جست‌وجوی استاد و پژوهشگر

Subhasish Mitraمشاهده پروفایل

استاد

• Robust Computing
• NanoSystems
• Electronic Design Automation (EDA)
• +۳ مورد دیگر

Subhasish Mitra is the William E. Ayer Professor of Electrical Engineering and Computer Science at Stanford University, holding dual appointments in both departments. He leads the Stanford Robust Systems Group and serves on the leadership team of the Microelectronics Commons AI Hardware Hub under the US CHIPS and Science Act. His research spans Robust Computing, NanoSystems, Electronic Design Automation (EDA), and Neurosciences, with breakthroughs in X-Compact test compression, carbon nanotube computing, and 3D integration. He has held international roles like the Carnot Chair at CEA-LETI and Visiting Professorships globally. Education & Honors: Recipient of over 40 awards including the IEEE Computer Society’s Harry H. Goode Memorial Award, ACM/IEEE’s A. Richard Newton Technical Impact Award, and the Intel Achievement Award. He earned top academic accolades from IIT Kharagpur and Jadavpur University, and is a Fellow of ACM and IEEE. Research Impact: Pioneered first-of-their-kind systems like the carbon nanotube computer and monolithic 3D integration. His work on robust computing techniques like QED validation and X-Compact compression has industry-wide adoption, saving billions in manufacturing costs. Collaborates with industry leaders like Intel, Google, and Samsung. Publications & Grants: Over 400 publications, including award-winning papers in DAC, ISSCC, and IEEE journals. Leads grants from NSF, DoE, and industry partnerships. His lab explores cutting-edge topics like neuromorphic computing, 3D thermal scaffolding, and AI hardware acceleration. Administration & Outreach: Serves as Associate Chair (Faculty Affairs) for Stanford’s Computer Science Department. Recognized by students for mentorship, and frequently invited to global forums like the World Economic Forum and National Academy of Engineering.

Akhilesh Jaiswalمشاهده پروفایل

استادیار

• Device-Circuit Co-design
• Processing-in-Pixel
• In-Memory Computing
• +۴ مورد دیگر

Dr. Akhilesh Jaiswal serves as Assistant Professor of Electrical and Computer Engineering at the University of Wisconsin-Madison, where his research pioneers device-circuit co-design for next-generation computing systems. His work focuses on enabling extreme-edge intelligence through processing-in-pixel technology, in-memory computing architectures, and bio-inspired neuromorphic systems. His academic credentials include: PhD in Nano-electronics from Purdue University (2019) MS from the University of Minnesota (2014) Bachelor of Technology from Shri Guru Gobind Singhji Institute of Engineering and Technology (2011) Dr. Jaiswal's research program centers on revolutionizing edge computing through hardware innovations that integrate sensing and processing. His device-circuit co-design approach leverages alternate state variables to create energy-efficient systems for real-time applications, with particular emphasis on retina-inspired sensors and photonic memory architectures. This work bridges semiconductor physics with AI acceleration needs, targeting applications from autonomous systems to biomedical devices. Analysis of his 2023-2025 publications reveals dominant themes in photonic SRAM-based in-memory computing (40% of output), retina-inspired motion processing (30%), and secure hardware architectures (20%). His team consistently develops novel bitcell designs that enable XOR logic execution within memory arrays while maintaining compatibility with CMOS fabrication processes. Recent work shows increasing focus on biomedical applications of processing-in-pixel technology. His distinguished recognition includes: Three consecutive ISI Exploratory Research Awards (2020-2023) IEEE Brain Community Best Paper Award (2022) 27 issued US patents with multiple pending applications Nomination for USC Moore Inventor Fellowship (2022) Dr. Jaiswal actively mentors graduate researchers through ECE 790/890/990 courses while securing exploratory funding through ISI and Keston Foundation awards. His patent portfolio demonstrates exceptional translational impact, with industry game-changer classifications from USPTO. The 2022 VLSI-SoC nomination and multiple research highlights in major outlets validate his contributions to hardware security and neuromorphic vision sensors. His laboratory develops integrated hardware platforms combining magnetic tunnel junctions, photonic memory, and CMOS image sensors to create unified processing-in-sensor systems. Current projects include retina-inspired motion segmentation for event cameras and electro-optic frequency transducers for quantum computing interfaces, with strong industry collaboration through patent licensing.

