جستجوی استاد راهنمای دانشگاهی

Vyas Sekarمشاهده پروفایل

استاد

• Networking
• Cybersecurity
• Network Security
• +۹ مورد دیگر

Vyas Sekar is the Tan Family Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU), with a courtesy appointment in the Computer Science Department. He is affiliated with CyLab and co-directs the Future of Enterprise Security initiative. His research focuses on networking, cybersecurity, distributed systems, and IoT security, with an emphasis on data-driven approaches and network verification. Education: Ph.D. in Computer Science (2010) from CMU; B.Tech. from IIT Madras (President of India Gold Medal recipient). Professional roles include Chief Scientist at Conviva and co-founder of Rockfish Data. Research Interests: Cybersecurity, network security, software-defined networking (SDN), IoT security, DDoS defense, privacy-preserving data sharing, and network performance optimization. Recent work includes developing tools like Pigasus (FPGA-accelerated intrusion detection), Nomad (cloud side-channel mitigation), and frameworks for anomaly detection in IoT networks. Articles Trends: Recent publications address advanced threats like LLM-driven network attacks, stealthy automotive network exploits (CANDid), and optical-layer DDoS defenses. Emphasis on practical solutions (e.g., SketchPlan for telemetry, Pryde for firewall evasion detection). Awards: ACM SIGCOMM Test of Time Award (2022), IIT Madras Young Alumni Achiever Award (2022), Intel Outstanding Researcher Award (2021), and NSF CAREER Award (2016). Recognized for contributions to intrusion prevention, network security, and IoT resilience. Grants & Projects: Led NSF-funded ONSET project (optical-layer DDoS defense), CyLab's Secure IoT Initiative, and collaborations with industry partners like Intel, Facebook, and Nokia Bell Labs. Advises graduate students in cybersecurity and networking. Labs & Teams: Active contributor to CyLab, co-developer of frameworks like Lumos (hidden IoT device detection) and KalKi (IoT security platform). Engages in interdisciplinary research across CMU’s Robotics Institute and Software Engineering Institute.

Eleanor O'Rourkeمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Artificial Intelligence
• Learning Sciences
• +۳ مورد دیگر

Eleanor O'Rourke is an Associate Professor at Northwestern University with joint appointments in the Department of Computer Science and the Learning Sciences, part of the McCormick School of Engineering. She co-directs the Delta Lab, focusing on interdisciplinary research in Human-Computer Interaction, Artificial Intelligence, and Learning Sciences. Her work examines how learning environments can foster motivation and effective practices in computer science education, supported by grants from NSF and Google. Educated at the University of Washington (PhD, MS in Computer Science & Engineering) and Colby College (BS in Computer Science and Spanish), her research employs mixed methods, including design-based research and grounded theory, to study student motivation, affective responses during programming, and AI-driven interventions. Notable contributions include tools like Ply and Isopleth , which support novice web developers, and studies on student self-assessment biases and growth mindset incentives. Her work has been recognized with multiple Best Paper Awards at ACM conferences, including ICER 2024 and SIGCSE 2022. She teaches courses such as Transformative AI and the Learning Sciences and Design of Learning Environments , and advises a diverse cohort of PhD students and undergraduates. The Delta Lab’s collaborative approach emphasizes innovation in educational technology and human-centered design.

Crystal Leeمشاهده پروفایل

استادیار

• Ethical Technology
• Data Visualization
• Disability Studies
• +۴ مورد دیگر

Crytal Lee is an Assistant Professor in Computational Media and Design at MIT, with a joint appointment in the Schwarzman College of Computing and Comparative Media Studies/Writing. She is also a Faculty Associate at Harvard's Berkman Klein Center for Internet & Society, co-leading the Ethical Tech Working Group, and a Senior Fellow at Mozilla's Responsible Computing Challenge. Her research focuses on data visualization, disability studies, and ethical technology, emphasizing the 'life-cycle of data representations.' Education: PhD in History, Anthropology, Science, Technology, and Society from MIT (2022); MA and BA (High Honors) in History of Science from Stanford University (2016 and 2015). Research Interests : Crystal examines how data is curated, visualized, and contested, with a particular lens on disability justice and accessible design. Her work bridges STS, HCI, and critical data studies, addressing issues like misinformation, algorithmic bias, and inclusive technology. Awards & Grants : Honorable Mentions at EuroVis 2022 and CHI 2021; NSF Dissertation Improvement Grant; SSRC Social Data Fellowship. Advising & Mentorship : Advised projects on accessible visualization, participatory AI, and disability inclusion. Current book project: Crip Computation . Labs & Teams : Co-leads Ethical Tech Working Group at Berkman Klein; involved in MIT's Data + Feminism Lab and Accessible Interactions projects.

