جست‌وجوی استاد و پژوهشگر

Ranjay Krishnaمشاهده پروفایل

استادیار

• Computer Vision
• Natural Language Processing
• Robotics
• +۳ مورد دیگر

Ranjay Krishna is an Assistant Professor at the Paul G. Allen School of Computer Science & Engineering at the University of Washington, where he co-directs the RAIVN lab and leads the computer vision team at the Allen Institute for AI (Ai2). His research intersects computer vision , natural language processing , robotics , and human-computer interaction . PhD in Computer Science from Stanford University (2021) Bachelor's and Master's degrees from Stanford and Cornell His work has received best paper , outstanding paper , and orals at top conferences like CVPR, ACL, CSCW, NeurIPS, UIST, and ECCV. Media outlets including Science , Forbes , and PBS NOVA have covered his research. He has been supported by grants from Google , Apple , NFS , and others. Ranjay advises a diverse group of 15 PhD and postdoctoral researchers , including Jieyu Zhang, Benlin Liu, and Cheng-Yu Hsieh. His teams have developed benchmarks like MemoryBench and The Colosseum , and his PathFinder framework achieved 74% accuracy in skin melanoma diagnosis—surpassing human experts by 9%. Notable contributions include: Perception Tokens for visual reasoning in MLMs SAM2Act for robotic manipulation with memory Synthetic Visual Genome dataset with 5.6M relationships

Howie Chosetمشاهده پروفایل

استاد

• Robotics
• Medical Robotics
• Snake Robots
• +۱۱ مورد دیگر

Howie Choset is a Professor of Robotics at the Robotics Institute, Carnegie Mellon University. He directs the Undergraduate Robotics Minor and leads the Biorobotics Laboratory, where his research focuses on snake robots, motion planning, and medical robotics. He is also affiliated with the Manufacturing Futures Institute. Ph.D., Mechanical Engineering, California Institute of Technology (1996) M.S., Mechanical Engineering, California Institute of Technology (1995) B.S.E., Computer Science and Engineering, University of Pennsylvania (1990) B.S., Economics, The Wharton School of Business (1990) Choset's research centers on robotics for confined and complex environments, particularly through the development of snake robots. His work integrates mechanism design, path and motion planning, and estimation to enable applications in surgery, manufacturing, infrastructure inspection, and search and rescue. He is a pioneer in medical robotics and has co-founded Medrobotics to commercialize minimally invasive surgical robots. His recent publications highlight a strong focus on ergodic exploration, multi-agent systems, motion planning under uncertainty, and medical robotics. Themes include optimizing robot trajectories for information gathering, solving complex path planning problems with dynamic obstacles, and advancing autonomous systems for disaster response and space exploration (e.g., the EELS robot for Enceladus). MIT Technology Review Top 100 Innovators under 35 (2002) Best Paper Award, RIA (1999) Best Paper Award, ICRA (2003) Best Paper, IEEE Bio Rob (2006) Best Video, ICRA (2011) Nominations for best papers at ICRA, IROS, and CLAWAR Choset has advised numerous students, many of whom have won top awards. His lab has received significant funding for robotics research, including projects in surgical robotics, additive manufacturing, and autonomous exploration. He is the lead author of the textbook Principles of Robot Motion and is actively involved in educational innovation through custom robotics labs. He leads the Biorobotics Laboratory at CMU, which develops advanced robotic systems like snake robots and the EELS (Exobiology Extant Life Surveyor) robot for NASA missions. The lab collaborates with industry and government agencies on applications ranging from surgery to space exploration.

• Reconfigurable Computing
• Field-Programmable Gate Arrays (FPGA)
• High-Level Synthesis
• +۳ مورد دیگر

