Sohmyung Ha is an Associate Professor of Electrical Engineering and Bioengineering at NYU Abu Dhabi and holds a Global Network position at NYU Tandon School of Engineering. He leads the Integrated BioElectronics Laboratory, focusing on advancing silicon integrated technologies for biomedical applications such as implantable devices and wearable sensors. His expertise spans biomedical circuits, neural interfaces, and wireless power systems. Education: MS (2004, KAIST), PhD (2016, UC San Diego) with a Best Thesis Award. Prior industry experience includes analog circuit design at Samsung Electronics (2006-2010). Academic affiliations include NYU Abu Dhabi, NYU Tandon, and global collaborations. Research interests include high-performance biomedical sensors, neural prosthetics, and energy-efficient bioelectronic systems. Notable achievements include a Best Paper Award (ISCAS 2024) and innovations in impedance spectroscopy and neural interface ICs. Current projects emphasize closed-loop neural interfaces, subcutaneous glucose monitoring, and retinal prostheses. His lab develops miniaturized, power-autonomous systems for healthcare applications.
Hyosang Lee is an Assistant Professor in the Robotics Section of the Mechanical Engineering Department at Eindhoven University of Technology (TU/e). He holds a PhD from KAIST and has held research positions at the Max Planck Institute and University of Stuttgart. His work focuses on tactile sensing technologies, including artificial skin development, soft robotics, and integration of sensory systems with AI. Bachelor's: Mechanical Engineering, Korea University Master's: Robotics and Mechanical Engineering (double major) PhD: Mechanical Engineering, KAIST (2017) Research interests span tactile sensor design, electrical impedance tomography (EIT), and human-robot interaction. His group emphasizes creating scalable, flexible tactile systems for robots. Recent work includes air pressure sensing for force estimation and biomimetic skin materials. Publications highlight innovations in multi-directional force sensing, soft component technologies, and haptic interfaces for autism therapy. He teaches 'Dynamics and Control of Robotic Systems' and serves on the editorial board of npj Robotics . No formal student advisees are listed, though his lab, the Tactile Sensing and Robotic Skin Group , likely involves graduate researchers. His research contributes to UN Sustainable Development Goals related to health and technology.
Sharon Rozovsky is a Professor in the Department of Chemistry and Biochemistry at the University of Delaware's College of Arts & Sciences, where she leads research on oxidative stress response mechanisms and protein quality control pathways. Her work bridges biochemistry, chemical biology, and structural biology with direct implications for understanding neurodegenerative diseases and viral pathogenesis. Her academic foundation includes a B.S. from Tel Aviv University (1994) and a Ph.D. from Columbia University (2000), establishing her expertise in protein dynamics and redox biochemistry. These credentials underpin her innovative approaches to studying cellular stress responses. Rozovsky's research program centers on selenoproteins—proteins containing the rare amino acid selenocysteine—and their critical roles in endoplasmic reticulum (ER) stress resolution. She investigates how membrane-bound selenoproteins like Selenoprotein S and K regulate the ER-associated degradation (ERAD) pathway, with recent work revealing their surprising autoproteolytic activity and involvement in SARS-CoV-2 replication. Her lab pioneers chemical tools including expressed protein ligation and advanced 77Se NMR spectroscopy to characterize these systems at molecular resolution. Analysis of her 2021-2025 publications shows dominant themes in selenoprotein structure-function relationships, ER stress mechanisms, and viral interactions, alongside methodological innovations in cryo-EM grid technology and NMR. This body of work demonstrates consistent focus on redox biochemistry with expanding applications in virology and structural biology. No major scientific awards or fellowships were explicitly documented in the available materials, though her research impact is evident through high-impact publications and methodological contributions. She directs the active Rozovsky Research Group, mentoring graduate students and postdoctoral researchers in biochemical and biophysical techniques. Her laboratory operations are supported by competitive funding including an NSF CAREER award (2011) focused on selenoprotein reactivity, reflecting sustained recognition of her innovative research program.