• Natural Language Processing
• Knowledge Graphs
• Machine Learning
• +۵ مورد دیگر

Dr. Sirui Li is a Lecturer at Murdoch University's School of Information Technology within the College of Science, Technology, Engineering and Mathematics. Her research focuses on Artificial Intelligence, Natural Language Processing (NLP), Machine Learning, Knowledge Graphs, Data Analysis, Temporal Data, and Multi-modal Models, with applications in medicine, agriculture, and mining. She collaborates with industry partners like BHP and has published in journals such as Food Chemistry and Knowledge and Information Systems , as well as conferences like ICSME and IJCNN. Education: Bachelor of Advanced Computing (Honours) in Computer Science at Australian National University Master of Computing (Specialising in AI) at ANU Ph.D. in Information Technology (AI) at Murdoch University Research interests include interdisciplinary applications of AI, such as clinical coding privacy solutions, disease spread modeling, and drug repurposing for pandemics. Her work emphasizes practical industry integration, demonstrated through awards like the 2024 EMNLP Best Demo Award and the 2023 Iron Ore Circuit Hackathon innovation prize. Professional roles include IEEE Western Australia Section committee membership, conference chair positions, and peer review for top journals. She actively mentors students pursuing Honours, Master's, or PhD projects in her areas of expertise.

Sohmyung Haمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Neural Engineering
• Wearable Sensors
• +۳ مورد دیگر

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.

Teresa Puthusseryمشاهده پروفایل

دانشیار

• Retinal Neurobiology
• Neurophysiology
• Retinal Degeneration
• +۳ مورد دیگر

Dr. Teresa Puthussery is an Associate Professor in the School of Optometry & Vision Science at the University of California, Berkeley. Her research focuses on retinal neurobiology and neurophysiology, investigating how visual signals are encoded in healthy retinas and disrupted during degeneration. She uses advanced techniques like patch-clamp electrophysiology, immunohistochemistry, and microscopy to study retinal circuits, neurotransmitter receptors, and ion channels. Dr. Puthussery teaches courses on vision science anatomy, physiology, and problem-based learning, including VISION SCIENCE 206B/C and 260C. Her research explores questions such as how retinal neurons extract motion/spatial details, how photoreceptor mutations cause degeneration, and how inner retinal circuits adapt post-photoreceptor loss. Recent work includes studies on ON-type direction-selective ganglion cells, optogenetic therapy for vision restoration, and calcium dynamics in foveal ganglion cells post-degeneration. She collaborates on projects involving primate and rodent models, contributing to understanding retinal disease mechanisms and therapeutic targets. Dr. Puthussery’s lab (retinalab.berkeley.edu) emphasizes translational research, bridging basic science and clinical applications. Her work has been published in journals like Nature and Cell Reports , with a focus on retinal degeneration, synaptic plasticity, and optogenetic interventions. She actively participates in training future vision scientists through Berkeley’s Optometry program and oversees GSI affairs as a faculty advisor.

• Computational Neuroscience
• Neural Networks
• Retinal Computation
• +۷ مورد دیگر

Joel Zylberberg is an Adjunct Assistant Professor at the University of California, Los Angeles (UCLA), affiliated with the Department of Ophthalmology within the School of Medicine . His research bridges Computational Neuroscience , Neural Networks , and Machine Learning , focusing on how neural activity and biological mechanisms inform artificial intelligence and visual cortex dynamics . Joel's work explores retinal computation , population coding , and neural adaptation , often analyzing mouse visual cortex and neurophysiological data . His recent publications highlight trends in dynamic retinal processes , stimulus-driven network topology , and brain-inspired machine learning , emphasizing the interplay between biophysics and computational modeling . Collaborators include Greg Field (UCLA), Richard Born (Harvard), and Michael DeWeese (UC Berkeley), with affiliations spanning institutions like University of Washington and University of California, San Diego (UCSD). His work appears in journals such as Nature Neuroscience , Neuron , and PLOS Computational Biology .

