David B. Lindell is an Assistant Professor in the Department of Computer Science at the University of Toronto, with affiliations to the Vector Institute and AXL. He is a founding member of the Toronto Computational Imaging Group. His research focuses on physically based intelligent sensing, integrating physical models, signal processing, and AI to advance sensing systems. Notable projects include imaging around corners, through scattering media, and developing machine learning algorithms for 3D scene reconstruction. Education: Ph.D. in Computational Imaging from Stanford University (advisor: Gordon Wetzstein). Awards include the 2024 Ontario Early Researcher Award and the Best Student Paper at CVPR 2025. His work combines computational imaging with applications in computer graphics and autonomous systems. Research interests span non-line-of-sight imaging, single-photon sensing, and neural representations. Key contributions include the Light-Cone Transform (Nature 2018), confocal diffuse tomography (Nature Communications 2020), and AutoInt (CVPR 2021). His lab develops systems for 3D reconstruction, transient imaging, and photon-efficient sensors. Selected grants and support: NSF CAREER Award, DARPA REVEAL program, and KAUST Visual Computing Center funding. Active collaborations with industry and academic institutions on autonomous driving and medical imaging applications.
Andre Levchenko is the John C. Malone Professor of Biomedical Engineering at Yale University, with secondary appointments in the Department of Neurosurgery and affiliations with the Cancer Signaling Networks, Immunology, and the Yale Program in Neurodevelopment and Regeneration. His research focuses on systems biology, signal transduction, and cell-cell communication, utilizing microfluidics and computational modeling to study cancer progression, stem cell behavior, and neurological disorders. PhD, Columbia University MEng, Moscow Institute of Physics and Technology Levchenko's work explores how cells process dynamic signals to make critical decisions, particularly in glioblastoma migration, organoid development, and cardiovascular tissue engineering. His lab develops innovative microfluidic platforms and mathematical models to dissect multicellular communication and signaling networks. Recent publications highlight his contributions to understanding YAP-driven cancer invasion , NOTCH signaling in angiogenesis , and metabolic regulation of hypoxia responses . He has pioneered methods for organoid modeling and single-cell analysis , advancing precision in biological signaling studies. Scientific Awards : Computational Molecular Biology Post-Doctoral Fellowship (Burroughs Wellcome Fund) National Academies Keck Futures Conference Invitee Distinguished Guest Lecturer, University of Virginia American Asthma Foundation Early Excellence Award Fellow, American Institute for Medical and Biological Engineering Levchenko leads the Levchenko Lab at the Yale Systems Biology Institute, collaborating with institutions like Mayo Clinic and Yale Cancer Center. His research has received recognition in Faculty of 1000 and multiple journal highlights.
Mayank R. Mehta is a Professor at the University of California, Los Angeles (UCLA), holding joint appointments in the Departments of Physics & Astronomy, Neurology, and Neurobiology. He is a member of the Brain Research Institute and the W. M. Keck Center for Neurophysics at UCLA. His research bridges experimental and theoretical neuroscience, focusing on how neuronal networks encode space-time, the role of brain rhythms in learning and memory, and the impact of sleep and virtual reality on neural dynamics. His recent publications highlight breakthroughs in understanding hippocampal spatiotemporal selectivity, dendritic activity during behavior, and the causal influence of visual cues on memory neurons. Notable findings include the discovery that dendrites generate ten times more spikes than neuronal cell bodies and the modulation of hippocampal theta rhythms in virtual reality. Research Themes: Neurophysics of spatial-temporal coding Dendritic contributions to learning Virtual reality and brain plasticity Neural oscillations in memory consolidation Key Collaborators: Bert Sakmann (Max Planck Florida Institute) Thomas Hahn (Bernstein Center Heidelberg/Mannheim) Maryam Ghorbani (UCLA) Mehta's lab at UCLA trains graduate and postdoctoral researchers in cutting-edge techniques combining hardware development, electrophysiological recordings, and biophysical modeling. His work has significant implications for treating learning and memory disorders like Alzheimer's disease.
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.