Somayeh Dodgeمشاهده پروفایل

دانشیار

• Spatial Data Science
• GIScience
• Movement Analysis
• +۵ مورد دیگر

Somayeh Dodge is an Associate Professor of Spatial Data Science in the Department of Geography at the University of California, Santa Barbara (UCSB). She leads the MOVE Lab and serves as Co-Associate Director of the UCSB Center for Spatial Studies and Data Science. Her research focuses on computational movement analysis, spatiotemporal data science, and the application of these tools to study human and ecological systems. She holds editorial roles in major journals including Journal of Spatial Information Science and Geographical Analysis. Education: PhD in GIScience (University of Zurich, 2011), MS in GIS Engineering (K.N.Toosi University of Technology, 2005), and BS in Geomatics Engineering (2003). Postdoctoral work at The Ohio State University and University of Zurich. Prior faculty positions include University of Minnesota (2016–2019) and University of Colorado, Colorado Springs (2013–2016). Research interests include wildfire impact analysis, mobility patterns during disasters, environmental vulnerability modeling, and geovisualization techniques. Her NSF CAREER project explores movement responses to environmental disruptions. Teaching focuses on GIScience, movement analytics, and spatial modeling courses. Awards: 2021 NSF CAREER Award and 2022 AAG Emerging Scholar Award. Active in editorial boards for multiple journals and serves on the Board of Directors for the University Consortium for Geographic Information Science (UCGIS). Advising: Supervises 7 graduate students in mobility analytics and environmental modeling. Labs/Teams: MOVE Lab (https://move.geog.ucsb.edu/) focuses on computational movement ecology and human mobility studies.

Michael Felsbergمشاهده پروفایل

استاد

• Artificial Visual Systems
• Computer Vision
• Robot Vision
• +۴ مورد دیگر

Michael Felsberg is a Professor and Head of Division at the Department of Electrical Engineering (ISY) at Linköping University, leading the Computer Vision Laboratory (CVL). His research focuses on artificial visual systems (AVS), including 3D computer vision, computational imaging, object tracking, and autonomous systems. He emphasizes HVS-inspired approaches to bridge the gap between human and machine vision capabilities. Notable achievements include over 20,000 citations (h-index 47), leadership roles in the Wallenberg AI, Autonomous Systems and Software Program (WASP), and recognition as Sweden’s top AI researcher by Vinnova. His work spans academic contributions, industry collaborations, and interdisciplinary projects like climate science applications of machine learning. Positions : WASP Executive Committee Member, WASP Area Cluster Leader for Machine Learning, and Vice-Head of Department (Electrical Engineering). Education : Extensive academic background in electrical engineering and computer vision (details not explicitly stated). Research trends in his articles reflect advancements in autonomous systems, multimodal AI, and robust vision models. His teams address challenges like object tracking, generative models for 3D simulation, and culturally diverse AI systems. Awards : Tracking Challenge Winner (OpenCV, 2015) Best Paper Awards (ICPR 2016, VISAPP 2021) Vinnova’s Highest-Ranked Swedish AI Researcher (2018) He advises numerous PhD students and oversees grants in WASP-funded initiatives. CVL collaborates on projects like disaster-response robotics and Berzelius supercomputer utilization for AI.

Deen Freelonمشاهده پروفایل

استاد

• Political Communication
• Computational Social Science
• Digital Media
• +۵ مورد دیگر

Deen Freelon is the Allan Randall Freelon Sr. Presidential Professor at the University of Pennsylvania's Annenberg School for Communication, where he leads research in digital politics and computational methods. His work centers on identity dimensions in social media, misinformation ecosystems, and political communication. Previously, he held tenured positions at American University and the University of North Carolina at Chapel Hill. Freelon earned a B.A. with honors from Stanford University (2002), followed by an M.A. (2008) and Ph.D. (2012) from the University of Washington. His endowed chair honors his great-grandfather, Allan Randall Freelon Sr., a Penn alumnus and prominent Philadelphia artist. Freelon's research explores intersections of technology and society with emphases on: Computational analysis of social media discourse Race, gender, and ideological asymmetry in online spaces Misinformation propagation and mitigation strategies Impact of personalized information environments on democracy His publications consistently address how digital platforms reshape political engagement and identity expression. Freelon has secured over $6 million in research funding from organizations including the Knight Foundation, Hewlett Foundation, Spencer Foundation, and US Institute for Peace. As a founding member of UNC Chapel Hill's Center for Information, Technology, and Public Life, he contributes to interdisciplinary efforts examining technology's societal impacts.