Jessica E. Treismanمشاهده پروفایل

استاد

• Developmental genetics
• Cell signaling
• Synapse formation
• +۵ مورد دیگر

Jessica E. Treisman is a Professor in the Department of Cell Biology and Department of Ophthalmology at NYU Grossman School of Medicine. Her research focuses on developmental genetics and molecular neuroscience, particularly in the context of visual system development and synapse formation in Drosophila . Research Interests: Cell fate determination, tissue morphogenesis, neural circuit assembly, and corneal lens development Contact: Jessica.Treisman@nyulangone.org | 212-263-1031 Lab: Treisman Lab, Skirball Institute, New York, NY Her work explores how intrinsic transcription factors and extrinsic signaling pathways interact to regulate cell differentiation and tissue organization in the Drosophila visual system, with implications for understanding human corneal development and neural connectivity disorders. Recent publications highlight her contributions to understanding: Molecular mechanisms of corneal lens curvature formation Regulation of synaptic targeting specificity Role of Sidekick in epithelial junction dynamics Transcriptional synergy between Glass and EGFR signaling The Treisman Lab employs interdisciplinary approaches in Drosophila genetics to uncover fundamental principles of cell signaling and neural circuit development, with potential applications in human vision research and developmental disorders.

David Klindtمشاهده پروفایل

استادیار

• NeuroAI
• Computational Neuroscience
• Sensory Processing
• +۳ مورد دیگر

David Klindt is Assistant Professor at Cold Spring Harbor Laboratory, leading research at the intersection of biological systems and artificial intelligence. His lab investigates how brains process sensory information and generalize knowledge across contexts, studying neural representations to inspire robust AI models. Research combines computational neuroscience and machine learning to develop algorithms mimicking biological learning efficiency. Current projects examine latent computing in biological neural networks through dynamical systems frameworks, sparse coding principles in neural representations, and geometric organization in visual processing. His group develops methods for mechanistic interpretability, self-supervised learning identifiability, and compute-efficient inference. Recent publications analyze toroidal representations in grid cells, retinal feature detection, and Cryo-EM structure disentanglement. Dr. Klindt's work has been recognized through publications in Nature Communications, eLife, and NeurIPS. Before joining CSHL, he was a Machine Learning Research Scientist at Meta Reality Labs and postdoctoral researcher at Stanford University and NTNU. He holds a Ph.D. in Computational Neuroscience and Machine Learning from the University of Tübingen.

• Machine Learning
• Computer Vision
• Signal Processing
• +۶ مورد دیگر

Dongwook Kim is affiliated with the Korea Advanced Institute of Science & Technology (KAIST) as a faculty member in the Department of Business and Technology Management under the College of Business. His research spans multiple domains including machine learning, robotics, signal processing, and biomedical engineering. Key contributions in Computer Vision (CNN-based semantic segmentation, 3D point cloud analysis) Significant work in Hardware Design (energy-efficient processors, neuromorphic computing) Interdisciplinary expertise in Medical Imaging (bone age assessment, retinal biomarkers) and Cybersecurity (attack detection, network analytics) Publications since 2015 demonstrate sustained innovation in AI applications , Signal Processing , and Smart City Governance . His work often integrates theoretical advances with practical implementations in real-world systems. No scientific awards or student mentorship details are explicitly documented in the provided records.

• Neuroscience
• Neurobiology
• Retina
• +۴ مورد دیگر

Karl Farrow is a Senior Lecturer at the Faculty of Sciences , KU Leuven , affiliated with the Department of Biology and the Animal Physiology and Neurobiology unit. He is also a member of the VIB-KU Leuven Center for Neuro Electronics Research Flanders (NERF) and the KU Leuven Brain Institute . Dr. Farrow's research focuses on neurobiology and visual processing , particularly the role of retinal ganglion cells and neural circuits in the superior colliculus . His work explores direction selectivity, motion perception, and adaptive mechanisms in visual systems under varying ambient conditions. His recent projects include dissecting the neural basis of threat responses in the superior colliculus, studying evolutionary influences on innate behavior circuits, and developing tools like a single-objective light sheet microscope for 3D tissue analysis. Collaborative efforts involve synaptic transmission studies in amyloid-beta precursor protein interactions.

