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Daniel W. BlissView profile

Professor

• Radar
• Wireless Communications
• Precision Positioning
• +7 more

Daniel W. Bliss is a Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University and Director of ASU's Center for Wireless Information Systems and Computational Architectures (WISCA). With over $50 million in research funding as principal investigator from organizations including DARPA, ONR, Google, and Airbus, his work bridges theoretical foundations with practical implementations across multiple domains of wireless systems. Dr. Bliss received his educational foundation with a B.S.E.E. from Arizona State University (1989), followed by M.S. and Ph.D. degrees in Physics from the University of California-San Diego (1995, 1997). His academic journey includes significant industry experience at General Dynamics (1989-1993) and MIT Lincoln Laboratory (1997-2012) before joining ASU. His research program focuses on advanced wireless systems spanning radar, communications, precision positioning, computational architectures, and medical monitoring applications. Bliss employs information theory, estimation theory, and signal processing to develop novel system concepts with disruptive capabilities. Current research emphasizes RF convergence, integrated sensing and communications, and anticipatory medical analytics using wireless technologies, with particular focus on extracting physiological data from radar signals. Analysis of recent publications reveals a strong trend toward integrated sensing and communications systems, particularly utilizing mmWave and radar technologies for medical monitoring applications. His work increasingly bridges traditional communications and radar domains while expanding into physiological monitoring, demonstrating a clear trajectory toward convergence of wireless technologies for healthcare applications and remote vital sign detection. Dr. Bliss has received significant recognition for his contributions: Fellow of the IEEE (2015) 2021 IEEE Warren D. White Award for Excellence in Radar Engineering 2016-2017 Top 5% Teaching Award at ASU 2017 ASU Fulton Engineering Exemplar Faculty As a dedicated mentor, Dr. Bliss has supervised numerous graduate students through successful dissertation and thesis defenses across both PhD and Master's programs. His research portfolio includes substantial funding from diverse sources with over $50 million secured as principal investigator. Current projects include the $17M DARPA DASH project focused on advanced software-reconfigurable heterogeneous SoCs for next-generation RF systems, and multiple initiatives in contactless vital sign monitoring using radar technologies. Dr. Bliss leads the BLISS Lab and serves as director of WISCA, fostering interdisciplinary research in wireless systems. His team includes researchers working on distributed coherent systems, MIMO radar, RF convergence, and medical monitoring applications, with recent successes including the Making Waves team that tied for first place in the Air Force Spark Tank challenge. He has founded two startup companies: DASH Tech Integrated Circuits Company and the Big Little Sensor Company, focusing on high-performance embedded processing and small-scale radar physiological monitoring, respectively.

Moe Z. WinView profile

Professor

• Wireless communications
• Optical communications
• Space communications systems
• +2 more

Moe Z. Win is the Robert R. Taylor Professor at the Massachusetts Institute of Technology (MIT), specializing in wireless communications, optical communications, and space communications systems. His research bridges theoretical and applied domains, including quantum sensing, network localization, and signal processing. B.S.E.E., Texas A&M (1987) M.S.E.E. & Ph.D., University of Southern California (1989, 1998) Recent work focuses on quantum-enhanced positioning, machine learning for localization, and next-generation (xG) non-terrestrial networks. He leads research at the Quantum neXus Laboratory (QX Lab), Wireless Information & Network Sciences Lab, and Laboratory for Information and Decision Systems. His career spans the Jet Propulsion Laboratory (1987-1995) and AT&T Research Laboratories (1998-2002). Key methodologies include soft information fusion, variational quantum sensing, and robust beam tracking for terahertz communications.

Gert CauwenberghsView profile

Professor

• Neuromorphic Engineering
• Biomedical Integrated Circuits
• Neural Interfaces
• +7 more

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.

