جستجوی استاد راهنمای دانشگاهی

Julian Shunمشاهده پروفایل

دانشیار

• Parallel Computing
• High-Performance Computing
• Graph Analytics
• +۷ مورد دیگر

Julian Shun is an Associate Professor at the Massachusetts Institute of Technology (MIT) in the Department of Electrical Engineering and Computer Science (EECS) and a principal investigator in the Computer Science and Artificial Intelligence Laboratory (CSAIL). Previously, he was a Miller Research Fellow at UC Berkeley and earned his Ph.D. from Carnegie Mellon University under Guy Blelloch. His research focuses on parallel and high-performance computing, with emphasis on graph analytics, spatial/graph clustering, and dynamic algorithms. He designs algorithms with theoretical guarantees and empirical efficiency, along with high-level programming frameworks to simplify parallel code development. His work spans cache-oblivious, external-memory, and streaming graph algorithms, addressing scalability and performance across diverse computational architectures. Julien's recent publications highlight advancements in parallel graph traversal, dynamic connectivity, and approximation algorithms for centrality metrics. His research also explores domain-specific languages like GraphIt for graph analytics and frameworks such as Julienne for work-efficient bucketing. Scientific Awards: Miller Research Fellow at UC Berkeley He has taught graduate-level courses at MIT, including 6.506 (Algorithm Engineering) and 6.886 (Graph Analytics), emphasizing theoretical foundations, experimental analysis, and open-ended research projects.

Leah Macfadyenمشاهده پروفایل

دانشگاهی

• Critical Intercultural Studies
• Digital Literacies
• Digital Research Methods
• +۶ مورد دیگر

Leah Macfadyen is an Associate Professor of Teaching in the Department of Language & Literacy Education at the University of British Columbia (UBC), Faculty of Education. She serves as Coordinator for Curriculum & Instruction in the Master of Educational Technology (MET) program. With interdisciplinary training in experimental sciences and humanities, she bridges analytical rigor with cultural theory in her research on digital education and learning analytics. Her research spans learning analytics , digital literacies , and critical intercultural communication . Key projects include developing UBC’s Introduction to Global Citizenship online course (2005) and co-authoring MET program courses like ETEC 542. She explores ethical dimensions of ‘big data’ in education and data literacy challenges. Recent publications (2020–2023) focus on institutional learning analytics frameworks, curriculum NLP analysis, and ethical codes for practitioners. Collaborative work with Shane Dawson and others has been published in journals like Journal of Learning Analytics , Computers & Education , and Journal of Genetic Counselling . Key Themes : Intercultural communication in digital spaces, systems thinking for educational analytics, ethical implications of data-driven learning Courses Developed : ETEC 500, 520, 542, 543, 581, and 590

Kenneth Zickمشاهده پروفایل

استاد پژوهش

• Unconventional computing
• Bio-inspired compute systems
• Ising machines
• +۷ مورد دیگر

Dr. Kenneth Zick is a Research Professor at the University of Southern California's Information Sciences Institute (USC ISI), where he serves as Research Director of Transformational Computing. His work focuses on game-changing computer architectures, hardware, and systems for solving critical government problems, with expertise in unconventional computing, quantum computing, and bio-inspired systems. Ph.D. in Computer Science & Engineering, University of Michigan-Ann Arbor M.S. in Electrical Engineering, University of Texas at Dallas Bachelor's in Electrical Engineering, University of Michigan-Ann Arbor Dr. Zick's research interests span unconventional computing , bio-inspired systems , Ising machines , quantum annealing , FPGA-based solutions , and neuromorphic computing . His group develops hardware-centric algorithm discovery and Cosm, a heuristic algorithm for sparse Ising optimization. Current projects include superconducting digital architectures, analog-digital hybrid computing, and human-AI co-design for breakthrough hardware. His team leverages advanced facilities such as USC ISI's MOSIS 2.0 and the California DREAMS hub in the DoD Microelectronics Commons, with expertise in high-speed I/O, FPGA prototyping, and radiation-hardened systems. He has received a NASA Fellowship for his Ph.D. work and mentored students like Aditi, who won the USC ECE Outstanding Academic Achievement Award.

