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James ShacklefordView profile

Associate Professor

• Medical Image Processing
• High Performance Computing
• Embedded Systems
• +2 more

James Shackleford serves as Associate Professor and Interim Associate Dean for Enrollment Management and Graduate Education in the Department of Electrical and Computer Engineering at Drexel University. His research bridges medical image processing, high performance computing, and emerging neuromorphic architectures with significant contributions to radiation therapy applications. Education: PhD in Electrical Engineering, Drexel University, 2011 MS in Electrical Engineering, Drexel University BS in Electrical Engineering, Drexel University Research Focus: Professor Shackleford's work centers on GPU-accelerated medical image registration (forming the core of the open-source Plastimatch software), real-time tumor motion management for radiation therapy, and digital spiking neuromorphic systems . His research integrates computer vision, machine learning, and embedded systems to solve clinical imaging challenges. Publication Trends: Recent work (2020-2024) reveals dual research trajectories: (1) advancing deformable image registration through CycleGAN-based domain adaptation for CT auto-segmentation in radiation oncology, and (2) pioneering neuromorphic computing with configurable hardware architectures, dataflow-based compilers, and resource-aware neural network mapping. These streams converge on high-performance solutions for medical imaging and efficient neural processing.

Pedram JohariView profile

Researcher

• Intra-body Communications
• Wireless Networking
• Internet of Medical Things
• +4 more

Pedram Johari serves as a Principal Research Scientist at Northeastern University's Institute for Wireless Internet of Things, working under Prof. Tommaso Melodia in the Department of Electrical and Computer Engineering within the College of Engineering. His research focuses on next-generation wireless communications with particular emphasis on medical applications and nanoscale networks. Dr. Johari earned his Ph.D. in Electrical Engineering from the University at Buffalo, State University of New York in 2018 under the supervision of Prof. Josep M. Jornet. Prior to joining Northeastern, he served as CTO of an IoT-tech startup in New York (2018-2019) and held academic positions at University at Buffalo as Adjunct Instructor and Research Assistant Professor (by courtesy appointment). His research spans four interconnected domains: Intra-body Communications and Networking focusing on nanoscale electromagnetic and optical communications within biological tissues; Internet of Medical Things developing wireless systems for healthcare applications; Low Power Wireless IoT creating energy-efficient communication protocols; and Vehicular Communications advancing cooperative driving systems. His work bridges theoretical modeling with practical implementation, often incorporating AI techniques for network optimization. Analysis of his recent publications reveals a strong trend toward digital twin technology for wireless networks, AI-enabled communication systems, and medical applications of nanoscale communications. His research increasingly integrates machine learning with traditional communication theory, particularly in Open RAN systems and seizure prediction technologies, demonstrating cross-disciplinary impact across engineering, computer science, and biomedical fields. Best Paper Award at IEEE Global Communications Conference (GLOBECOM) Best Short Paper Award at IEEE Vehicular Networking Conference (VNC) Best Presentation Award at IEEE Conf. on Computer Communications Workshops (INFOCOM WKSHPS) Dr. Johari actively contributes to academic service as a reviewer for numerous prestigious journals including IEEE Transactions on Wireless Communications, IEEE Transactions on Mobile Computing, and IEEE Internet of Things Journal. He has served on technical program committees for major conferences including IEEE/ACM CHASE and IEEE SECON. His teaching experience includes courses in programming, circuit analysis, and digital principles at University at Buffalo. As a key member of the Wireless Networks and Embedded Systems Lab at Northeastern University, Dr. Johari contributes to the Colosseum wireless network emulator project - recognized as the world's largest wireless network emulator. His work with the Institute for Wireless Internet of Things involves collaboration with industry partners to translate research into practical wireless communication solutions.