Vivek Srikumarمشاهده پروفایل

دانشیار

• Machine Learning
• Natural Language Processing
• Artificial Intelligence
• +۵ مورد دیگر

Vivek Srikumar is an Associate Professor in the Kahlert School of Computing at the University of Utah, co-leading the Utah NLP group and affiliated with the Utah Center for Data Science. His research focuses on Machine Learning and Natural Language Processing, particularly in structured prediction, bias mitigation, and healthcare NLP applications. He teaches Machine Learning (CS 6350/DS 4350) and has been supported by NSF, NIH, and corporate grants from Intel, Google, and others. Education: Ph.D. in Computer Science, University of Illinois at Urbana-Champaign (2013) Postdoctoral Researcher at Stanford University's NLP Group (2013-2014) Visiting Researcher at Allen Institute for Artificial Intelligence (2022 sabbatical) Research Interests: Srikumar explores text understanding, structured learning, and robust AI systems. His work addresses challenges in table-based reasoning, adversarial robustness, and ethical AI. He develops methods to ensure models use appropriate evidence and mitigate biases in representations. Grants & Collaborations: Supported by NSF, NIH, BSF, and industry partnerships with Intel, Google, Verisk, Bloomberg, and Nvidia. Notable projects include table QA systems (TempTabQA), bias mitigation (OSCaR/VERB), and crisis counseling NLP tools (ClientBot). Advising: Supervised over 30 students, including 15+ Ph.D./M.S. alumni now in academia and industry (e.g., Google, Amazon, Microsoft). Current advisees focus on multimodal reasoning, healthcare NLP, and AI ethics. Labs/Teams: Utah NLP Group and Utah Center for Data Science. Active in reproducibility efforts (LogFlux) and open-source tools (CogCompNLP/Pylon frameworks).

Steven M. LaValleمشاهده پروفایل

استاد

• Robotics
• Motion Planning
• Artificial Intelligence
• +۷ مورد دیگر

Steven M. LaValle is a Professor at the University of Oulu's Faculty of Information Technology and Electrical Engineering since 2018. Previously, he held tenured positions at the University of Illinois Urbana-Champaign (UIUC) and was a Principal Scientist at Oculus VR. His research spans robotics, motion planning (notably pioneering RRT algorithms), virtual reality, and sensor fusion. He has authored influential textbooks like Planning Algorithms and Virtual Reality . Education: PhD (1995), MS (1993), and BS (1990) in Electrical Engineering from UIUC. Research Interests: Focuses on minimal information requirements for robots, perception engineering, and foundational VR/AR systems. His work integrates control theory, computational geometry, and human perception. Achievements: Recipient of the IEEE ICRA Milestone Award (2019), University Scholar (UIUC, 2012), and XTIC Award 2024 for Innovation. Leads the Perception Engineering Group at Oulu, advancing VR/AR and telepresence technologies. Grants & Industry: ERC Advanced Grant (2021–2026), former VP of Huawei's VR/AR division, and collaborator with institutions like IIT Madras. Advises startups in robotics and virtual reality.

Igor Jurisicaمشاهده پروفایل

استاد

• Data Science and Computational Biology
• Machine Learning
• Artificial Intelligence
• +۶ مورد دیگر

Igor Jurisica is a Professor at the University of Toronto and a Senior Scientist at the Krembil Research Institute’s Data Science Discovery Centre for Chronic Diseases. He also serves as Visiting Scientist at IBM CAS, Scientific Director of the World Community Grid, and Chief Scientist at the Creative Destruction Lab (Rotman School of Management). His research focuses on integrative computational biology, data mining, and AI-driven models for cancer mechanisms, drug discovery, and chronic disease management. Key affiliations include the Osteoarthritis Research Program, Schroeder Arthritis Institute, and leadership roles in open science initiatives like the World Community Grid, a global distributed computing platform with 810,000+ volunteers. Jurisica’s work bridges computational tools (e.g., NAViGaTOR visualization platform, MirDIP databases) and clinical applications, emphasizing explainable AI in healthcare. Research interests span proteomics, microRNA regulation, systems vaccinology, and multi-omics integration for disease stratification. Notable contributions include identifying prognostic signatures in cancer and osteoarthritis, machine learning models for drug repurposing, and sportomics analyses of athletic biomarkers. He has been recognized as a Thomson Reuters Highly Cited Researcher (2014-2016) and ranked among the Top 100 AI Leaders in Oncology (2023). His labs develop open-access tools like PathDIP, OsteoDIP, and miRAnno to advance translational research.