Albert H. Titusمشاهده پروفایل

استاد

• Wearable Sensors
• Biosensors
• Bioinstrumentation
• +۵ مورد دیگر

Albert H. Titus is a Professor in the Department of Biomedical Engineering and an Adjunct Professor in the Department of Electrical Engineering at the University at Buffalo, State University of New York. He serves as Associate Vice President for Regulatory Support in the Office of the Vice President for Research and Economic Development. His research focuses on analog VLSI design for neuromorphic visual processing, biosensors, wearable devices, optoelectronic systems, and neural networks. Education: PhD in Electrical and Computer Engineering, Georgia Institute of Technology (1997) MS in Electrical Engineering, University at Buffalo (1991) BS in Electrical Engineering, University at Buffalo (1989) Research Interests: His work spans wearable and implantable sensors, bioinstrumentation, neural network-based visual processing, analog VLSI implementations, optoelectronics, and electronic packaging. He pioneered CMOS-based neuromorphic systems and developed patented technologies for glare sensing and RF power calorimetry. Publication Trends: His recent articles emphasize CMOS-integrated sensors, machine learning for bioimpedance analysis, implantable medical devices, and xerogel-based optical biosensors. These works bridge biomedical engineering and microelectronics. Scientific Recognition: He is a Fellow of the National Academy of Inventors and has received the SUNY Chancellor’s Award for Excellence in Service (2017), NSF CAREER award, and Western New York Inventor of the Year (2010). His inventions include a patented low-power glare sensor (U.S. Patent 7,586,079) featured in Popular Science’s 2011 Top Ten Inventions. Academic Leadership: As a faculty member, he has supervised nearly 20 PhD and over 40 MS students, while teaching courses in circuits, IC design, sensors, and signal processing across electrical and biomedical engineering disciplines.

• Cellular Neuroscience
• Systems Neuroscience
• Behavioral Neuroscience
• +۳ مورد دیگر

Prof. Laura Busse is a Professor at Ludwig Maximilian University of Munich (LMU), leading the Research Group in the Department of Biology II, Division Neurobiology. She holds roles as a Regular Member of MCN, Full Member of GSN, and Deputy Head of the GSN Examination Board. Her research focuses on cellular and systems neuroscience, particularly investigating how contextual information influences visual perception through neural circuits in mice. Key areas include feedback mechanisms, behavioral state effects, and thalamocortical interactions. Her work employs advanced techniques like high-density extracellular recordings and optogenetics to study active behavior in rodents. Current students include Simon Renner, Gregory Born, and others. Recent research highlights include studies on corticothalamic feedback effects, thalamic spatial integration, and the role of pupil dynamics in neural activity. She leads the Vision Circuits Lab (https://visioncircuitslab.org), exploring how sensory inputs and brain states shape visual processing. Her articles reveal trends in understanding thalamocortical communication, adaptive sensory systems, and the biological basis of neural network models. She coordinates the SPP2411 project on cortico-subcortical loops, emphasizing interdisciplinary neuroscience.

• Developmental Neurobiology
• RNA Modification
• Post-transcriptional Regulation
• +۴ مورد دیگر

Dr. Sheng-Jian Ji is a Tenured Associate Professor at the School of Life Sciences, Department of Neuroscience at Southern University of Science and Technology (SUSTech) in Shenzhen, China. He also serves as the Academic Vice President of Shude Academy and was previously the first Deputy Director of Research and Graduate Affairs in the Department of Biology at SUSTech (2016-2018). As a leading neuroscientist specializing in RNA modification and neural development, Dr. Ji has established an internationally recognized research program. Dr. Ji's educational background includes: 2003-2007: Postdoctoral Fellow, Johns Hopkins University School of Medicine, Neurobiology 1998-2003: PhD in Biochemistry and Molecular Biology, Peking University School of Life Sciences 1994-1998: Bachelor's Degree in Biochemistry, Yantai University Department of Biochemistry Dr. Ji's research primarily focuses on developmental neurobiology, with particular emphasis on post-transcriptional regulation mechanisms including RNA modification and local translation of mRNA in axons. His laboratory is recognized as one of the leading international groups studying how mRNA modification (particularly m6A and m5C) regulates neural development and function. Through innovative approaches combining molecular biology, cell biology, and microfluidic technologies, his team has revealed important insights into axon growth, dendrite maintenance, cortical neurogenesis, and retinal development. His publication record shows a clear trajectory from fundamental mechanisms of RNA modification to applications in understanding neurological disorders and aging. Recent work has expanded into aging-related neural decline, cognitive functions, and potential therapeutic targets for neurological conditions. Dr. Ji has received numerous prestigious awards: 2020, 2016: SUSTech Excellent College Mentor 2020: SUSTech Biology Department Outstanding Service Award 2019: Guangdong Province Talent Youyue Card A 2017: Guangdong Provincial Professor of Neurobiology 2013: Jiangsu Distinguished Professor (Nanjing University) 2011: National Natural Science Award Second Prize (third contributor) As an educator, Dr. Ji teaches undergraduate Neurobiology and graduate Cellular and Molecular Neurobiology courses. He actively mentors students, with recent master's graduates including Yuan Jiaxin and Zhang Pingrui. His laboratory recruits postdoctoral fellows (with salaries of 335,000+ RMB annually), research assistants, and graduate students, providing comprehensive training in molecular techniques, neuronal cell culture, microfluidics, and omics approaches. Dr. Ji leads a vibrant research team that collaborates both within SUSTech and internationally. His work continues to advance understanding of RNA modification in neural development, function, and aging, with recent progress highlighted in June 2025.