• Membrane Science
• Separation Processes
• Carbon Dioxide Capture
• +۵ مورد دیگر

Dr. W.S. Winston Ho is a Distinguished Professor of Engineering at The Ohio State University, holding joint appointments in the William G. Lowrie Department of Chemical and Biomolecular Engineering and the Department of Materials Science and Engineering. With over 50 years of combined industrial and academic experience, he leads pioneering research in molecular separation technologies. His industrial tenure includes R&D leadership at Exxon, Xerox, and Commodore Separation Technologies, where he commercialized gas treating processes and membrane systems. Education: Ph.D. in Chemical Engineering, University of Illinois at Urbana-Champaign (1971) M.S. in Chemical Engineering, University of Illinois at Urbana-Champaign (1969) B.S. in Chemical Engineering, National Taiwan University (1966) His research focuses on advanced membrane systems for critical environmental and energy challenges, including: CO 2 -selective membranes for hydrogen purification and carbon capture High-flux desalination membranes with fouling resistance Proton-exchange membranes for fuel cells operating under low humidity Supported liquid membranes for pharmaceutical recovery and heavy metal removal Recent publications demonstrate a strong emphasis on scaling membrane technologies for industrial applications, particularly carbon capture from flue gas and hydrogen purification. Over 75% of his last 15 articles address CO 2 separation, membrane scalability, or material enhancements for energy systems. Major Scientific Awards: Elected to National Academy of Engineering (2002) and Academia Sinica (2014) AIChE Institute Award (2006), Gerhold Award (2007), Evans Award (2012) New Jersey Inventor of the Year (1991) with 60+ U.S. patents Global recognition including Chemcon Distinguished Speaker Awards He directs the Winston Ho Research Group, focusing on membrane process scale-up and holds advisory roles in national research panels. Current projects include field testing spiral-wound membrane modules for carbon capture and developing fluoride-containing membranes to enhance solid oxide fuel cell efficiency. His work has been funded by DOE, NSF, and industrial partners, resulting in commercial implementations of membrane technologies.

Christopher John Rozellمشاهده پروفایل

استاد

• Computational Neuroengineering
• Artificial Intelligence
• Neuroscience
• +۷ مورد دیگر

Christopher John Rozell is the Julian T. Hightower Chaired Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology's College of Engineering. He serves as Executive Director of the Institute for Neuroscience, Neurotechnology & Society (INNS) and directs the Sensory Information Processing Lab (SIPLab). His research bridges computational neuroscience, machine learning, and neurotechnology, with clinical applications in treatment-resistant depression and neuromodulation therapies. Education: B.S.E. in Computer Engineering & B.F.A. in Music, University of Michigan (2000) M.S. and Ph.D. in Electrical Engineering, Rice University (2002, 2007) Postdoctoral Scholar, Redwood Center for Theoretical Neuroscience, UC Berkeley Research Focus: Dr. Rozell's interdisciplinary work spans computational neuroengineering, theoretical neuroscience, and artificial intelligence. He develops data analysis tools inspired by neural processing and creates therapeutic neurotechnologies. Key areas include: computational psychiatry (developing DBS therapies for depression), neural dynamics modeling, brain-computer interfaces, and societal impacts of neurotechnology. His lab focuses on high-dimensional data analysis, neural coding principles, and scalable neuromodulation approaches. Publication Trends (2023-2025): Recent works concentrate on deep brain stimulation mechanisms for depression, computational modeling of neural/autonomic dynamics, and machine learning applications in neuroscience. Dominant themes include biomarker discovery for treatment response, neural interoception modulation, probabilistic modeling of latent states, and brain-computer interface taxonomy. Clinical translation of neurotechnology is a consistent focus across publications. Awards & Honors: Elected AIMBE Fellow (2025) NIH BRAIN Initiative Photo/Video Award (2024) Congressional Panelist for BRAIN Initiative 10th Anniversary (2024) Sigma Xi Best Faculty Paper (2024) Neuro Open Science International Prize (2022) W. Howard Ector Outstanding Teacher Award (2019) McDonnell Foundation 21st Century Science Award (2014) NSF CAREER Award (2014) Leadership & Training: Dr. Rozell co-founded Neuromatch, Inc. to build global computational neuroscience communities. He advises Motif Neurotech and the Institute of Neuroethics. His mentees have received prestigious fellowships (Schmidt, Fulbright, NIH K99/R00) and hold leadership positions across academia and industry. Research is supported by NIH BRAIN Initiative, NSF, and private foundations. Labs & Initiatives: Directs the Sensory Information Processing Lab (theoretical neuroscience/neuroengineering) and the Institute for Neuroscience, Neurotechnology & Society (addressing ethical/societal implications). Neuromatch promotes open, accessible computational neuroscience training globally.