Paolo Ienne is a Professor at the Swiss Federal Institute of Technology in Lausanne (EPFL), where he leads the Processor Architecture Laboratory (LAP) within the School of Computer and Communication Sciences. His research focuses on advancing reconfigurable computing systems through innovative FPGA architectures and high-level synthesis methodologies. His primary research domains include reconfigurable computing, FPGA architecture design, dynamically scheduled dataflow circuits, and hardware acceleration techniques. Recent work emphasizes memory system optimization for FPGAs, formal verification of circuit transformations, and rapid C-to-hardware compilation flows. He has pioneered approaches for handling thousands of outstanding memory misses in FPGA accelerators and developed novel techniques for switch-block exploration without explicit pattern enumeration. Analysis of his 2023-2025 publications reveals a strong trend toward practical FPGA deployment challenges, with increasing focus on HBM integration, virtual memory systems for PCIe-attached devices, and formally verified circuit transformations. His work consistently targets real-world bottlenecks in high-level synthesis toolchains while maintaining theoretical rigor in dataflow architecture design. Professor Ienne's laboratory receives support from the Swiss National Science Foundation and industry partners including Huawei, enabling cutting-edge research in FPGA-based acceleration. His collaborative network spans major semiconductor companies and academic institutions worldwide, with frequent co-authorship on conference proceedings and journal publications in IEEE and ACM venues.

• Machine Learning
• Artificial Intelligence
• Data Science
• +۶ مورد دیگر

Chris J. Maddison is an Assistant Professor at the University of Toronto, holding joint appointments in the Department of Computer Science and the Department of Statistical Sciences. He is also a CIFAR AI Chair at the Vector Institute and a member of the ELLIS Society. Maddison earned his DPhil from the University of Oxford and previously worked as a Senior Research Scientist at Google DeepMind and a member at the Institute for Advanced Study. His research focuses on advancing machine learning methodologies, particularly in leveraging data’s natural structure for efficient learning, with applications in drug discovery, causal inference, and AI safety. Education: DPhil in Computer Science, University of Oxford His research interests span machine learning, AI safety, reinforcement learning, and the integration of logical reasoning into large language models. Maddison has contributed to foundational work on gradient estimation techniques and was a key member of the AlphaGo project. He actively explores how statistical structures in real-world data influence AI capabilities. Recent publications emphasize evaluating conversational agents, mitigating AI safety risks, and enhancing logical reasoning in LLMs. His work bridges theoretical advancements with practical applications, such as code generation and multi-agent systems. Awards: NeurIPS Best Paper Award (2014), Open Philanthropy AI Fellowship Maddison advises multiple PhD students and postdoctoral researchers, fostering collaborations across academia and industry. His former advisees now hold roles at institutions like OpenAI, Stanford, and Magic AI. He teaches advanced courses in machine learning and statistical methods, including CSC 2541 (Large Models) and STA 314 (Machine Learning). Maddison is affiliated with the Schwartz Reisman Institute for Technology and Society, extending his impact to societal implications of AI. His lab’s interdisciplinary approach combines algorithmic innovation with real-world problem-solving.

Yang Liuمشاهده پروفایل

دانشیار

• Smart Manufacturing
• Smart Energy Systems
• Clean Energy Transition
• +۵ مورد دیگر

Yang Liu is a tenured Associate Professor at the Department of Management and Engineering , Linköping University, Sweden, and an Adjunct Professor at the University of Oulu, Finland. His expertise spans smart manufacturing, clean energy transition, and Industry 4.0 applications. He holds an M.Sc. and D.Sc. from the University of Vaasa, Finland. Research & Awards: Liu's work focuses on sustainable systems, decision support systems, and AI-driven energy efficiency. He has authored over 140 Web of Science publications, including top 0.1% ESI Hot Papers. He is ranked among the world's top 2% scientists (Stanford-Elsevier) and leads globally in 'big data analytics in manufacturing' and 'Industry 4.0-driven circular economy' research. Leadership & Projects: He leads projects like FlexSUS (EU Horizon 2020) and PERSEUS, developing tools for smart urban energy planning and 15-minute city models. He serves as Editor-in-Chief of Cleaner Engineering and Technology and Guest Editor for multiple journals. His research emphasizes bridging data science with sustainability challenges in manufacturing and energy systems. Key Achievements: Top-ranked in global citations, ESI Highly Cited Papers, and industry-driven sustainability frameworks. Grants: Leads EU-funded projects and collaborates with Siemens Energy on energy transition solutions. Labs & Teams: Part of the Environmental Technology and Management (MILJÖ) division and Unit for Product Service Innovation (MILJOPSI) at Linköping.