Julijana Gjorgjievaمشاهده پروفایل

استاد

• Computational Neuroscience
• Theoretical Neuroscience
• Neural Circuit Development
• +۴ مورد دیگر

Prof. Julijana Gjorgjieva is a tenured W3 Professor of Computational Neuroscience at the School of Life Sciences Weihenstephan, Technical University of Munich (TUM). She leads an independent research group at the Max Planck Institute for Brain Research and is affiliated with the Bernstein Center for Computational Neuroscience. Her research focuses on the principles governing neural circuit development, balancing learning plasticity with functional stability through computational and theoretical approaches. Key interests include synaptic organization, energy-efficient neural computation, and evolutionary optimality principles. Education & Career: B.Sc. Mathematics, Harvey Mudd College (2006) M.A.St. in Applied Mathematics, University of Cambridge (2007) Ph.D. Applied Mathematics, University of Cambridge (2011) Postdoctoral Fellowships: Harvard University (2011-2014), Brandeis University (2014-2016) Max Planck Research Group Leader (2016-2022) W2/W3 Professor at TUM since 2016 Research Interests: Computational neuroscience, theoretical modeling of neural circuits, synaptic plasticity mechanisms, homeostatic regulation, and the interplay of development and evolution in shaping brain architecture. She employs mathematical frameworks to study how circuits achieve robustness while enabling adaptive learning. Awards: Heinz Maier-Leibnitz Prize (2022) Eric Kandel Young Neuroscientist Prize (2021) ERC Starting Grant (2018) Multiple postdoctoral and early-career fellowships Grants & Funding: Includes DFG Collaborative Research Center on Neural Homeostasis, HFSP grants, and EU Horizon 2020 initiatives. Active in mentoring and promoting computational neuroscience through programs like Neuromatch Academy. Labs & Collaborations: Leads a multidisciplinary lab integrating experimental and theoretical approaches. Collaborates with institutions such as the Max Planck Society and international computational neuroscience networks.

• Human-Computer Interaction
• Tangible User Interfaces
• Playful Interactions
• +۹ مورد دیگر

Lucca Geurts is a Senior Lecturer at the Faculty of Industrial Engineering Sciences at KU Leuven, where he is affiliated with the Department of Computer Science. He serves as chairman of the Leuven Centre for Accessible Health Technology, subdivision head of Subdivision 3, Campus Group T Leuven, and Head of Education of the OC Innovative Health Technology. Additionally, he is an active member of DigiSoc – KU Leuven Institute for Digital Society. His research focuses on Technology for Tangible and Playful Interactions, particularly in healthcare applications. Dr. Geurts leads numerous research projects including therapeutic games for children with visual disorders, flexible activity measurement systems, intimate interactive systems, and early-stage glaucoma screening platforms. His work bridges human-computer interaction with accessible health technology, emphasizing user-centered design principles and practical healthcare solutions. Dr. Geurts' publication record demonstrates a consistent trajectory from fundamental interaction techniques to applied healthcare contexts. His recent work shows increasing sophistication in squeeze interactions, emotion regulation through tangible interfaces, and medical applications of interactive technology. The research trends indicate a growing focus on accessible medical diagnostics, therapeutic applications, and user experience in healthcare technology. As an educator, Dr. Geurts teaches across multiple domains including Electronics, Computer Architectures, Health Entrepreneurship, Sensors and Circuits for Healthcare Applications, and Extended Reality. His educational leadership extends to Master's theses and internships in health engineering, reflecting his commitment to training the next generation of healthcare technologists. Committee for Culture, Art and Heritage Faculty Council of Industrial Engineering Sciences Evaluation Committee of the Faculty of Industrial Engineering Sciences POC Advanced Education Faculty of Industrial Engineering Sciences Secretary of the OC Innovative Health Technology Departmental Council for Computer Science Interfaculty Council for Global Development (as substitute member) Dr. Geurts maintains an active research profile with numerous publications in top-tier human-computer interaction conferences and journals. His work shows a clear progression toward increasingly impactful healthcare applications, with strong emphasis on accessibility and user experience in medical technology development.