Ehat ErcanliView profile

Teaching Professor

• Computer Architecture
• Embedded System Design
• System Verification
• +3 more

Ehat Ercanli is an Associate Teaching Professor at Syracuse University, serving as the Associate Chair of Education and Operations. He holds a Ph.D. in Computer Engineering from Case Western Reserve University. His research focuses on optimizing embedded systems, computer architecture, system verification, and VLSI design automation. He has contributed to advancements in memory management, compiler optimization, and energy-efficient computing. Key research interests include embedded system design, task recomputation techniques for memory utilization, and database systems optimization. His work emphasizes practical applications in multi-core systems, low-power electronics, and compiler-driven performance improvements. His publications highlight trends in system-on-chip (SoC) optimization, shared private memory management, and energy consumption reduction strategies. Notably, his 2007 paper was ranked #3 in the ACM Digital Library’s Most Popular Papers. Dr. Ercanli’s contributions also extend to automated code generation for database applications and custom processor synthesis for image processing.

Taekwang JangView profile

Associate Professor

• Analog and Mixed-Signal Circuits
• Energy-Efficient Systems
• Wireless Sensor Networks
• +3 more

Prof. Taekwang Jang is an Associate Professor at the Department of Information Technology and Electrical Engineering, ETH Zürich. He leads the Energy Efficient Circuits and IoT Systems Group, focusing on analog and mixed-signal circuits for energy-constrained applications such as wireless sensor nodes and biomedical electronics. His research includes sensor interfaces, energy harvesters, power converters, and communication systems. He holds 15 patents and has authored over 80 peer-reviewed publications. Key awards include the 2024 IEEE Solid-State Circuits Society New Frontier Award and the SNSF Starting Grant. Educations: B.S. and M.S. in Electrical Engineering, KAIST (2006, 2008) Ph.D. in Electrical Engineering, University of Michigan (2017) Affiliations: Chair of IEEE Solid-State Circuits Society, Switzerland Chapter Associate Editor for Journal of Solid-State Circuits (JSSC) Research Interests: His work spans energy-efficient integrated circuits, biomedical interfaces, and IoT systems. Notable contributions include low-power keyword spotting ICs, ultra-low-noise amplifiers, and neural stimulation systems. He emphasizes practical applications in healthcare and wearable devices. Awards: 2024 IEEE Solid-State Circuits Society Distinguished Lecturer 2022 IEEE ISSCC Jan Van Vessem Award 2009 IEEE CAS Guillemin-Cauer Best Paper Award Advising & Grants: Supervises a team of researchers and has secured grants including the SNSF Starting Grant. His lab collaborates with institutions like the Competence Center for Rehabilitation Engineering and Science. Labs & Teams: Leads the Energy-Efficient Circuits and Intelligent Systems group at ETH Zurich, focusing on interdisciplinary projects at the intersection of circuits, systems, and biomedical engineering.

• Low-power Integrated Circuits
• Very Large Scale Integration (VLSI) Circuit Design
• Sensors and Data Acquisition Systems
• +8 more

Yusuf Leblebici is a Turkish academic and current President of Sabanci University (2018-present), reappointed in December 2022. He previously served as a Chair Professor and Director of the Microelectronic Systems Laboratory at EPFL, Switzerland (2002-2018), and held academic roles at Worcester Polytechnic Institute (1997-1999), Istanbul Technical University (1993-1997), and the University of Illinois at Urbana-Champaign (1991-2000). His career spans microelectronics, VLSI design, and neuromorphic systems. BSc and MSc in Electrical Engineering from Istanbul Technical University (1984, 1986) PhD in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign (1990) His research focuses on low-power integrated circuits , VLSI design , sensor interfaces , semiconductor modeling , and neuromorphic computing . He has co-authored over 400 scientific articles and seven books, including two internationally acclaimed textbooks. Scientific Awards : 2020 ECE Distinguished Alumni Award (UIUC) 2009 IEEE Fellow 2009 IEEE Distinguished Lecturer 1999 WPI Satin Distinguished Fellow Award 1995 Turkish TUBITAK Young Investigator Award He has graduated 58 PhD students and over 100 MSc students, and played a pivotal role in establishing Sabanci University's Microelectronics Program (1999-2002) and directing EPFL's Microelectronic Systems Laboratory (2002-2018). As Sabanci University President, he has enhanced global visibility, attracted international talent, and strengthened global collaborations.