Eetu Mäkeläمشاهده پروفایل

استاد

• Digital Humanities
• Human Sciences–Computing Interaction
• Computational Humanities
• +۳ مورد دیگر

Eetu Mäkelä is a Professor of Digital Humanities at the University of Helsinki, leading the research group at the Helsinki Centre for Digital Humanities. He focuses on computational methods in humanities and social sciences, including datafication and interdisciplinary collaboration. He serves as Technical Director of DARIAH-FI and a Research Programme Director at the Helsinki Institute for Social Sciences and Humanities. Currently, he heads the preparatory group for the Helsinki Liberal Arts and Sciences Bachelor’s Programme. His research emphasizes technological and theoretical foundations of computational research, with notable contributions to linked open data, sociolinguistic analysis, and historical text mining. He has developed widely used tools like Recon, Palladio, and Octavo, which are employed in academic and public sectors. His work has garnered over 20 awards, including best paper and open science recognitions. Key areas of expertise include digital humanities methodologies, data integration, and open science practices. He actively contributes to teaching, designing courses such as 'Methods for Digital Humanities' and demonstrating innovative pedagogical approaches. His recent projects involve analyzing 18th-century philosophical texts and sociolinguistic change using computational methods. Awards: Multiple best paper awards, open data awards, and open science awards. Grants/Advising: Leads research initiatives funded by the Academy of Finland and other bodies. Mentors interdisciplinary research teams but no specific student names listed. He maintains active roles in academic infrastructure, including the DARIAH-FI initiative and the Helsinki Institute’s datafication program. His work bridges technical innovation with humanities scholarship, emphasizing practical, enduring systems for academic and public use.

• Artificial Intelligence
• Natural Language Processing
• Multimodal Reasoning
• +۴ مورد دیگر

Graham Neubig is an Associate Professor at the Language Technologies Institute (LTI) within Carnegie Mellon University (CMU). His research focuses on advancing artificial intelligence, particularly in natural language processing (NLP), multimodal reasoning, and large language models (LLMs). He explores topics such as AI safety, generative AI, and human-AI interaction, with an emphasis on practical applications like machine translation and web-agent systems. His work often involves developing frameworks for evaluating AI systems, such as OpenAgentSafety and BehaviorBox, which assess real-world agent performance and model behavior. Neubig's research also delves into improving LLM capabilities through reasoning analysis, hallucination detection (e.g., ZINA), and culturally aware systems (e.g., CAIRe). He has contributed to open-source projects like Pangea (a multilingual LLM) and frameworks such as Cmulab for model deployment. His recent work addresses challenges in agentic tasks, self-improving agents (Skillweaver), and benchmarking across domains like visual reasoning (VisualPuzzles) and software engineering. Notable achievements include advancing evaluation methodologies for LLMs, developing tools for ethical AI, and creating benchmark suites that test systems under realistic conditions. His lab collaborates on projects like the BrowserGym ecosystem and OpenHands platform, which aim to standardize web-agent research and AI-driven software development. Neubig's contributions span theoretical advancements and practical implementations, bridging the gap between cutting-edge research and real-world applications. He advises students such as Apurva Gandhi and actively publishes in top venues, addressing topics from instruction-following improvements to the societal impacts of AI. His work frequently emphasizes the importance of transparency, controllability, and cultural awareness in AI systems.

Joshua Newمشاهده پروفایل

استاد پژوهش

• Building Energy Modeling
• Climate Change Science
• Supercomputing
• +۵ مورد دیگر

Dr. Joshua New is a Distinguished R&D Staff Member at Oak Ridge National Laboratory (ORNL) and holds a Joint Faculty Position at The University of Tennessee since 2012. He leads research in building energy modeling, climate change science, and supercomputing. His work focuses on urban-scale energy systems, AI-driven analytics, and high-performance computing applications. Education: Ph.D. in Computer Science (University of Tennessee, 2009), M.S. in Computer Systems, B.S. in Computer Science and Mathematics (Jacksonville State University). His research interests include optimizing building energy efficiency, simulating climate impacts on urban infrastructure, and developing tools like AutoBEM and ModelAmerica to model 122.9 million U.S. buildings. He has over 150 peer-reviewed publications and led 45+ projects involving supercomputing, visual analytics, and AI for big data. Awards include the R&D 100 Award (2016), ASHRAE Distinguished Service Award (2018), and Lab-Corps (2015). His teams prioritize utility use cases and validate models against real-world data. He is a Senior IEEE member, Certified Energy Manager (CEM), and holds certifications in project management and energy efficiency. Key contributions include the Roof Savings Calculator Suite, AutoGen/AutoSim tools, and the ModelAmerica initiative. His work addresses national energy policy, heatwave resilience, and sustainable city design through interdisciplinary collaborations.