• Information Retrieval
• Machine Learning
• Natural Language Processing
• +۳ مورد دیگر

Mohammad Aliannejadi is an Assistant Professor at the IRLab (formerly ILPS) within the Informatics Institute at the University of Amsterdam. His research focuses on Information Retrieval (IR), machine learning, natural language processing (NLP), and conversational systems, particularly in modeling user information needs on mobile devices and conversational search systems. He holds a Ph.D. in Informatics from Università della Svizzera italiana (USI), Lugano, Switzerland, and a M.Sc. in Computer Engineering from Tehran Polytechnic. During his Ph.D., he visited the CIIR Lab at the University of Massachusetts Amherst, USA. His research interests include conversational search systems, recommender systems, unified search frameworks, and user-centric evaluation methodologies. Notable contributions include work on clarifying questions in open-domain dialogues, contextual suggestion systems, and cross-market recommendation. Aliannejadi has organized major shared tasks and workshops, including the IGLU Contest (NeurIPS 2021) and XMRec Workshop (RecSys 2021). He serves on program committees of top IR conferences like SIGIR, CIKM, and ECIR, and has authored over 50 peer-reviewed publications in these areas. His work has received recognition, including top performance in TREC Contextual Suggestion tracks (2015, 2016). He actively contributes to the IR community through teaching, including courses on Information Retrieval and Human-in-the-Loop Machine Learning at the University of Amsterdam.

• Computer Science
• Networking
• Telecommunications
• +۴ مورد دیگر

Prof. Liam Murphy is a Full Professor of Computer Science & Informatics at University College Dublin (UCD) and Director of the Performance Engineering Laboratory. He holds a B.E. from UCD, M.Sc. and Ph.D. from UC Berkeley. His research focuses on performance engineering of networks, software systems, and multimedia transmissions. He has published over 150 peer-reviewed papers and is an IEEE member and Fellow of the Irish Computer Society. Education: B.E. in Electrical Engineering, UCD (1985) M.Sc. & Ph.D. in Electrical Engineering & Computer Sciences, UC Berkeley (1988, 1992) Research Interests: Dynamic resource allocation in networks Cloud computing efficiency Software performance engineering Wireless multimedia systems Quality of Service (QoS) optimization Recent work emphasizes energy-efficient cloud workflows, multi-objective data center optimization, and decentralized traffic simulation. Grants & Awards: Fellow of the Irish Computer Society (2007) Conference Paper Awards (2004, 2002, 2001) Principal Investigator in multiple funded projects (e.g., EU-funded traffic simulation, cloud resource allocation) Advising & Labs: Directed 24 Ph.D. and 8 M.Sc. students. Leads the Performance Engineering Laboratory (PEL), focusing on distributed systems, cloud efficiency, and network performance. Collaborates on industry-relevant projects like crovan (UCD/DCU campus company). Teaching: Coordinates courses on computer science fundamentals, distributed systems performance, and software engineering at UCD.

Anna Choromanskaمشاهده پروفایل

دانشیار

• Machine Learning
• Deep Learning
• Optimization
• +۶ مورد دیگر

Anna Choromanska is an Associate Professor in the Department of Electrical and Computer Engineering at NYU Tandon School of Engineering, with affiliations to NYU Center for Data Science (CDS), NYU Center for Urban Science and Progress (CUSP), NYU Center for Advanced Technology in Communications (CATT), and the C2SMART Center. Her research focuses on deep learning optimization, generalization, and applications in autonomous driving and large-scale data analysis. She holds an Alfred P. Sloan Fellowship and NSF CAREER Award, and her work impacts industries like NVIDIA and Facebook. She directs the Learning Systems Laboratory (LSL), emphasizing interdisciplinary experimental/theoretical work. Research Interests: Machine Learning fundamentals, DL optimization, continual learning, autonomous vehicle systems, large data analysis. Her lab explores DNN learning dynamics, training architecture design, and scalable algorithms. Professional Impact: Over 50 invited talks, workshop organization for top ML conferences, and contributions to open-source projects like Vowpal Wabbit. Her algorithms are deployed in production systems at Facebook and Baidu. Awards: NSF CAREER Award Alfred P. Sloan Fellowship IBM Global University Program Academic Award (2x) Columbia University Presidential Fellowship Advising & Labs: Leads LSL, supervising interdisciplinary projects in optimization and autonomy. Actively involved in NYU's Modern AI seminar series and industry partnerships through CATT. Personal Interests: Accomplished pianist, salsa dancer, and fashion design enthusiast with notable performances and certifications in dance and music.