Quanxi JiaView profile

Professor

• Materials Science
• Electronic Materials
• Energy Materials
• +4 more

Quanxi Jia is a SUNY Distinguished Professor, Empire Innovation Professor, and National Grid Professor of Materials Research at the University at Buffalo. He holds appointments in the Department of Materials Design and Innovation within the School of Engineering and Applied Sciences and serves as Scientific Director of the New York State Center of Excellence in Materials Informatics (CMI). Education: PhD in Electrical and Computer Engineering, University at Buffalo, 1991 MS in Electronic Engineering, Jiaotong University, Xian, China, 1985 BS in Electronic Engineering, Jiaotong University, Xian, China, 1982 Research Focus: Jia's work centers on advanced electronic and energy materials, particularly epitaxial thin films and heterostructures. His research investigates processing-structure-property relationships, monolithic integration of functional materials, and superconductors for quantum/energy applications. Key methodologies include pulsed laser deposition and polymer-assisted techniques, with emphasis on oxide heterostructures , memristive devices , and multiferroic systems for next-generation electronics. Publication Trends: Recent publications (2023-2025) reveal dominant focus on neuromorphic computing via resistive switching devices (58% of sampled works), superconducting thin films for quantum applications (20%), and strain-engineered oxide heterostructures (22%). His group pioneers HfO 2 -based artificial neurons, NbN superconducting films on CMOS platforms, and multiferroic membranes, demonstrating strong industry-academia translation potential. Scientific Recognition: Fellow of Los Alamos National Laboratory Fellow of Materials Research Society (MRS) Fellow of American Physical Society (APS) Fellow of American Ceramic Society (ACerS) Fellow of AAAS Fellow of IEEE Fellow of National Academy of Inventors (NAI) Leadership & Infrastructure: As CMI Scientific Director, Jia oversees New York's flagship materials informatics initiative integrating AI with experimental materials science. His prior directorship of DOE's Center for Integrated Nanotechnologies (Los Alamos/Sandia) established expertise in national lab collaboration. The group maintains 50+ U.S. patents and 500+ publications, with current work targeting quantum device integration and sustainable neuromorphic hardware. Research Ecosystem: The CMI hub connects Jia's team with industry partners (including National Grid) and national labs, facilitating rapid prototyping of energy materials. Current thrusts include machine learning-guided ferroelectric design, CMOS-compatible superconductors, and recyclable perovskite sensors, positioning the group at the semiconductor-energy nexus.

Stefano GregoriView profile

Professor

• Computer Engineering
• Integrated Circuit Design
• Analog and Mixed-Signal Systems
• +7 more

Stefano Gregori is a Professor at the University of Guelph's School of Engineering. He specializes in analog and mixed-signal integrated circuit design, with a focus on low-power systems, sensor networks, and microsystem integration. His research involves collaborations with industry leaders like STMicroelectronics and TSMC, emphasizing practical applications in IoT, energy efficiency, and biomedical devices. He holds a PhD and is a Professional Engineer (PEng). His work bridges theoretical design and real-world applications, such as secure cryptographic circuits and sustainable materials for biomedical composites. He actively supervises graduate students and has mentored numerous scholars, many of whom now work in leading tech companies like Qualcomm and Thales. Gregori's funding sources include NSERC, CMC Microsystems, and the Ontario Centres of Excellence. He emphasizes ethics in engineering, advocating for safety and environmental responsibility. His lab, located in Richards Building Room 3521, focuses on cutting-edge projects like energy-efficient audio amplifiers and blockchain-based IoT security.