Trey Porto is an Adjunct Professor at the University of Maryland, affiliated with the Joint Quantum Institute (JQI) and NIST. His research focuses on ultra-cold atoms, quantum optics, and quantum information science. He leads projects on Rydberg atoms, optical lattices, and quantum networking, leveraging cold atom systems to explore novel quantum phenomena and control strategies. Research areas include ultra-cold Rb/Yb mixtures for studying Bose-Einstein condensates and engineered dissipation, as well as photon-photon interactions using Rydberg-dressed polaritons. His work bridges quantum simulation, quantum computing, and precision measurement, with applications in quantum networking and many-body physics. Key achievements include the 2023 UMD Quantum Invention of the Year Award for developing photon-counting methods that preserve quantum states. Porto collaborates with groups such as RQS and JQI, contributing to advancements in subwavelength optical potentials and Floquet-engineered systems. He mentors graduate students in experimental and theoretical aspects of cold atoms and quantum technologies. Publications highlight breakthroughs in Rydberg blockade enhancement, prethermal Bose-Einstein condensation, and compact auto-alignment systems for experimental setups. His lab is based in the Physical Sciences Complex on the UMD campus, with ongoing projects exploring quantum dissipation and photon-atom hybrid systems.
Dr. Kanwaljeet S. Anand is a dual-appointed Professor of Pediatrics (Pediatric Critical Care) and Anesthesiology, Perioperative & Pain Medicine at Stanford University School of Medicine. As director of the Pain/Stress Neurobiology Lab and Jackson Vaughan Critical Care Research Fund, he serves as Editor-in-Chief of Pediatric Research and maintains active membership in Bio-X, MCHRI, and Wu Tsai Neurosciences Institute. Rhodes Scholar with D.Phil from University of Oxford Harvard postdoctoral fellowship and Boston Children's Hospital residency Founded Harmony Health Clinic - Arkansas' largest charitable medical-dental facility A translational researcher with 30+ years of impact, Dr. Anand established the first scientific framework for infant pain perception and developed novel pain assessment methodologies. Current research focuses on: Hair biomarker analysis for stress and social affiliation (cortisol/oxytocin) Machine learning systems for objective pain detection in non-verbal infants Biopsychosocial interventions for stress reduction in disadvantaged youth Neurotoxicity mechanisms of sedatives in developing brains Global NICU opioid usage patterns through the NeoOpioid Consortium His work has yielded over 260 publications and significant advances in: Pediatric pain management protocols Neonatal stress biomarker development Critical care neurobiology insights Community health initiatives AI-driven clinical decision support systems Scientific Recognition 9th Annual 'In Praise of Medicine' Public Address, Erasmus University (2014) Nightingale Excellence Award (2016) Honorary Doctorate from University of Örebro (2019) NIH SBIB-H82 Study Section Chair (2018) Multiple IASP and American Pain Society awards Swedish Academy of Medicine's Nils Rosén von Rosenstein Award (2009) St. Jude Endowed Chairholder (2010) As mentor to Med Scholar Anjali Gupta and advisor to numerous professional bodies, Dr. Anand maintains active clinical leadership in Pediatric Intensive Care while advancing computational approaches to pain detection through collaborations with Stanford's AI researchers.
Prof. Dr.-Ing. Elisabeth Clausen is a Professor and Director of the Chair and Institute for Advanced Mining Technologies at RWTH Aachen University. She holds key roles in the Specialist Group for Raw Materials and Disposal Technology, serves as a rectorate representative, and leads the Commission for EU Research Funding. Her research spans Underground mining automation Acoustic emission diagnostics Sustainable mining systems Space resource extraction Advanced sensor technologies Her recent publications focus on autonomous mining machinery, underground communication systems, and acoustic emission analysis across 15+ studies from 2013–2025, with particular emphasis on Ultra-wideband positioning Thermographic detection Crack monitoring in planetary gearboxes Explosive atmosphere safety Mineral processing diagnostics Digitalization trends Prof. Clausen contributes to mining education reform through initiatives like CDIO™ and has developed innovative learning spaces in underground mines. She coordinates international educational labs and integrates sustainability into mining engineering curricula, with publications on Adaptive ventilation systems Mining education frameworks Future-proof mineral extraction Entrepreneurial mindset in engineering