Frede Blaabjergمشاهده پروفایل

استاد

• Power Electronics
• Wind Turbines
• Photovoltaic (PV) Systems
• +۶ مورد دیگر

Frede Blaabjerg is a Professor at Aalborg University (AAU Energy) , affiliated with the Faculty of Engineering and Science . Since 1998, he has pioneered power electronics research in applications such as wind turbines , photovoltaic (PV) systems , reliability engineering , and Power-2-X technologies. Education : PhD in Electrical Engineering (1995, Aalborg University) Honorary Degrees : Honoris Causa at University Politehnica Timisoara (2017) and Tallinn Technical University (2018) His research focuses on power electronics control , system optimization , and reliability for renewable energy and electric mobility . Recent work includes grid-forming converters , virtual synchronous generators , and smart EV charging systems. Key publication trends span 15+ years , with over 3,733 peer-reviewed articles and 900+ journal papers in power electronics , renewables , and energy storage . Notable book series: Control of Power Electronic Converters and Systems (4 volumes, Elsevier). Scientific Awards : 46 IEEE Prize Paper Awards 2020 IEEE Edison Medal 2019 Global Energy Prize 2014 IEEE William E. Newell Power Electronics Award Leadership Roles : Editor-in-Chief, IEEE Transactions on Power Electronics (2006–2012) Chairman, Danish Council for Research and Innovation Policy (2020–) President, IEEE Power Electronics Society (2019–2020)

Emilio Frazzoliمشاهده پروفایل

استاد

• Autonomous Robotics
• Control Systems
• Game Theory
• +۴ مورد دیگر

Emilio Frazzoli is a Full Professor at ETH Zurich’s Department of Mechanical and Process Engineering. He leads the Institute for Dynamic Systems and Control and the Center for Sustainable Future Mobility, focusing on autonomous systems, robotics, and socio-technical control frameworks. Current affiliations: ETH Zurich (Dynamic Systems and Control, Sustainable Future Mobility) Research: Autonomous mobility-on-demand, game theory for resource allocation, and safety verification in multi-agent systems His work bridges robotics, control theory, and economics, with projects like the open-source AMoDeus simulation framework for autonomous taxis and karma-based resource allocation systems. Recent publications emphasize trustworthy AI, reproducibility in autonomous vehicle control, and human-robot interaction challenges. Notable projects include nuReality (VR-based pedestrian interaction studies) and CARSI II (context-driven vehicle interfaces).

Antonio A. Casilliمشاهده پروفایل

استاد

• Digital Labor
• Sociology of Technology
• Platform Economy
• +۴ مورد دیگر

Antonio A. Casilli is a Professor of Sociology at Télécom Paris (Institut Polytechnique de Paris) and a researcher at the Interdisciplinary Institute of Innovation (i3) . He is an associate member of LACI-IIAC (formerly the Edgar Morin Center) at EHESS and serves as a Faculty Fellow at the Nexa Center for Internet and Society (Polytechnic University of Turin) since 2018. Research Focus: Digital labor, platform economy, AI ethics, and the social implications of technology Awards: Prix Étoiles de la SCAM, Prix Meilleur Documentaire de l'Année (Bangkok), selected as Nature Journal Top Science Pick His work analyzes how digital platforms reshape labor dynamics, privacy norms, and social inequalities. Recent studies explore global AI data work, including fieldwork in Latin America, Africa, and Europe. He advocates for ethical frameworks recognizing human labor behind automation. Media Engagement: Regular contributor to France Culture , Le Monde , Wired , and Rue89 . Authored En attendant les robots (2019) and Schiavi del clic (2020), investigating hidden digital labor structures.