• Mobile Generative AI
• Edge General Intelligence
• Quantum Computing and Networking
• +3 more

Roles & Affiliations: Professor and President's Chair Professor in Computer Science and Engineering at Nanyang Technological University (NTU), Singapore. Member of the IEEE and IET, with roles in editorial boards of major journals like IEEE Transactions on Network Science and Engineering and IEEE Communications Surveys & Tutorials. Current positions: Editor-in-Chief of IEEE Transactions on Network Science and Engineering, Area Editor in multiple journals including IEEE Communications Surveys and Tutorials. Education: Ph.D. (2008) and M.Sc. (2005) in Electrical and Computer Engineering from the University of Manitoba, Canada. B.Eng. (1999) in Computer Engineering from King Mongkut's Institute of Technology Ladkrabang, Thailand. Research Interests: Focuses on mobile generative AI, edge general intelligence, quantum networking, incentive mechanisms, and wireless communication systems. Explores applications in 6G, IoT, UAV networks, and secure communication. Recent Articles & Trends: 15 most recent articles highlight advancements in generative AI for wireless networks, quantum computing integration, secure communication protocols, and AI-driven network optimization. Key themes include semantic communication frameworks, RIS-aided systems, and federated learning in edge networks. Awards: Over 20+ prestigious awards including IEEE Fellow (2017), IET Fellow (2022), Stuart Meyer Memorial Award (2024), and multiple best paper awards at top conferences like IEEE WCNC and IEEE ICC. Advising & Grants: Advisor to numerous students (not listed explicitly). Active in funding initiatives for AI in wireless systems, quantum networks, and low-altitude economy networking. Leads projects on GenAI for networking and 6G innovations. Labs & Teams: Research focuses on CCDS labs at NTU, collaborating on projects like GenAI for ISAC, mobile edge computing, and secure federated learning systems.

• Database Systems
• Distributed Systems
• Cloud Computing
• +4 more

Dr. Kenneth Salem is a Professor at the University of Waterloo, Canada , with a distinguished career spanning over three decades in database systems, distributed computing, and data management. His work has significantly influenced transaction processing, replication, and scalability in modern databases. Institution: University of Waterloo Collaborations: Frequent co-author with Hector Garcia-Molina, Ashraf Aboulnaga, Umar Farooq Minhas, Khuzaima Daudjee Research Interests: Dr. Salem’s research focuses on database systems, particularly in transaction processing , distributed databases , cloud computing , and energy-efficient data storage . He has pioneered techniques for schema design in NoSQL , adaptive caching , and RDMA-based data transfer . His work often addresses challenges in high availability , workload-aware optimization , and cardinality estimation . Recent Article Trends: His latest publications (2023-2025) explore ad hoc transactions , eventual durability , and summary-based cardinality estimation , emphasizing practical solutions for real-world database scalability and consistency. Earlier works (2018-2022) covered memory power optimization , RDMA abstractions , and workload-aware CPU scaling , reflecting a sustained focus on performance and efficiency. Advising and Collaborations: Dr. Salem has mentored numerous co-authors in database research, including Ashraf Aboulnaga, Umar Farooq Minhas, and Khuzaima Daudjee. His collaborative projects span Apache Spark caching , RemusDB high availability , and DimmStore memory optimization . Labs and Teams: He has been a key contributor to the DaMoN and Versatile Database Systems workshops, focusing on hardware-aware database design. His work with teams at Waterloo and collaborations with institutions like ETH Zurich and MIT has advanced self-managing databases and edge replication technologies.