Karen Cochraneمشاهده پروفایل

استادیار

• Human-Computer Interaction (HCI)
• Mental Health Technologies
• Accessibility
• +۶ مورد دیگر

Dr. Karen Cochrane is an Assistant Professor at the University of Waterloo, specializing in Human-Computer Interaction (HCI) with a focus on wearable and tangible computing for mental health and accessibility. Her research integrates soma design, autoethnography, and design fiction to address the needs of underrepresented communities, particularly those with disabilities. Key projects include developing assistive technologies for queer/crip identities, accessible gaming wearables, and tactile interfaces for sensory exploration. She explores embodied experiences through multidisciplinary approaches, blending traditional craft practices with modern computational tools. Her work prioritizes participatory design methodologies, collaborating with occupational therapists, disabled communities, and neurodivergent individuals to co-create inclusive technologies. Recent innovations include VARitouch (a haptic feedback device), Breathing Scarf (for emotional regulation), and adaptive switches for children with motor disabilities. Her research extends into sensory narratives, exploring how fabric and data can articulate bodily experiences through projects like Sensory Data Dialogues and Queer/Crip Body Mapping. While no formal grants or awards are listed, her publications reflect a strong focus on ethical technology, accessibility, and embodied interaction. Current projects emphasize the intersection of wearable tech with identity expression, mindfulness practices, and neuromotor rehabilitation. She actively designs prototypes that bridge clinical needs with creative technology solutions, though specific lab affiliations or team collaborations are not detailed in available texts.

David Lindlbauerمشاهده پروفایل

استادیار

• Mixed Reality
• Computational Interaction
• Extended Reality (XR)
• +۵ مورد دیگر

David Lindlbauer is an Assistant Professor at Carnegie Mellon University's Human-Computer Interaction Institute (HCII), where he leads the Augmented Perception Lab and co-directs the CMU Extended Reality Technology Center. His research focuses on advancing Mixed Reality (MR) and Extended Reality (XR) interfaces through computational interaction methods that optimize spatial, temporal, and multimodal feedback.

David Hsuمشاهده پروفایل

استاد

• Robotics
• Artificial Intelligence
• Machine Learning
• +۲ مورد دیگر

David Hsu is Provost's Chair Professor in the Department of Computer Science at the National University of Singapore (NUS) School of Computing, where he founded and directs the NUS Artificial Intelligence Laboratory (NUSAIL) and leads the Smart Systems Institute. His academic leadership includes chairing major conferences such as Robotics: Science & Systems (2015) and IEEE ICRA (2016), alongside editorial roles in IEEE Transactions on Robotics and the Journal of Artificial Intelligence Research. He earned a B.Sc. in Computer Science & Mathematics from the University of British Columbia and a Ph.D. in Computer Science from Stanford University. His research spans robotics, AI, and computational biology, with recent focus on robot planning under uncertainty and human-robot collaboration. Current work integrates machine learning with decision-theoretic planning to enable robust human-robot co-existence in unstructured environments. Analysis of his 2023-2025 publications reveals dominant trends in deformable object manipulation (e.g., clothes handling via semantic keypoints), open-world navigation using scene graphs, and LLM-driven multi-agent reasoning for complex tasks. Key innovations include perspective-aware visual grounding for human-centric interaction and functional object arrangement through compositional generative models, reflecting a strong emphasis on real-world applicability. His scientific contributions have earned prestigious recognition: IJCAI-JAIR Best Paper Prize (2022) for foundational AI research Robotics: Science & Systems Test of Time Award (2021) IEEE Fellowship (2018) for contributions to robotic planning RSS Best Systems Paper Award (2017) RoboCup Best Paper Award at IROS (2015) Humanitarian Robotics Award at ICRA (2015) As director of the Adaptive Computing Laboratory, Hsu drives research on fundamental computational frameworks for human-robot interaction. The lab's work on uncertainty-aware decision-making has secured significant research funding through grants from Singapore's National Research Foundation and industry partnerships with robotics firms. While specific student names aren't publicized, his leadership in the NUSAIL indicates extensive mentorship of doctoral candidates in AI and robotics.