Raouf Boutaba is a Professor at the University of Waterloo , serving as Director of the David R. Cheriton School of Computer Science since July 2020. He holds prestigious fellowships including FRSC , FIEEE , FIEC , and FCAE . 2024: Inaugural Rogers Chair in Network Automation 2024: Ontario Research Fund–Research Excellence (ORF–RE) $2M grant for next-gen mobile networks 2021: University Professor title, University of Waterloo Research Interests span network automation, resource management in wired/wireless networks, network function virtualization (NFV), software-defined networking (SDN), cloud computing, blockchain, future Internet architecture, and cybersecurity. His work focuses on zero-touch networks, 5G/B5G slicing, and AI-driven orchestration. Scientific Contributions include 15+ recent publications on topics like reinforcement learning for RAN slicing, encrypted traffic classification, quantum network optimization, and self-driving infrastructure. His projects 5G LEAP and 5G ELITE explore network isolation and Open RAN principles. 2024: IFIP/IEEE CNOM Test of Time Paper Award 2024: Graduate Supervision Excellence Award 2021: Kenneth C. Sevcik Outstanding Student Paper Award (advisor) Teaching includes co-developing the NSERC CREATE Network Softwarization program, offering courses like Network Softwarization: Principles and Foundations (Winter 2024) and Technologies and Enablers since 2018. He emphasizes hands-on training in SDN, NFV, Open RAN, and 5G. Students and Collaborations : Supervised PhD students such as Shihabur R. Chowdhury (2021), Nashid Shahriar (2020), and undergrad Leni Aniva (2022 Gov. Gen. Silver Medal ). His team includes researchers working on 5G, blockchain, and AI-driven network management. Professional Leadership : Organized Rogers TEP Workshops (2024-2025), delivered keynotes at IEEE Globecom, ColCom, and BalkanCom, and served on expert panels for AI orchestration and 5G cybersecurity at major symposia.
Jesper Rindom Jensen is an Associate Professor in the Department of Electronic Systems at Aalborg University, Denmark, under the Technical Faculty of IT and Design. He is the Head of the Audio Analysis Lab, a leading research group in audio signal processing, since 2023. His work bridges theoretical signal processing and practical applications in artificial intelligence and audio systems. Full Name: Jesper Rindom Jensen Institution: Aalborg University School: The Technical Faculty of IT and Design Department: Department of Electronic Systems Research Lab: Audio Analysis Lab Email: jrj@es.aau.dk Office: Fredrik Bajers Vej 7B, B5-206, 9220 Aalborg Øst, Denmark Education: M.Sc. in Electronic Systems, Aalborg University (cum laude, 2009) Ph.D. in Signal Processing, Aalborg University (2012) Research Interests: Jesper Rindom Jensen's research centers on audio signal processing, with a strong emphasis on artificial intelligence, speech enhancement, noise reduction, beamforming, and multichannel systems. His work applies to diverse domains including robot and drone audition, spatial audio, and active noise control. He develops novel filtering techniques, including variable span linear filters and harmonic beamformers, to improve speech quality and intelligibility in noisy and reverberant environments. Publication Trends: His recent publications (2023–2025) show a strong trend toward integrating deep learning with classical signal processing, particularly in direction-of-arrival estimation, underwater acoustics, and robust multichannel systems. There is a clear focus on real-world applications, including sound zone control, active noise control, and limited-data scenarios using knowledge distillation. His work consistently emphasizes robustness, efficiency, and practical deployment. Scientific Awards and Recognition: AAU Talent for emerging research leaders Recipient of a competitive postdoc grant from the Danish Independent Research Council Advising and Grants: Jesper has supervised multiple PhD and master’s students, including Nørholm, Karimian-Azari, Zhang, and Wang. He has led significant research projects such as 'Sound Processing for Robots and Drones' (2018–2020) and participated in others related to joint audio-visual tracking and speech enhancement. His research has been supported by national funding bodies, reflecting its innovation and impact. Labs and Teams: He is a founding and core member of the Audio Analysis Lab at Aalborg University, which focuses on cutting-edge audio signal processing and AI-driven solutions. The lab fosters interdisciplinary collaboration and has produced numerous publications, datasets, and real-world applications. Jensen’s leadership since 2023 underscores his pivotal role in shaping the lab’s research direction.
Nathalie P. de Leon is an Associate Professor of Electrical and Computer Engineering at Princeton University and an Associated Professor of Physics. She is affiliated with the Princeton Plasma Physics Laboratory and co-leads the Co-Design Center for Quantum Advantage (C 2 QA). Her lab focuses on quantum hardware development using color centers in wide bandgap materials and superconducting qubits, with applications in quantum networks and nanoscale sensors. Ph.D., Chemical Physics, Harvard University, 2011 B.S., Chemistry, Stanford University, 2004 Her research spans optical materials , light-matter interactions , and quantum information processing , integrating nanophotonics , surface science , and quantum metrology . Recent publications highlight advances in diamond-based quantum sensors , superconducting circuit engineering , and noise/loss mitigation in quantum systems. Scientific Awards: APS Rolf Landauer and Charles H. Bennett Award in Quantum Computing (2023) DOE Early Career Award (2018) DARPA Young Faculty Award (2018) NSF CAREER Award (2018) Her lab has advised 22 graduate students and collaborates extensively with institutions like Princeton Plasma Physics Laboratory, University of Chicago, UZH, and Brookhaven National Laboratory. Current projects emphasize hybrid quantum devices , telecom band photonics , and many-body quantum physics .