Katy Ilonka Geroمشاهده پروفایل

مدرس

• Human-Computer Interaction
• Creativity
• Writing Assistants
• +۶ مورد دیگر

Katy Ilonka Gero is a Lecturer at the University of Sydney's School of Computer Science, with a PhD in Computer Science from Columbia University (2022). She holds a BSc in Mechanical Engineering from MIT, where she received the Carl G. Sontheimer Prize for Excellence in Innovation and Creativity. Education : BSc (MIT), PhD (Columbia) Her research focuses on Human-Computer Interaction , Creative Writing , and AI Ethics , particularly examining how language models impact writing processes, ownership, and agency. She advocates for community-driven language models trained on consensual data and explores technical innovations for personalized AI tools. Recent publications span language model ethics (Nature Machine Intelligence 2023), generative AI (CHI 2025 Best Paper), and creative collaboration (CHI 2023). Key trends include user-centered AI design , creative ownership , and data ethics . Scientific Awards : NSF Graduate Research Fellowship, Brown Institute for Media Innovation, Amazon Research Award, CHI Best Paper (2025), CHI Honorable Mention (2024) As co-founder of Ensemble Park and former taper editor, she bridges computational poetry and traditional literary practices. Her work at startups Rest Devices and Soofa demonstrates technical innovation in consumer and urban tech.

Matthew Turkمشاهده پروفایل

استادیار

• Data Science
• Computational Astrophysics
• Information Visualization
• +۳ مورد دیگر

Matthew Turk is an Assistant Professor at the University of Illinois' School of Information Sciences and holds a Research Assistant Professor appointment in the Department of Astronomy. His work bridges computational astrophysics and data science, focusing on data analysis tools, human-computer interaction, and the social structures of scientific software communities. PhD in Physics from Stanford University (2009) Postdoctoral work at University of California, San Diego NSF Fellowship in Transformative Computational Science at Columbia University Turk's research centers on data visualization , reproducibility in scientific workflows , and computational infrastructure for astrophysics . He has developed tools like yt, a widely-used astrophysical simulation analysis toolkit, and explores how researchers interact with data through software and visualization techniques. His recent publications highlight trends in scientific software sustainability , machine learning applications in cosmology , and interdisciplinary data sonification . Turk's work demonstrates a consistent focus on integrating computational methods with human-centric approaches to scientific discovery. NSF Fellowship in Transformative Computational Science Turk contributes to scientific education through courses like Data Visualization (IS445ACG) and Independent Study (IS589MJT). His involvement in grants and collaborative projects, including the yt toolkit development and the Data Storytelling Toolkit for Libraries (DSTL), showcases his commitment to expanding computational literacy across domains.