Jungsang Kim is the Schiciano Family Distinguished Professor of Electrical and Computer Engineering and Professor of Physics at Duke University. He serves as Associate Director of the Duke Quantum Center and leads the Multifunctional Integrated Systems Technology group. Quantum Computing with Trapped Ions Quantum Information Science Photonic Device Development Quantum Communication Networks His research focuses on scalable quantum information processors using trapped atomic ions and advanced photonic technologies. Key innovations include microfabricated ion traps, optical MEMS, and cryogenic systems for quantum integration. Recent publications highlight trapped ion quantum simulation, high-fidelity gate design, and photonic error mitigation. His group develops practical quantum hardware and co-founded IonQ, the first publicly traded pure-play quantum computing company. Fellow, American Physics Society (2021) Stansell Family Distinguished Research Award (2016) Fellow, National Academy of Inventors Fellow, Optica (formerly OSA) Kim's work bridges quantum physics and engineering, with over 80 patents and leadership in Duke's quantum computing initiatives. He recently stepped down as IonQ's CTO while maintaining active research and strategic roles at Duke.
Aditya K. Jagannatham is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur). With expertise in wireless communications and signal processing, he has established himself as a leading researcher in 5G/6G technologies, MIMO systems, and cognitive radio networks. His educational background includes: PhD in Electrical and Computer Engineering from UC San Diego (2007) M.S. in Electrical and Computer Engineering from UC San Diego (2004) B.Tech. in Electrical Engineering from IIT Bombay (2001) Professor Jagannatham's research primarily focuses on next-generation wireless communication systems, with special emphasis on 5G and 6G technologies. His work spans OTFS modulation, Terahertz communications, Visible Light Communication (VLC), Intelligent Reflecting Surface (IRS) technology, Massive MIMO, mmWave MIMO, Non-Orthogonal Multiple Access (NOMA), and Filter-Bank Multi-Carrier (FBMC) systems. His research integrates theoretical analysis with practical implementation challenges, addressing critical issues in modern wireless networks. His recent publications demonstrate a strong trend toward advanced signal processing techniques for next-generation wireless systems, particularly focusing on Sparse Bayesian Learning approaches for channel estimation, cooperative communication systems with energy harvesting capabilities, and millimeter wave MIMO technologies. His work bridges theoretical communication theory with practical implementation challenges in emerging wireless standards. Professor Jagannatham has received numerous prestigious awards and fellowships: Arun Kumar Endowed Chair Professorship (2019) Qualcomm Innovation Fellowship (2018) P.K. Kelkar Young Faculty Research Fellowship for excellence in research (2015-2018) IEEE Signal Processing Society travel grant to attend ICASSP 2015 Gopal Das Bhandari Memorial Distinguished Teacher Award (2012-13) Cal(IT)2 fellowship for graduate study at UC San Diego As an educator, Professor Jagannatham has received commendation letters from the Director of IIT Kanpur for excellence in teaching courses including EE624 Information and Coding Theory, EE670 Wireless Communications, and EE320 Principles of Communication Systems. His research has attracted significant funding, though specific grant details are not provided in the available information. He likely supervises graduate students working on cutting-edge wireless communication research. Professor Jagannatham is based in the Advanced Centre for Electronic Systems (ACES) at IIT Kanpur, where he leads research in wireless communications. His work appears to be closely connected with the Center for Developing Intelligent Systems (CDIS) and other research centers at IIT Kanpur focused on next-generation communication technologies.