Professor Niki Trigoni is a faculty member at the University of Oxford's Department of Computer Science and a Governing Body Fellow at Kellogg College. She holds the rank of Professor of Computing Science. Her research focuses on intelligent and autonomous sensor systems, with applications in positioning, healthcare, environmental monitoring, and smart cities. Trigoni leads the Cyber Physical Systems Group and directs the EPSRC Centre for Doctoral Training on Autonomous Intelligent Machines and Systems (AIMS), which integrates robotics, machine learning, verification/control, and sensor networks. Education: DPhil from the University of Cambridge (2001), followed by postdoctoral research at Cornell University (2002–2004) and a Lectureship at Birkbeck College (2004–2007). Current roles include leadership in AIMS and the Cyber Physical Systems Group. Research Interests: Her work spans sensor networks, inertial navigation, mmWave radar applications, and deep learning for localization and mapping. Recent projects include indoor positioning systems for emergency responders and wildlife monitoring. She has open positions for PhD and postdoc researchers in areas like sensor fusion, human-robot interaction, and SLAM. Publications: Over 50+ peer-reviewed articles, including work on mmPoint, P2-Net, and RandLA-Net. Her research emphasizes real-world applications in robotics and autonomous systems. Grants and Leadership: Received a 3-year NIST grant (2017) for indoor positioning systems and leads initiatives in cyber-physical systems. Active in conference organization, e.g., TPC chair for Sensys 2017 and IPSN 2016. Labs/Teams: Cyber Physical Systems Group focuses on sensor systems, robotics, and autonomous systems. Collaborations span academia and industry, addressing challenges in smart cities and healthcare.
Larry Heck is a Professor at the Georgia Institute of Technology with joint appointments in the School of Electrical and Computer Engineering and the School of Interactive Computing. He holds the Rhesa S. Farmer Advanced Computing Concepts Chair and is a Georgia Research Alliance Eminent Scholar. His research focuses on machine learning, deep learning, natural language processing, conversational systems, and speech/speaker recognition. He directs the AI Virtual Assistant (AVA) Lab, advancing next-generation AI assistants. Dr. Heck has held leadership roles in industry, including at Microsoft, Google, Samsung, and Viv Labs, and has over 50 U.S. patents. Education: BSEE from Texas Tech University (1986) MSEE and PhD in Electrical Engineering from Georgia Tech (1991) Research Interests: Dr. Heck’s work bridges machine learning and human-centric AI, with emphasis on conversational systems, multimodal interaction, and real-world applications. His AVA Lab develops AI assistants that integrate visual, auditory, and contextual cues for natural interaction. Recent projects include multimodal sensor integration, dialogue systems for caregiving networks, and embodied AI for avatar animation. Awards: IEEE Fellow (2020) Academy of Distinguished Engineering Alumni, Georgia Tech (2017) Distinguished Engineer Award, Texas Tech University (2017) Advising & Grants: While primarily focused on industry collaboration, Dr. Heck mentors students through Georgia Tech’s interdisciplinary programs. His research is funded by government agencies and corporate partnerships, including the NSA and DARPA. Labs & Teams: The AVA Lab collaborates with academia and industry to create AI systems that understand context, gestures, and environment. Current initiatives include multimodal dialogue datasets (e.g., OKCV, SensorQA) and reinforcement learning frameworks for real-time systems.