Carolyn Conner Seepersadمشاهده پروفایل

استاد

• Design for Additive Manufacturing
• Engineering Design
• Additive Manufacturing
• +۴ مورد دیگر

Carolyn Conner Seepersad serves as the J. Mike Walker Professor of Mechanical Engineering at the University of Texas at Austin and directs the Center for Additive Manufacturing and Design Innovation. She holds membership in the U.T. System Academy of Distinguished Teachers and maintains active leadership in the additive manufacturing community through roles such as co-organizer of the Solid Freeform Fabrication Symposium and ASME Design Engineering Division Executive Committee membership. Her academic credentials include: PhD in Mechanical Engineering from Georgia Tech (2004) MA/BA in Philosophy, Politics and Economics from Oxford University (1998, Rhodes Scholar) BS in Mechanical Engineering from West Virginia University (1996) Dr. Seepersad's research centers on computational design methodologies and additive manufacturing innovation , with particular expertise in simulation-based design of complex systems, environmentally conscious product development, and materials engineering. Her work bridges theoretical design frameworks with practical manufacturing applications, emphasizing sustainability and performance optimization across aerospace, automotive, and energy systems. Current projects explore reactive extrusion additive manufacturing, negative stiffness materials, and machine learning integration for process-aware design. Analysis of her 15 most recent publications reveals a dominant focus on process innovation in additive manufacturing (70%), particularly stereolithography and selective laser sintering, with growing emphasis on data-driven design approaches (20%) and sustainable engineering applications (10%). Her work demonstrates consistent progression from fundamental material design toward integrated system optimization and industrial scalability. Her scientific recognition includes: International Outstanding Young Researcher Award in Freeform and Additive Manufacturing (2009) UT System Regents’ Teaching Award (2010) ASME Design Automation Committee Outstanding Young Investigator Award (2010) ASEE Outstanding New Mechanical Engineering Educator Award (2013) Multiple ASME and ASEE best paper awards U.T. System Academy of Distinguished Teachers membership Dr. Seepersad maintains an extensive advising portfolio with 48 graduate students (16 PhD, 24 MS, and 8 current) plus 2 postdoctoral researchers, reflecting sustained research productivity and educational impact. Her Product, Process, and Materials Design Lab fosters interdisciplinary collaboration between mechanical engineering, materials science, and computational design teams.

Rasmus Paghمشاهده پروفایل

استاد

• Algorithms
• Data Structures
• Big Data
• +۷ مورد دیگر

Rasmus Pagh is a Professor at the Department of Computer Science, University of Copenhagen, specializing in algorithms and complexity. His career includes a 2002 PhD from Aarhus University under Peter Bro Miltersen and a tenure at IT University of Copenhagen until 2020. He leads theoretical research with practical applications in big data, databases, and modern computer architecture parallelism. His research interests span algorithms, data structures, and privacy-preserving computing. Recent work includes the ERC-funded project on Scalable Similarity Search and contributions to the BARC center for basic algorithms research. He has collaborated with Google Research (2019-2020) and focuses on theoretical foundations with real-world impact. Key research trends in his 2023-2024 publications include privacy-preserving data analysis probabilistic data structures distributed secure computation noise-robust coding hashing efficiency continual privacy mechanisms Scientific recognition includes 2024 ACM Fellowship ERC grant leadership multiple top-tier conference publications

Bei Jiangمشاهده پروفایل

دانشیار

• Biostatistics
• Functional Data Analysis
• Statistical Machine Learning
• +۶ مورد دیگر