Anthony Rollett is a Professor in the Department of Materials Science and Engineering at Carnegie Mellon University , where he has been a faculty member since 1995. He serves as the Principal Investigator and Co-Director of the NASA-supported Institute for Model-Based Qualification & Certification of Additive Manufacturing (IMQCAM) and co-director of the Next Manufacturing Center . Prior to CMU, he held leadership roles at Los Alamos National Laboratory (1991-1995). Education: Ph.D., Materials Engineering, Drexel University (1987) MA, Metallurgy and Materials Science, Cambridge University (1977) Research Interests: Rollett’s work focuses on microstructural evolution and microstructure-property relationships in 3D using experiments and simulations. His expertise spans additive manufacturing , metal 3D printing , materials for energy systems , grain growth , recrystallization , and stereology , with techniques like high-energy diffraction microscopy (HEDM) and dynamic x-ray radiography (DXR) . Scientific Contributions: He has over 320 peer-reviewed publications and an h-index >80 . His recent articles highlight machine learning for laser processing , fatigue analysis of additively manufactured alloys, and design optimization for heat exchangers in supercritical CO2 and solar thermal applications . Scientific Awards: Fellow of ASM International (1996) Fellow of the Institute of Physics (UK) (2004) Fellow of The Minerals, Metals & Materials Society (TMS) (2011) Cyril Stanley Smith Award (TMS, 2014) Member of Honor, French Metallurgical Society (2015) US Steel Professor (2017) Francqui International Professor (2020-2021) International FAME Award (2023) Leadership & Impact: Rollett co-led the development of a NASA Space Technology Research Institute for additive manufacturing and established a new master’s program in additive manufacturing (2018). His research group is funded by industry , federal agencies , and Pennsylvania state grants . He also serves on the Basic Energy Science Advisory Committee and Defense Programs Advisory Committee for the Department of Energy.
James C. Hoe is Professor of Electrical and Computer Engineering at Carnegie Mellon University (College of Engineering). He is on sabbatical at MangoBoost and directs research in computer architecture, reconfigurable computing, and high-level hardware design. Education Ph.D., Electrical Engineering and Computer Science, MIT (2000) M.S., Electrical Engineering and Computer Science, MIT (1994) B.S., Electrical Engineering and Computer Science, UC Berkeley (1992) Research Interests Professor Hoe’s work spans computer architecture , reconfigurable computing , FPGA architectures , and high-level hardware synthesis . His group created the CoRAM abstraction for virtualized FPGA computing and leads efforts in power-efficient accelerators, in-network computing, and security-oriented FPGA systems. Scientific Awards IEEE Fellow (2013) Intel Outstanding Researcher Award (2021) Research Funding & Projects Intel / VMware Crossroads 3D-FPGA Academic Research Center – co-leading exploration of FPGA roles in future datacenters. DARPA BRASS program ($2.7 M, 4 years) – ensuring long-lived software systems remain robust to resource changes. Pigasus open-source IDS – world’s fastest FPGA-accelerated intrusion-detection system (100 Gb/s on one server). Labs & Teams He heads activities within the Computer Architecture Lab at Carnegie Mellon (CALCM) , supervising graduate researchers on CoRAM++, SPIRAL autotuning, and FPGA overlays for stream processing.
Di Zhu is a Presidential Young Professor in the Department of Materials Science and Engineering at the National University of Singapore (NUS). He holds a B.Eng. from Nanyang Technological University and M.Sc./Ph.D. from MIT, both in Electrical Engineering. His postdoctoral research at Harvard focused on lithium niobate integrated photonics and superconducting detectors. He previously worked as a research scientist and PI at A*STAR's Institute of Materials Research and Engineering (IMRE). Research Interests : Integrated quantum photonics, superconducting detectors, nonlinear optics, and nanofabrication. His group develops scalable quantum photonic devices using lithium niobate and superconducting materials, emphasizing applications in quantum computing, communication, and sensing. Awards : National Research Foundation (NRF) Fellowship Harvard Quantum Initiative (HQI) Postdoctoral Fellowship MIT Jin-Au Kong Thesis Award Advising & Recruitment : Actively recruiting postdocs, PhD students, and interns in areas like integrated photonics, quantum optics, and superconducting detectors. Positions include work on thin-film lithium niobate, quantum simulation, and microwave-optical transduction. Group website: dizhulab.org .
Dr. Rajesh Bera is a Research Fellow at ICFO's Functional Optoelectronic Nanomaterials group specializing in quantum-confined nanostructures. His research examines ultrafast carrier dynamics, excitonic properties, and optoelectronic applications of nanomaterials including quantum dots, nanoplatelets, and hybrid nanostructures. Current investigations focus on intraband transitions in doped nanocrystals, orientation-dependent excitonic behavior in 2D materials, and charge transfer mechanisms in heterostructure devices. Work bridges fundamental photophysics with applications in photodetection, sensing, and energy conversion. Recent publications demonstrate expertise in time-resolved spectroscopy of quantum materials, nanomaterial synthesis via colloidal chemistry, and rational design of optoelectronic devices. Continually develops novel characterization methods to probe ultrafast processes at nanoscale interfaces.