Andrew ChildsView profile

Professor

• Quantum Algorithms
• Quantum Information Processing
• Quantum Simulation
• +2 more

Andrew Childs is a Professor at the University of Maryland, affiliated with the Department of Computer Science and the Institute for Advanced Computer Studies (UMIACS). He serves as Director of the NSF Quantum Leap Challenge Institute for Robust Quantum Simulation (RQS) and is a Fellow at the Joint Center for Quantum Information and Computer Science (QuICS). His research focuses on quantum algorithms for simulating physical systems, algebraic problems, and quantum walk protocols, with applications in quantum computing and computational complexity. University of Maryland Institute for Advanced Computer Studies (UMIACS) Joint Center for Quantum Information and Computer Science (QuICS) NSF Quantum Leap Challenge Institute for Robust Quantum Simulation Childs' research spans quantum simulation, quantum Fourier transform, phase estimation, and Hamiltonian dynamics. He has developed techniques to reduce quantum computational resources for simulating quantum systems and explored limitations of quantum computers through hidden subgroup problems and non-unitary dynamics. His publications cover diverse areas including quantum walk optimization, Hamiltonian simulation methods, and applications to cryptography and condensed matter physics. Recent works address spatial search algorithms, product formulas for commutators, and quantum routing protocols. As an educator, Childs has taught courses on quantum algorithms and information processing at both the University of Maryland and University of Waterloo, with lecture notes and materials spanning multiple years. Contact: amchilds@umd.edu | Office: ATL 3359 | Affiliated with University of Maryland's quantum research institutes.

Michael McAlpineView profile

Professor

• 3D Printing
• Nanotechnology
• Biomedical Engineering
• +4 more

Michael McAlpine is a Professor in the Mechanical Engineering department at the University of Minnesota . He also holds affiliations with the Biomedical Engineering and Electrical and Computer Engineering departments. His research focuses on 3D printing functional materials & devices , Nanoscale inks , Biomedical devices , Bioelectronics , and Flexible Microsystems . Research Interests : 3D Printing, Biomedical Engineering, Nanotechnology, Flexible Electronics, Microfluidics Labs : ME 361/363 Contact : mcalpine@umn.edu , (612) 626-3303, ME 117 Recent Research Trends include 3D Printed Biomedical Devices , Flexible Electronics , and Bioprinting Applications . His work spans from Spinal Organoid Formation to Programmable Drug Release Capsules . Scientific Award : Circulation Research 2020 Best Manuscript Award

Dana AndersonView profile

Professor

• Quantum Computing
• Ultracold Atoms
• Atomtronics
• +3 more

Dana Anderson is a Professor of Physics and JILA Fellow at the University of Colorado Boulder. He holds dual affiliations with the Department of Physics and JILA, a joint institute between the University of Colorado Boulder and the National Institute of Standards and Technology (NIST). His research focuses on ultracold atoms, quantum computing, and atomtronics, with applications in quantum sensing and space-based experiments. He currently serves as Chief Strategy Officer (CSO) of Infleqtion (formerly ColdQuanta), a quantum technology company he co-founded. Anderson is a principal investigator in the Quantum Pathways Institute, a NASA-funded initiative to develop quantum-based Earth-sensing technologies. He collaborates with institutions like NIST, JPL, and ColdQuanta on projects such as the Cold Atom Laboratory (CAL) for space-based ultracold atom research. His work has been recognized by TIME Magazine and led to significant grants, including a $15M NASA award for quantum space research. Research interests include atomtronics (hybrid atom-electronics systems), neutral atom quantum computing, and ultracold atom gyroscopes. His group develops novel atom chip technologies, such as window atom chips enabling high-resolution imaging, and explores applications like matterwave transistors and quantum inertial sensors. Current projects include shaken lattice interferometry for navigation and Rydberg atom-based microwave sensors. Anderson has pioneered concepts like the matterwave transistor oscillator and contributed to the first neutral atom quantum computing arrays. His work bridges fundamental physics and applied technologies, with a focus on translating quantum phenomena into practical devices. He actively mentors students and postdocs in experimental atomic physics and quantum engineering.