Kerrianne HarringtonView profile

Researcher

• Optical Fibre Technology
• Laser Physics
• Medical Applications of Light
• +3 more

Kerrianne Harrington is a Researcher in the Department of Physics at the University of Bath, focusing on developing hollow core optical fibres for advanced applications. Her work contributes to the 'u-Care' interdisciplinary project, aiming to create compact UV-C light sources for medical therapies targeting drug-resistant pathogens and precision cancer surgery. She also leads the 'Robotic microscopy for globally accessible science and healthcare' project, advancing fibre-based imaging and diagnostic tools. Her research expertise spans optical fibre fabrication, splicing, and simulation, with a focus on anti-resonant fibres enabling UV light transmission below 220 nm—unachievable in traditional fibres. Key contributions include Axi-Stack manufacturing techniques and methods to minimize interconnection losses in hollow-core fibres. Collaborations involve projects funded by EPSRC and The Royal Society, addressing quantum communication, low-loss fibre integration, and biomedical applications. Her work aligns with UN SDGs, particularly in advancing health and innovation. Recent publications highlight achievements in supercontinuum generation, UV light guidance, and multi-core fibre designs. Harrington’s research bridges fundamental physics with practical innovations in healthcare, photonics, and quantum technologies.

Xuan ZhangView profile

Associate Professor

• Artificial Intelligence Hardware
• Machine Vision Sensors
• Electronic Design Automation
• +3 more

Xuan Zhang serves as Associate Professor in Electrical and Computer Engineering at Northeastern University, leading the Sensory AI Lab since joining in January 2024. Her research bridges computer architecture, integrated circuits, and artificial intelligence to develop miniaturized AI systems for autonomous physical platforms. She earned her PhD in Electrical and Computer Engineering from Cornell University in 2012. Her educational background forms the foundation for her interdisciplinary work spanning hardware and software co-design. Dr. Zhang's research focuses on artificial intelligence hardware, machine vision sensors, and security for autonomous systems. She pioneers techniques for efficient in-sensor computing, analog circuit optimization via machine learning, and hardware-level privacy preservation. Her work addresses critical challenges in energy efficiency, robustness, and security for edge AI deployment, particularly in resource-constrained environments like medical devices and autonomous vehicles. Analysis of her 2023-2025 publications reveals three dominant trends: (1) hardware-accelerated privacy mechanisms for sensors, (2) machine learning-driven analog circuit design automation, and (3) energy-efficient architectures for neural network inference. These works consistently target real-world applications in healthcare, autonomous systems, and semiconductor design. Her accolades include the prestigious NSF CAREER Award (2020) and leadership in a $10 million federal semiconductor initiative. She contributes to national efforts in AI-powered chip design through the National Center for the Advancement of Semiconductor Technology. Dr. Zhang advises graduate researchers in the Sensory AI Lab, securing significant funding for projects spanning hardware security, in-sensor computing, and autonomous system assurance. Her lab collaborates with federal agencies and industry partners on cutting-edge semiconductor research. The Sensory AI Lab operates at the hardware-software interface, developing novel architectures for intelligent edge devices. Current projects include optical privacy preservation, robust analog design tools, and energy modeling frameworks for in-sensor visual computing systems.

Semih DoğuView profile

Assistant Professor

• Electromagnetic Theory
• Microwave Imaging
• Inverse Scattering Problems
• +3 more

Semih Doğu is an Assistant Professor at the Department of Electronics and Communication Engineering , Faculty of Electrical and Electronics Engineering , Istanbul Technical University . His research focuses on Electromagnetic Theory , Microwave Imaging , Inverse Scattering Problems , and Antenna Design . Doctorate: Istanbul Technical University (2023) Master's: Istanbul Technical University (2017) Bachelor's: Yıldız Technical University (2015) His research interests emphasize microwave-based diagnostics, including: Microwave imaging for breast cancer detection Antenna optimization for medical and security applications Inverse problem solving in electromagnetic systems Through-the-wall imaging for surveillance Semih Doğu's recent publications demonstrate his expertise in: Neural networks for temperature monitoring in hyperthermia Ku/Ka-band antenna designs for satellite systems Microwave salinity sensing Algorithm development for improved imaging accuracy He contributes to the ITU Electromagnetics Research Group , participating in projects like: Microwave Brain and Breast Imaging Device Development Compressed Sensing for Energy-Efficient Communication Microwave Tissue Analysis