Gordon Wetzstein is an Associate Professor of Electrical Engineering and, by courtesy, Computer Science at Stanford University. He leads the Stanford Computational Imaging Lab and co-directs the Stanford Center for Image Systems Engineering (SCIEN). His research focuses on computational imaging, wearable computing, and neural rendering, blending computer graphics, vision, AI, and optics. Education: Ph.D., Computer Science, University of British Columbia (2011) Diploma, Media Systems Science, Bauhaus University (2006) Research Interests: His work spans computational displays , holography , non-line-of-sight imaging , and AI-driven optical systems . Key projects include Autofocals (gaze-contingent eyeglasses) and neural holography systems. He explores applications in AR/VR, medical imaging, and scientific visualization. Publications: Recent work includes advances in 3D holography, gaze-tracking systems, and AI-optics integration. His papers address challenges in display efficiency, light-field processing, and real-time imaging. Awards: Fellow of Optica NSF CAREER Award (2016) PECASE (2019) ACM SIGGRAPH Significant New Researcher Award (2018) Advising & Grants: He advises over 20 doctoral and postdoctoral students. His lab collaborates with industry (e.g., Raxium, Google) and has secured grants from NSF, DARPA, and private foundations. Labs & Teams: His lab develops cutting-edge systems like neural holography and non-line-of-sight imaging. The SCIEN center fosters interdisciplinary image systems research.
Emma Maclean is a Part-Time Lecturer and Module Coordinator in the Division of Occupational Therapy and Arts Therapies at Queen Margaret University. She holds qualifications including MA (Distinction), PG Dip, and BA (Joint Honours). Her roles include teaching on the MSc Music Therapy program, focusing on supervision for practice education placements and interdisciplinary studies. Education: MA (Distinction) in Music Therapy PG Dip in Music Therapy BA (Joint Honours) Research Interests: Partnership working, collaboration, evaluation, group work, and mental health across children, adults, and older populations. She employs research methods such as case studies and focus groups. Publications & Presentations: Her work includes a peer-reviewed article on partnership evaluation and a chapter in Arts Therapies in Schools . She co-presented a plenary session at the 2016 BAMT conference titled Music Therapy in a Changing Landscape . Affiliations: British Association for Music Therapy (BAMT) representative on Allied Health Professionals Federation Scotland (AHPFS) Registered with the Health and Care Professions Council Fellow of the Higher Education Academy Clinical Work: Works as a lead music therapist in the NHS, specializing in pediatric services, adult/older adult mental health (including dementia), and supervision. Engages in freelance violin performance with ceilidh bands, tango groups, and orchestras.
Janne Lindqvist is an Associate Professor at the Department of Computer Science, Aalto University. His research bridges security engineering, human-computer interaction (HCI), and privacy, with a focus on making security systems usable and user-centric. University: Aalto University Department: Department of Computer Science Rank: Associate Professor Email: janne.lindqvist@aalto.fi Lindqvist’s work spans security engineering , privacy systems , and user research , emphasizing practical authentication methods, password management, and human behavior in security contexts. He explores how users interact with systems like TPM APIs, gesture passwords, and mobile authentication mechanisms. Recent publications highlight trends in authentication systems , ubiquitous computing security , and mobile user behavior . Key themes include biometric authentication, gesture-based security, and balancing usability with cryptographic robustness. CHI'25 Honorable Mention Award CHI'24 Best Paper Award His research integrates empirical studies with technical implementations, such as analyzing password forgetting patterns and developing acoustic sensing for vehicle detection (e.g., Auto++, BO-Ear). Collaborative efforts span machine learning, psychology, and embedded systems.