Yimin D. ZhangView profile

Associate Professor

• Statistical Signal Processing
• Array Processing
• Radar Signal Processing
• +10 more

Yimin D. Zhang is an Associate Professor in the Department of Electrical and Computer Engineering at Temple University's College of Engineering, where he leads the Advanced Signal Processing (ASP) Lab. His research spans statistical signal processing, array processing, radar, wireless communications, and convex optimization. Research Interests: Dr. Zhang's work focuses on cutting-edge signal processing techniques including compressive sensing, sparse arrays, time-frequency analysis, and robust beamforming. These are applied to radar systems, satellite navigation, assisted living, and wireless networks. His research addresses core challenges in target localization, direction-of-arrival estimation, and spectrum-efficient joint radar-communication systems. The recent publications highlight a strong trend in exploiting sparsity, virtual arrays, and deep learning to enhance resolution and robustness in radar and communication systems. Themes include multi-frequency processing, low-rank matrix recovery, and optimized OFDM waveforms for dual-function systems. Scientific Awards: 2016 IET Radar, Sonar and Navigation Premium Award 2017 IEEE Aerospace and Electronic Systems Society Harry Rowe Mimno Award 2018 IEEE Signal Processing Society Young Author Best Paper Award (coauthor) Advising and Grants: Dr. Zhang has served as Principal or Co-Principal Investigator on over $6 million in research funding from the NSF, AFRL, ONR, and DARPA. While student advisees are not listed, his leadership of the ASP Lab suggests active mentorship of graduate researchers. He contributes extensively to the academic community as an associate editor for IEEE Transactions on Signal Processing and editor for Signal Processing journal, and serves on key IEEE technical committees. Labs and Teams: He directs the Advanced Signal Processing (ASP) Lab at Temple University, which focuses on developing novel algorithms for real-world applications in radar, communications, and navigation. Previously, he led the Wireless Communications and Positioning Lab and the RFID Lab at Villanova University.

Kristofer S.J. PisterView profile

Professor

• Micro/Nano Electro Mechanical Systems (MEMS)
• Control Systems
• Robotics
• +6 more

Kristofer Pister is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He co-directs the Berkeley Sensor and Actuator Center (BSAC) and the Ubiquitous Swarm Lab. His career spans groundbreaking innovations in Micro/Nano Electro Mechanical Systems (MEMS), Control Systems, and Low-Power Circuits, with a focus on Smart Dust and synthetic insects. Education: Ph.D. and M.S. in EECS from UC Berkeley (1992, 1989); B.A. in Applied Physics from UC San Diego (1986). His research areas include MEMS , Control Systems , Robotics , and Integrated Circuits , with recent work on self-powered micro-sensors, crystal-free radios, and interplanetary swarm networks. Key awards include the ISA Albert F. Sperry Founder Award (2009) , Alexander Schwarzkopf Prize (2006) , and the NSF CAREER Award (1996) . He has authored numerous influential publications in wireless sensor networks and microrobotics. His lab, Ubiquitous Swarm Lab , explores distributed robotics and swarm intelligence. Pister emphasizes open collaboration in research, ethical conduct in academia, and efficient resource utilization for graduate students.

Yannis ChronisView profile

Assistant Professor

• Database Systems
• Hardware-Software Co-design
• Data Processing Efficiency
• +3 more

Yannis Chronis is an incoming Assistant Professor at the Department of Computer Science , ETH Zurich (starting August 2025), where he will join the ETH Systems Group . Prior to this, he spent 3 years as a Systems Researcher at Google's Systems Research Group in Sunnyvale, USA. He holds a Ph.D. in Computer Science from the University of Wisconsin-Madison (advised by Prof. Jignesh Patel) and a Bachelor's/Master's from the University of Athens, Greece (advised by Prof. Yannis Ioannidis). His research focuses on optimizing databases and data processing for modern hardware through software-hardware co-design. Key areas include database efficiency in memory-centric architectures, learned query optimizers, and cloud resource management. His work is supported by a Facebook Fellowship and has been recognized with the EDBT 2016 Medal for best paper. Teaching: Taught CS 564 - Database Management Systems at UW-Madison (Spring 2022). Service: Served on program committees for SIGMOD, VLDB, CIDR, and others, and chairs the CIDR Proceedings Committee. Key Publications: His recent work includes studies on memory-centric computing for databases, cardinality estimation benchmarks, and adaptive query processing techniques.