• Biomedical Engineering
• Circuits and Systems
• Neural Engineering
• +3 more

Halil Andac Yigit is a Doctoral Assistant at the Telecommunications Circuits Laboratory (TCL) within the School of Engineering (STI) at EPFL. He is affiliated with the Institute of Microengineering (IEM) and pursues a Doctoral Program in Electrical Engineering through the École Doctorale d'Électronique et d'Electrotechnique (EDoc). His research focuses on biomedical circuits, energy harvesting, and low-power electronics for medical implant systems. Yigit's work emphasizes implantable cochlear devices, wireless power solutions, and precision neural stimulation interfaces. Education : Current doctoral student in Electrical Engineering at EPFL. Research Interests : Development of energy-efficient biomedical devices, including cochlear implants and neural stimulation systems. Specializes in low-power circuits for medical applications, wireless power transfer, and advanced memory technologies like eDRAM optimization. His research bridges microelectronics design with clinical needs, aiming for miniaturization and energy autonomy in implantable systems. Lab Affiliation : Telecommunications Circuits Laboratory (TCL), EPFL, where he collaborates on projects involving MEMS-based systems and autonomous medical devices.

Arnout DevosView profile

Lecturer

• Artificial Intelligence
• Machine Learning
• Generative AI
• +5 more

Dr. Arnout Devos is a Lecturer at the Department of Computer Science at ETH Zurich and a staff member at the ETH AI Center and ELLIS. His work focuses on Artificial Intelligence research and education, with specializations in generative AI, few-shot learning, and accelerating deep tech innovation. He co-founded the Sciencepreneurship Community to foster entrepreneurial scientists and leads initiatives like the ETH AI Center Academic Talk Series (AICATS) to bridge academic collaborations. Education: PhD in Machine Learning (EPFL, 2024) as a Marie-Curie fellow; Master’s in Computer Science (USC, 2018); degrees in Management, Electrical Engineering, and EECS (KU Leuven). Awards include the EPFL Teaching Assistant Award (2024). Research interests span AI ethics, healthcare applications, and interdisciplinary collaborations. His PhD thesis advanced few-shot learning techniques for efficient model adaptation. Projects include the Sciencepreneurship Summer School and investments via S2S Ventures, including exits like Digit Soil. Key Activities: Academic leadership, startup mentorship, venture capital advising Labs/Teams: ETH AI Center, ELLIS, S2S Ventures Grants: Marie-Curie Fellowship (PhD funding)

S.V. SreenivasanView profile

Professor

• Nanotechnology
• Nanofabrication
• Advanced Manufacturing
• +3 more

S.V. Sreenivasan is a Professor and holds the Cockrell Family Regents Endowed Chair #7 in Engineering at The University of Texas at Austin. He is a leading nanotechnologist specializing in high-throughput nanofabrication techniques for electronics, displays, and healthcare applications. As the Director of the NSF-funded NASCENT Center, he leads interdisciplinary research in nanomanufacturing systems. He co-founded Molecular Imprints Inc. and currently serves as Chief Technologist at Canon Nanotechnologies, Inc. His research focuses on scalable nanotechnologies, including molecular imprint lithography, metal-assisted chemical etching, and advanced 3D integrated circuits. He has authored over 130 papers and holds 100+ patents. His work emphasizes bridging academic innovation with industrial applications, particularly in semiconductor manufacturing and nanoelectronics. Dr. Sreenivasan has received prestigious awards such as the ASME Leonardo da Vinci Award (2009), TAMEST O'Donnell Award (2010), and election to the National Academy of Engineering (2021). He is a Fellow of the National Academy of Inventors (2016) and ASME (2020). His research groups develop novel fabrication methods like nanoshape imprint lithography and precision inkjet printing systems. Collaborations include Magic Leap and Canon, focusing on next-gen displays and semiconductor tools. He advocates for accessible nanotechnology through portable fabrication platforms.