Frank L. Hammond III serves as Assistant Professor at Georgia Tech's Woodruff School of Mechanical Engineering since April 2015, directing the Adaptation Robotic Manipulation (ARM) Laboratory. A Carnegie Mellon PhD graduate, he previously held postdoctoral positions at MIT and Harvard as a Ford Fellow. His interdisciplinary work bridges mechanical engineering, biomedical applications, and computational design. Education Ph.D. in Mechanical Engineering, Carnegie Mellon University M.S. in Mechanical Engineering, University of Pennsylvania M.S. in Electrical Engineering, University of Pennsylvania B.S. in Electrical Engineering & Biomedical Engineering, Drexel University Hammond's research pioneers adaptive robotic manipulation (ARM) systems that operate in unstructured human environments through bioinspired computational design. His lab develops xenomorphic (non-biomorphic) robots using soft pneumatic actuation, flexible electronics, and machine learning to achieve biological-level versatility. Key application domains include wearable human augmentation devices , haptic-enabled surgical teleoperation , and autonomous soft platforms for medical and industrial use. The ARM methodology integrates empirical biomechanics characterization with simulation-driven optimization and rapid prototyping. Analysis of his 15 most recent publications (2023-2025) reveals three dominant trends: (1) Medical rehabilitation breakthroughs through intention-driven exoskeletons with soft bioelectronics, (2) Novel locomotion strategies for soft robots in complex environments (sand, water, cluttered spaces), and (3) Advanced haptic feedback systems leveraging multimodal sensory substitution for proprioceptive restoration. These works consistently bridge biomechanics, control theory, and human factors. Awards Ford Postdoctoral Research Fellowship at Harvard School of Engineering Hammond actively mentors graduate researchers including PhD candidates Lucas Tiziani (soft actuators) and Bangyuan Liu (earthworm robotics), and Master's student Alex Hart (pediatric haptics). His lab secures research funding for projects like tunable mechanical interfaces for neuropathy treatment and cognition-focused wearable devices, with strong industry and clinical partnerships evident in co-authored medical device publications. The ARM Lab maintains robust collaborations across Georgia Tech's robotics, neuroscience, and biomedical engineering communities. The Adaptation Robotic Manipulation Laboratory operates from Whitaker Building Room 4102, housing specialized facilities for soft robot fabrication (3D printing, shape deposition manufacturing) and biomechanics testing. Current projects include pediatric haptic feedback displays, biomimetic swimming robots, and kirigami-skinned earthworm robots for subsurface locomotion. The lab emphasizes translational research with multiple pending medical device patents and active participation in K-12 STEM outreach programs.
John P. O'Doherty serves as the Fletcher Jones Professor of Decision Neuroscience within Caltech's Division of Humanities and Social Sciences, holding continuous faculty appointments since 2004 (Assistant Professor 2004-07, Associate Professor 2007-09, Professor 2009-present, Fletcher Jones Professor 2021-present). He previously directed the Caltech Brain Imaging Center (2013-17) and maintains affiliations with the T&C Chen Center for Social and Decision Neuroscience. His educational background includes a B.A. from University of Dublin, Trinity College (1996) and D.Phil. from University of Oxford (2000). His research focuses on computational and neural mechanisms of reward-based learning and decision-making , employing fMRI, intracranial recordings, and mathematical modeling to investigate how the brain solves complex decision problems through evolutionarily conserved algorithms. Key areas include Reinforcement learning systems (model-based/model-free arbitration) Observational and social learning mechanisms Neural representation of value, risk, and uncertainty Computational phenotyping of mental disorders Temporal dynamics of goal persistence Analysis of his 2023-2025 publications reveals dominant trends in computational psychiatry (problem gambling, autism traits), hierarchical decision-making, and neuroeconomic modeling of social behavior. His work consistently integrates cross-species computational frameworks with human neuroimaging to identify transdiagnostic mechanisms. While specific awards beyond his endowed professorship aren't detailed, his leadership as Brain Imaging Center Director and prolific high-impact publications demonstrate significant recognition. Current advising includes graduate researcher Sneha Aenugu on goal-persistence projects, with administrative support from Mary A. Martin (mmartin@caltech.edu). His active research program continues to pioneer computational approaches to understanding decision pathologies.