Yayun DuView profile

Assistant Professor

• Bioelectronics
• Intelligent Systems
• Wearable and Implantable Sensors
• +7 more

Dr. Yayun Du is an Assistant Professor in the Department of Electrical and Computer Engineering at Vanderbilt University School of Engineering. She holds a Ph.D. in Robotics and System Control (Minor: Solid Mechanics) from UCLA (2022) and was a postdoctoral scholar at Northwestern University's Rogers Group through 2024. Current faculty at Vanderbilt University Ph.D. from University of California, Los Angeles Postdoctoral experience at Northwestern University Her research integrates bioelectronics and robotics through three core directions: 1) Developing multimodal wearable/implantable sensors for health monitoring, 2) Creating human-in-the-loop interaction systems using brain-computer interfaces, and 3) Applying machine learning to medical environment robotics. She has deployed four sensor types across seven hospitals globally, serving users from neonates to elderly patients. Dr. Du's recent publications focus on wireless bioelectronic devices ( PNAS ), sustainable sensor materials ( ACS Sustainable Chemistry & Engineering ), and agricultural robotics ( ICRA , IROS ). She serves as Associate Editor for ICRA 2025 and has received two Best Paper Award final nominations at IROS 2021. Finalist - Best Paper Award in Agri-Robotics (IROS 2021) Finalist - Best Paper Award in Robot Mechanisms and Design (IROS 2021) As head of the Du Group, she leads interdisciplinary research with applications in both healthcare and agricultural contexts, collaborating with Vanderbilt Institute for Surgery and Engineering (VISE) and clinical partners. Her work emphasizes deployable systems that transition from academic research to real-world implementation in medical and industrial environments.

Canan DagdevirenView profile

Associate Professor

• Biomedical Engineering
• Piezoelectric Devices
• Wearable Electronics
• +6 more

Dr. Canan Dagdeviren is an Associate Professor and LG Career Development Professor of Media Arts and Sciences at the Massachusetts Institute of Technology, where she directs the Conformable Decoders research group at the MIT Media Lab. She joined the MIT faculty in January 2017 and has established herself as a leading innovator in conformable biomedical devices. Education: Ph.D. in Materials Science and Engineering, University of Illinois at Urbana-Champaign M.Sc. in Materials Science and Engineering, Sabanci University, Istanbul, Turkey B.Sc. in Physics Engineering, Hacettepe University, Ankara, Turkey Dr. Dagdeviren's research focuses on creating mechanically adaptive electromechanical systems that can intimately integrate with biological surfaces for sensing, actuation, and energy harvesting. She believes vital information from nature and the human body is 'coded' in various physical patterns, and her work develops 'conformable decoders' to translate these patterns into beneficial signals and energy. Her research spans wearable and implantable medical devices, with particular emphasis on piezoelectric systems that can be twisted, folded, stretched, wrapped, and implanted onto curvilinear surfaces of the human body without damage or significant alteration in performance. Analysis of her recent publications reveals a strong focus on medical applications of conformable electronics, particularly in ultrasound technology for breast cancer detection, deep brain stimulation, and bladder monitoring. Her work consistently bridges materials science, electrical engineering, and medical applications, with increasing emphasis on practical healthcare solutions that can be deployed outside clinical settings. Major Scientific Awards: NSF CAREER Award (2021) 3M Non-Tenured Faculty Award (2021) MIT Technology Review's Top 35 Innovators Under 35 (2015) Forbes' Top 30 Under 30 in Science (2015) National Academy of Engineering US Frontiers of Engineering Symposium participant (2019) Frank E. Perkins Award for Excellence in Graduate Advising Aziz Sancar Science Award Dr. Dagdeviren actively mentors graduate students and has received recognition for her advising excellence. Her research is supported by significant grants including the NSF CAREER award and has resulted in numerous patents and commercialization opportunities. She has developed innovative cleanroom-based courses at MIT that train students in microfabrication techniques for biomedical devices. The Conformable Decoders research group operates a specialized cleanroom facility at the MIT Media Lab, enabling the development and fabrication of novel conformable electronic systems. The group's work has attracted attention from major media outlets including BBC, CNN, and Nature, and has potential applications across multiple medical specialties including neurology, oncology, and urology.