Dr. Bei Jiang is an Associate Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta , Canada. She holds the Canada CIFAR AI Chair and is affiliated with the Alberta Machine Intelligence Institute (Amii) . Her academic journey includes a PhD in Biostatistics (2014) from the University of Michigan, MS (2008) and BS (2004) from the University of Alberta and Beijing University of Technology, respectively. Current Positions : 2021–Present (Associate Professor), 2022–Present (CIFAR AI Chair) Past Appointments : Assistant Professor (2015–2021), Postdoctoral Fellow at Columbia University (2014–2015), Research Assistant at University of Michigan (2009–2013) Research Interests : Dr. Jiang specializes in methods for joint modeling of longitudinal and health outcome data , Bayesian hierarchical modeling , functional and imaging data analysis , and statistical machine learning . Her work integrates kernel machine regression , differential privacy , and synthetic data generation to address challenges in heterogeneous health data and neuroimaging. Scientific Awards : Highlights include the 2015 SAMSI New Research Fellow , multiple Rackham Conference Travel Awards (2013, 2012), and prestigious NSERC scholarships (2009–2012). She has also received the J Gordin Kaplan Graduate Award (2008) and Statistical Society of Canada Travel Award (2008). Grants : $375,000 (CIFAR AI Chairs, 2022–2027), $480,000 (MITACS Accelerate, 2022–2025), and $210,000 (Canadian Statistical Sciences Institute, 2022–2025) Students and Postdocs : She mentors numerous PhD , MSc , and Postdoctoral Fellows , including Junxi Zhang (2023–Present), Enze Shi (2022–Present), and former advisees like Wenxing Guo (now Lecturer at University of Essex) and Yafei Wang (Assistant Professor at University of Alberta).

Le-Nam Tranمشاهده پروفایل

پژوهشگر

• Wireless Communications
• 5G/6G Network Optimization
• Signal Processing
• +۴ مورد دیگر

Dr. Le-Nam Tran is a researcher at the UCD School of Electrical & Electronic Engineering , University College Dublin. His work focuses on optimizing the last hop of 5G/6G wireless networks through mathematical programming, with emphasis on energy efficiency, interference management, and security against eavesdropping. Develops low-cost, low-complexity transmission techniques Projects supported by Science Foundation Ireland Career Development Award Author of over 80 peer-reviewed publications Research Keywords: Wireless Communications Network Security Signal Processing Energy-Efficient Systems Beamforming Optimization Interference Mitigation

Chenhao Maمشاهده پروفایل

استادیار

• Graph Computing
• Data Mining
• Database Systems
• +۳ مورد دیگر

Dr. Chenhao Ma is an Assistant Professor at the School of Data Science , The Chinese University of Hong Kong, Shenzhen , where he works on large-scale data management and data mining. Previously, he was a Postdoctoral Fellow at the University of Hong Kong (2021–2022) and earned his PhD in Computer Science from the University of Hong Kong (2021) and B.Eng. from Shandong University (2017). Current research focuses on graph computing (dense subgraph discovery, motif analysis, graph learning), AI+DB (Text-to-SQL, vector search), and traffic data mining (trajectory analysis, outlier detection). He has published over 40 papers in top venues including SIGMOD, PVLDB, KDD and received the ACM SIGMOD Research Highlight Award 2021 and Best of SIGMOD 2020 (4/458). Scientific Awards : ACM SIGMOD Research Highlight Award 2021 Best of SIGMOD 2020 (4/458) Presidential Young Fellow at CUHK-Shenzhen (2023) Hong Kong and China Gas Scholarship (2019-2020) Reaching Out Award (2019) HKU Postgraduate Scholarship (2017-2021) ACM-ICPC Gold Medal (2015) National Scholarship (2014, 2015) Advising and Research Team : He leads a team including Postdoc Dr. Yuanyuan Zeng, PhD students Lujie Ban, Yuwei Xu, and MPhil students Yi Yang, Yuyang Liang. Former mentees like Yichen Xu (PhD at Berkeley) and Jiayang Pang (Master at UC San Diego) have achieved academic placements. Professional Service : He has served as PC member/reviewer for VLDB, KDD, ICDE, WWW, NeurIPS, TKDE , and guest editor for Applied Sciences and Frontiers in Big Data . He chairs sessions at ICDE and VLDB.