Dusan Milosevic is an Assistant Professor at Eindhoven University of Technology (TU/e) in the Electrical Engineering department. He is affiliated with the Mixed-Signal Microelectronics research group and the RF Sensing & Communication Lab. His research focuses on analog and RF electronics, particularly in power amplifiers, ultra-low-power RF systems, and energy harvesting. He holds an MSc from the University of Niš and a PhD from TU/e. Education: MSc in Electronics and Telecommunications Engineering (University of Niš, 2001) PhD in Electrical Engineering (TU/e, 2009) Research Interests: Design of RF power amplifiers and mm-wave circuits Ultra-low-power communication systems RF energy harvesting technologies High-efficiency analog circuit design His work emphasizes circuit techniques for wireless communication and integrates analog methods with digital control for improved performance. Teaching: Electronic Circuits 1 RF Transceivers 1: Fundamentals Electronics: Selected Topics Collaborations: Active in mm-wave communication, satellite links, and sensor networks. His recent work includes inter-satellite link front-ends and optoelectronic modulation systems. Labs/Teams: Leads the RF Sensing & Communication Lab, focusing on mm-wave systems and energy-efficient RF design.
Diogo Carbonera Luvizon is a Researcher at the Max-Planck-Institut für Informatik (MPI-INF) in Saarbrücken, Germany, and a member of the Visual Computing and Artificial Intelligence (VIA) Research Center. He holds a PhD in Computer Vision and Machine Learning from CY Cergy Paris University (2019), and Bachelor's and Master's degrees in Engineering and Applied Computing from UTFPR, Brazil. His research focuses on solving complex problems in Computer Vision, Computer Graphics, and Deep Learning, particularly in human modeling and real-time systems. Education: PhD (2019) - CY Cergy Paris University; M.Sc. (2015) - UTFPR; B.Sc. (2011) - UTFPR. Research interests include 3D human pose estimation, action recognition, multitask learning, and novel view synthesis. He has contributed to patents on multiplane image generation (Samsung) and vehicle speed measurement systems. His work has been recognized with awards like the Best Paper Honorable Mention at GCPR-VMV 2022 and Best Presentation Award at ETIS Lab (2018). He has developed open-source tools, including the deephar repository for human action recognition and pose estimation. His current affiliations include MPI-INF and the VIA Research Center, a partnership between MPI-INF and Google.
Dr. Nilanjan Banerjee is a Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He leads the Mobile, Pervasive, and Sensor System Lab, focusing on embedded and distributed systems for mobile, pervasive, and sustainability-based computing. His research spans renewable energy-driven systems, health diagnostics, mobile usability, and experimental testbed design. He holds a Ph.D. in Computer Science from the University of Massachusetts (2009), an M.S. from the same institution (2007), and a B.Tech. (Hons) from the Indian Institute of Technology (2004). Dr. Banerjee's work emphasizes interdisciplinary innovation, including low-power wearable devices for health monitoring (e.g., RestEaZe), cybersecurity frameworks for embedded systems (e.g., CARE), and sensor-based solutions for environmental sustainability. His contributions address challenges in mobility, energy efficiency, and accessibility, such as the Presight sidewalk localization system for visually impaired riders and the Inviz gesture-recognition textile sensors. His recent publications (2018–2021) reflect a focus on health technology, cybersecurity, and sustainable systems. Notable trends include: Integration of machine learning with sensor data for medical applications (e.g., sleep analysis, infection detection) Development of lightweight security protocols for embedded devices Exploration of renewable energy solutions for mobile and sensor networks No scientific awards are explicitly listed in the provided text. His academic advising and grant activities are not detailed here, but his lab's active research suggests significant collaborative projects. The lab also pioneers educational strategies in mobile app development and inclusive faculty recruitment through peer education programs like STRIDE.
Rahim Rahimi is an Assistant Professor of Materials Engineering at Purdue University, associated with the College of Engineering. His research focuses on advanced materials for biomedical applications, environmental sensing, and flexible electronics. Key interests include developing smart sensors for healthcare, antibacterial coatings for medical implants, and sustainable agricultural monitoring systems. Research emphasizes targeted drug delivery systems via smart capsules, environmental sensor networks for water quality and soil health, and nanotechnology applications in wearable devices. Notable projects include oxygen-generating surgical meshes for wound healing and low-cost wireless sensors for precision agriculture. His work bridges materials science with clinical and environmental challenges, leveraging plasma deposition techniques and nanomaterial functionalization. Recent efforts focus on self-calibrating sensors and integrating machine learning for manufacturing optimization. No scientific awards are explicitly listed in the provided information. His advisory role and grant activities are inferred through his research outputs in materials engineering and biomedical innovation. Rahimi collaborates across disciplines within Purdue's engineering ecosystem, contributing to labs focused on bio-inspired materials and flexible electronics. Future work aims to advance implantable medical devices and scalable sensor technologies for global health applications.