Qing CaoView profile

Associate Professor

• Nanomaterials
• Electronic Devices
• Optoelectronic Devices
• +5 more

Qing Cao is an Associate Professor of Materials Science and Engineering at the University of Illinois at Urbana-Champaign, with courtesy appointments in Chemistry and Electrical Engineering. He leads the Cao Research Group within the Grainger College of Engineering and serves as Deputy Editor of Science Advances. Dr. Cao received his B.S. in Chemistry from Nanjing University in 2004 and his Ph.D. in Materials Chemistry from the University of Illinois at Urbana-Champaign in 2009. After working for 9 years as a research scientist at IBM Thomas J. Watson Research Center, he returned to UIUC in 2018 as a faculty member. His research focuses on developing functional nanomaterials for unconventional electronic systems, high-performance logic devices, and low-cost energy harvesting. The Cao Research Group specifically works on: nanoelectronic devices based on novel nanomaterials; next-generation memory devices for neuromorphic and in-memory computing; monolithic 3D integration for high performance electronics; high-performance printable electronic materials; and bioelectronics for healthcare applications. His work bridges materials science, chemistry, electrical engineering, and device physics. Analysis of Dr. Cao's recent publications reveals a strong focus on electrochemical memory devices for neuromorphic computing, with significant work on carbon nanotube-based electronics and novel nanomaterials. His 2023 Nature Electronics paper on CMOS-compatible electrochemical synaptic transistors demonstrates his leadership in developing hardware solutions for deep learning acceleration. His research trajectory shows a progression from fundamental carbon nanotube device physics to more applied systems for computing and sensing applications. IBM Pat Goldberg Memorial Best Paper Award (2017) IBM Master Inventor Award (2016) MIT Technology Review TR35 (2016) Forbes '30 Under 30' (2012) and 'Most Influential All-Star Alumni' (2016) Atlantic Council Millennium Fellow (2017) US Frontiers of Engineering by National Academy of Engineering (2016, 2019) 17 IBM Invention Achievement Awards (2011-2018) Dr. Cao has secured significant research funding including NSF grants 1950182 and 2139185. His research group actively recruits graduate students and postdoctoral researchers to work on cutting-edge materials and device projects. His work has resulted in over thirty research papers and fifty patents and patent applications. He teaches graduate courses including MSE 403 (Synthesis of Materials), MSE 460 (Electronic Materials I), and MSE 488 (Optical Materials). The Cao Research Group operates within the University of Illinois' world-class facilities including the Frederick Seitz Materials Research Laboratory and Holonyak Micro and Nanotechnology Laboratory. His research has received support from NSF, DoD, DOE, and industry partners including TSMC. The group's recent $2 million project focuses on developing technology to help mobile devices learn and adapt to their surroundings.