• Lattice-Based Cryptography
• Post-Quantum Cryptography
• Cryptographic Protocols
• +۵ مورد دیگر

Ron Steinfeld is an Associate Professor at the Cybersecurity Lab of the Faculty of Information Technology , Monash University . His research focuses on lattice-based cryptography , post-quantum cryptographic protocols , and privacy-preserving technologies . He has contributed to advancements in secure multiparty computation , digital signatures , and blockchain confidentiality . Key areas: Lattice-Based Cryptography, Zero-Knowledge Proofs, Blockchain Security Recent work trends: Quantum-safe protocols, Efficient sampling algorithms, Scalable blockchain solutions Scientific Awards : BEST PAPER AWARD (ASIACRYPT 2015) He has served on program committees for major conferences including CRYPTO , EUROCRYPT , and ASIACRYPT . Ron is a member of the Discrete Mathematics Research Group and has collaborated with institutions like Macquarie University in the past.

• Food Engineering
• Thermal Engineering
• Biophysics
• +۳ مورد دیگر

Thijs Defraeye is a Senior Scientist at Empa (Swiss Federal Laboratories for Materials Science and Technology) and Adjunct Professor at Dalhousie University. He holds a PhD in Building Physics from KU Leuven (2011) and a Master's in Civil Engineering (2006). His work focuses on optimizing food supply chains through multiphysics simulations and digital twins, addressing challenges in refrigerated transport, postharvest quality preservation, and energy-efficient food processing. He leads the SimBioSys group, developing solutions for perishable goods logistics and electrohydrodynamic technologies. Research interests include: Biophysics of food systems Digital twin applications in agriculture Electrohydrodynamic drying Thermal management in cold chains Sustainable food technologies Recent work emphasizes reducing food loss through physics-based modeling of refrigerated containers, ventilated packaging optimization, and scalable evaporative cooling systems. His studies bridge engineering principles with biological processes, aiming to enhance global food security and environmental sustainability.

Prineha Narangمشاهده پروفایل

استاد

• Quantum Materials
• Quantum Information Science
• Non-Equilibrium Dynamics
• +۷ مورد دیگر

Dr. Prineha Narang is a Professor of Physical Sciences and Electrical and Computer Engineering at the University of California, Los Angeles (UCLA). Previously, she held positions as an Assistant Professor at Harvard University and a Research Scholar at MIT. Her research focuses on quantum materials, quantum information science, and non-equilibrium dynamics, with interdisciplinary contributions to photonics, topological materials, and cavity quantum electrodynamics (QED). She leads the Narang Lab, which develops theoretical and computational methods to design quantum systems and explores applications in quantum networks and energy conversion. Dr. Narang has held leadership roles in major initiatives such as the DOE Quantum Science Center and the NSF Center for Quantum Networks. She is also the founder and CTO of Aliro Quantum, a company advancing quantum networking technologies. Education: M.S. and Ph.D. in Applied Physics from the California Institute of Technology (Caltech). Her work has been recognized with prestigious awards, including the Mildred Dresselhaus Prize, NSF CAREER Award, and being named a Moore Inventor Fellow. She serves on editorial boards for journals like ACS Nano and Applied Physics Letters , and chairs international conferences. Outside academia, she advises organizations like arXiv and actively engages in promoting quantum technologies through industry collaborations. Research Interests: Quantum materials engineering, quantum networks, non-equilibrium phenomena, topological quantum states, and quantum defect physics. Current projects include designing scalable quantum repeaters, developing error-corrected quantum systems, and studying light-matter interactions in novel materials. Her lab’s SpaRTaNS code enables spatially-resolved transport simulations, advancing understanding of electron and phonon dynamics. Awards and Grants: Over 20 major awards, including the Guggenheim Fellowship (2023), ONR Young Investigator Award (2022), and leadership roles in DOE and NSF-funded centers. Her work bridges academia and industry, with partnerships at companies like Applied Materials and Northrop Grumman.