NSF HDR Grant: Collaborative research on data analytics for community enrichment PACRI Grant: Improving health outcomes for asthmatic children in public housing Bezos Earth Fund: Indoor environmental quality disparities in underserved communities Dr. Chung collaborates with interdisciplinary teams, including public health experts and data scientists, to advance health communication strategies. She has mentored students and researchers in projects analyzing social media's role in health promotion, digital privacy, and community-academic partnerships.
Sumeet Kumar Gupta is an Associate Professor in the Department of Electrical and Computer Engineering at Purdue University. His academic career spans from his current role to a prior Assistant Professorship at Pennsylvania State University (2014-2017) and an engineering position at Qualcomm Inc. (2012-2014). He holds a PhD in Electrical and Computer Engineering from Purdue University (2012), an M.S. from the same institution (2008), and a B.Tech in Electrical Engineering from IIT Delhi (2006). B.Tech, Electrical Engineering, IIT Delhi (2006) M.S., Electrical and Computer Engineering, Purdue University (2008) PhD, Electrical and Computer Engineering, Purdue University (2012) Dr. Gupta's research focuses on neuromorphic computing, low power variation-aware VLSI design in emerging nanotechnologies, device-circuit co-design, and nano-scale device modeling/simulations. His work addresses challenges in ferroelectric materials, crossbar arrays for deep neural networks, and energy-efficient AI hardware. Recent publications (2025-2024) highlight trends in: Ferroelectric HfO2/HZO thin films Compute-in-memory architectures Variability/stochasticity analysis Machine learning for device optimization Interconnect resistance/temperature effects AI hardware fault tolerance Scientific Awards & Recognitions: DARPA Young Faculty Award (2016) Early Career Professorship, Penn State (2014) 6th TSMC Outstanding Student Research Bronze Award (2012) Magoon Award (Purdue) Outstanding Teaching Assistant Award (Purdue, 2007) Intel PhD Fellowship (2009) His professional journey includes academic appointments at Purdue University (2020-present, Associate Professor) and Pennsylvania State University (2014-2017, Assistant Professor) after industry experience at Qualcomm Inc. (2012-2014). He maintains IEEE and EDS membership while publishing over 100 refereed works.
Lars Ulander is a Professor at Chalmers University of Technology specializing in radar remote sensing. His research focuses on synthetic aperture radar (SAR) signal processing, particularly for applications in forest biomass mapping and ground imaging using VHF/UHF-band systems. He is a key proposer for ESA's BIOMASS satellite mission (launching 2025) and leads the BorealScat project, utilizing a 50-meter tower-based tomographic radar to study boreal forest dynamics. His work spans radar system development, SAR tomography techniques, and environmental monitoring of forests and sea surface currents. Current research areas include vegetation water content estimation, bistatic radar configurations, and optimization of SAR data processing algorithms for multi-temporal analysis. Recent publications demonstrate expertise in P-band/L-band SAR for biomass retrieval, passive radar systems, and interferometric techniques. His articles investigate radar backscatter sensitivity to forest structure, moisture parameters, and seasonal changes, while contributing to mission design frameworks like SLAINTE and SESAME.
Amr Youssef is a Professor at the Concordia Institute for Information Systems Engineering, Concordia University. His research focuses on applied cryptography, network security, cyber-physical systems security, blockchain, and privacy. He has contributed extensively to securing smart grids, IoT devices, and web applications through cryptographic protocols and machine learning-driven solutions. His work addresses critical challenges in cybersecurity, including e-voting systems, fault-tolerant differential protection, and privacy-preserving communication protocols. He explores vulnerabilities in modern systems such as SSO permissions, JavaScript exploits, and stalkerware tools, while developing frameworks like MEGR-APT for APT detection and TEE-Receipt for non-repudiation. Youssef’s research integrates interdisciplinary approaches, combining cryptography with AI (e.g., vision transformers for power quality analysis) and leveraging trusted execution environments (TEE) for secure computing. His projects often involve collaboration with industrial standards (e.g., IEC 61850), emphasizing practical implementations in real-world systems.