Adam KhalifaView profile

Assistant Professor

• Low-Power Electronics
• Biomedical Engineering
• Neural Engineering
• +4 more

Adam Khalifa is an Assistant Professor in the Department of Electrical & Computer Engineering at the University of Florida. His research focuses on low-power analog/RF/Mixed-mode ASIC design, miniaturization of biomedical devices, wireless powering solutions, and neural stimulation/recording techniques in animal models. He holds a PhD from Johns Hopkins University and degrees from The Hong Kong University of Science and Technology. His work emphasizes implant packaging, electrode microfabrication, and coil design for medical applications. Key research areas include developing energy-efficient wireless systems for implanted devices, such as magnetoelectric antennas and galvanic body-coupled powering. He has pioneered advancements in miniaturized implantable devices, including the 'Microbead' stimulator. His NIH T32 Fellowship (2019) and Ferdinand H. Fellowship (2018) reflect his impactful contributions. Publications highlight innovations in wireless power transfer, metamaterials for biomedical implants, and injectable microdevice fabrication. His work spans from circuit-level modeling to in vivo validation, emphasizing both technical and biological integration challenges. Collaborative efforts address challenges like implant migration tracking via MRI and energy harvesting for battery-free systems.

W. Hong YeoView profile

Professor

• Flexible Electronics
• Human Augmentation
• Micro and Nano Device Engineering
• +6 more

W. Hong Yeo is a Professor in the Woodruff School of Mechanical Engineering and Program Faculty in Bioengineering at the Georgia Institute of Technology, where he also directs the WISH Center. He holds adjunct appointments in the Wallace H. Coulter Department of Biomedical Engineering. Previously, he was an Assistant Professor at Virginia Commonwealth University (2014-2016) and a postdoctoral fellow at the University of Illinois Urbana-Champaign's Beckman Institute. Dr. Yeo's research integrates nanomechanics, soft materials, and nano-microfabrication to develop bio-interfaced systems. Key areas include: Flexible Bioelectronics : Wearable/implantable sensors for health monitoring Human-Machine Interfaces : Neural prosthetics and soft robotics Translational Nanoengineering : Nanoparticle biosensing and diagnostics His publications (2023-2025) demonstrate strong focus on wireless health technologies, including multi-modal wearable systems, implantable sensors for cardiovascular/neurological monitoring, and AI-integrated diagnostics. Trends show increasing emphasis on closed-loop therapeutic systems and scalable manufacturing. Awards & Recognition : BMES Innovation and Career Development Award Virginia Commercialization Award Blavatnik Award Nominee NSF Summer Institute Fellowship Research funding sources include MEDARVA Foundation, NIH, DARPA, and industry partners like CooperVision. He leads the Center for Human-Centric Interfaces & Engineering , developing next-generation bio-interfaced systems.

Deepak GanesanView profile

Professor

• Networking and Distributed Systems
• Mobile and Sensor Systems
• Human-Computer Interactions
• +3 more

Deepak Ganesan is a Professor at the Manning College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst. His research focuses on low-power sensing and communication, networked systems, and machine learning applied to pervasive health monitoring and societal challenges. PhD, Computer Science, University of California, Los Angeles (2004) MS, Computer Science, University of California, Los Angeles (2000) BTech, Computer Science, Indian Institute of Technology, Madras (1998) Ganesan's work bridges wireless sensor networks, smart textiles, and healthcare applications. He designs ultra-low-power wearable devices for tracking health signals like drug use, smoking, and cognitive performance, often integrating machine learning for robust detection. His research emphasizes societal impact, particularly in aging and Alzheimer's care through the Massachusetts AI and Technology Center for Connected Care (MassAITC) and the Center for Personalized Health Monitoring (CPHM). Recent publications highlight innovations in edge-cloud collaboration, fabric-based sensors, and longitudinal health analytics. His NIH-funded MD2K Center for Excellence and affiliations with the Center for Data Science and Computational Social Science Institute further underscore his interdisciplinary approach. ACM Fellow NSF CAREER Award (2006) IBM Faculty Award (2008) UMass Junior Faculty Fellow (2008) UMass Lilly Teaching Fellow (2009) Best Paper at CHI 2013 Best Paper Runner-up at Mobicom 2014 Honorable Mentions at Ubicomp 2013 Ganesan leads the SENSORS: Wireless Sensor Networks Group and contributes to global initiatives like the Internet of Battlefield Things. His work spans academic research, industry partnerships, and policy development in AgeTech and digital health.