Amin Sakzadمشاهده پروفایل

دانشیار

• Lattice-Based Cryptography
• Wireless Communications
• Post-Quantum Cryptography
• +۶ مورد دیگر

Dr. Amin Sakzad is an Associate Professor in the Department of Software Systems & Cybersecurity at Monash University's Faculty of Information Technology. His research focuses on lattice-based cryptography, wireless communications, and post-quantum security protocols. He holds a PhD in Applied Mathematics from Amirkabir University of Technology (2011) and has held academic roles at Carleton University and Monash since 2012. Dr. Sakzad’s expertise spans lattice coding theory, MIMO systems, and privacy-preserving technologies for genomic databases and blockchain applications. He leads multiple ARC-funded projects, including work on secure databases (SRDBMS) and post-quantum cryptographic primitives for FinTech and energy sectors. His research has been recognized through awards such as the FIT Dean’s Award for Teaching Excellence (2021). Key collaborations include projects on blockchain security (CollinStar Lab), genomic data privacy, and energy market cybersecurity. His work addresses UN SDGs through contributions to quality education (SDG 4) and industry innovation (SDG 9). Recent publications highlight advancements in lattice-based cryptography (e.g., CRYSTALS-Kyber variants), privacy-preserving energy trading, and secure blockchain protocols like FPPW watchtower systems. His research bridges theoretical cryptography with practical implementations in embedded systems and 5G telecommunications. Grants: 16 active/completed projects including $1.2M in ARC funding Advising: Supervising PhD projects on lattice applications in post-quantum crypto and blockchain Labs: Core member of Monash’s Software Defined Telecommunications (SDT) Lab and CollinStar Lab

• Power Systems
• Distributed Energy Resources
• Smart Grids
• +۳ مورد دیگر

Gustavo Valverde Mora is a Lecturer at ETH Zurich's Power Systems Laboratory in the Department of Information Technology and Electrical Engineering. His research focuses on distributed energy resources, smart grid technologies, and power system control, with expertise in behind-the-meter DER integration and hosting capacity analysis. His recent work addresses key challenges in renewable energy integration, including voltage control coordination between transmission and distribution networks, data-driven local control schemes for active distribution grids, and unsupervised load disaggregation techniques using smart meter data. He has developed novel methods for DER modeling, GIS-based system analysis, and distribution network planning. Recognized with multiple awards including the 2022 Costa Rican National Technology Award, he actively contributes to IEEE Task Forces on DER integration. His research demonstrates strong emphasis on practical grid applications, combining theoretical power systems knowledge with advanced data analytics. Dr. Valverde teaches Power System Analysis (227-0526-00L) and maintains collaborations with utilities worldwide on renewable integration challenges.

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +۶ مورد دیگر

Wenpeng Yin is an Assistant Professor in Computer Science and Engineering, specializing in Natural Language Processing and Machine Learning. His research focuses on advancing Large Language Models (LLMs) and their applications in scientific, societal, and interdisciplinary domains. Research Interests : LLMs, medical QA, financial AI, model consistency, and instruction-following frameworks. Recent Work : Investigates low-resource NLP tasks, bias evaluation (Gptbias), and adaptive trading systems using LLMs. Current trends in his publications highlight innovations in multimodal learning, symbolic reasoning, and ethical AI, with a strong emphasis on practical implementations across diverse fields.

Vijay Kumarمشاهده پروفایل

استاد

• Robotics
• Multi-Robot Systems
• Micro Aerial Vehicles
• +۶ مورد دیگر

Vijay Kumar is the Nemirovsky Family Dean of Penn Engineering at the University of Pennsylvania, with faculty appointments in the Departments of Mechanical Engineering, Computer and Information Science, and Electrical and Systems Engineering. He is a leading figure in robotics and computer architecture research. Research Interests include robotics, particularly multi-robot systems and micro aerial vehicles (MAVs), as well as computer architecture innovations for machine learning, GPU acceleration, and datacenter efficiency. His work spans theoretical foundations and practical applications in autonomous systems and hardware optimization. Scientific Awards include: 1991 NSF Presidential Young Investigator Award 1996 Lindback Award for Distinguished Teaching 2012 ASME Mechanisms and Robotics Award 2014 Engelberger Robotics Award 2017 IEEE George Saridis Leadership Award Multiple best paper awards at DARS, ICRA, and RSS conferences Editorial Leadership includes serving as Editor of the ASME Journal of Mechanisms and Robotics and Advisory Board Member of AAAS Science Robotics Journal . His GRASP Lab team developed foundational frameworks for micro UAV testbeds and swarm robotics.