جست‌وجوی استاد و پژوهشگر

Nur Zincir-Heywoodمشاهده پروفایل

استاد

• Cyber Security
• Resilience
• Autonomous Cyber Operations
• +۹ مورد دیگر

Nur Zincir-Heywood is a Distinguished Research Professor and Associate Dean (Research) in the Faculty of Computer Science at Dalhousie University, Halifax, Nova Scotia, Canada. She has been a Full Professor since 2010, following progressive academic appointments from Assistant to Associate Professor. Her research centers on developing intelligent and secure systems for modeling and analyzing behaviors across networks and services. Key areas include: Cyber Security and Resilience Autonomous Cyber Operations Threat Analysis and Detection Machine Learning and Big Data Analytics Computer Communications and Networks Her recent recognition as a Distinguished Research Professor reflects her significant contributions to research and scholarship. She leads the NIMS Lab and is actively involved in research clusters focused on Systems, Big Data Analytics, AI, and Machine Learning. She also co-organized the 'Dal FCS Hands on Security Day' with industry partners like Cisco and 2Keys. A special issue she is involved with in IEEE TNSM on AI for network and service management highlights her leadership in cutting-edge domains. Scientific awards include: Distinguished Research Professor (2021–present) She advises students and leads research projects, with fellowship opportunities currently available in her lab. Her work bridges academic innovation with real-world applications in security and intelligent systems. She is also engaged with public outreach, occasionally appearing on CBC Information Morning.

• Computer Networks
• Data Center Networking
• Software Defined Networking (SDN)
• +۵ مورد دیگر

Yashar Ganjali is a Professor in the Department of Computer Science at the University of Toronto , leading the Systems and Networking Group . His research spans computer networks , with a focus on data center networking , software-defined networking (SDN) , and congestion control . Education : Not explicitly detailed, but inferred from academic rank as a Professor. His work on flow consolidation , load migration in SDN controllers , and machine learning for network management has been influential. Recent projects include FORESIGHT (2025) for ML-driven scheduling and Meta-Migration (2023) to reduce switch migration latency. Scientific Awards include the IFIP Networking 2025 Best Paper Award . Collaborations with institutions like Google (2024) and Facebook (2019) highlight his industry impact. Advisees include Sepehr Abbasi Zadeh (PhD, 2024). Current projects integrate optical packet switching and eBPF-based network augmentation , aiming to address scalability, micro-bursts, and resource allocation efficiency in cloud environments.

Sherry Tongshuang Wuمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Natural Language Processing
• Artificial Intelligence
• +۶ مورد دیگر

Sherry Tongshuang Wu is an Assistant Professor at Carnegie Mellon University's School of Computer Science, with primary appointments in the Human-Computer Interaction Institute (HCII) and secondary affiliation with the Language Technology Institute (LTI) . Trained at the University of Washington under Jeffrey Heer and Dan Weld, she bridges HCI and NLP to study human interactions with AI systems across diverse user groups. Her educational background includes a Ph.D. (2016-22) and M.S. (2016-18) in Computer Science and Engineering from the University of Washington, and a B.Eng. (2012-16) from Hong Kong University of Science and Technology. Industry experience includes research internships at Google Brain, Microsoft Research, and Apple. Wu's research focuses on three interconnected pillars: Real-world AI Evaluation (developing frameworks like SPHERE for systematic assessment), Task-specific AI Test & Distill (optimizing general-purpose models for specific use cases), and Human-AI Task Delegation (designing optimal collaboration between humans and AI). Her work emphasizes practical deployment, user-specific net gains, and error recovery mechanisms. Analysis of her 15 most recent publications reveals a strong trend toward evaluation frameworks (35%), human-AI collaboration systems (30%), and specialized model distillation (25%), with growing emphasis on educational applications (10%). Key methodological themes include checklist-based evaluation, perspective-aware retrieval, and structural analysis of AI outputs. Google Academic Research Award (2024) Amazon Research Awards (2024) AIED 2024 Best Paper Award ACL 2020 Best Paper Award Rising Stars in EECS Workshop (2020) Wu actively mentors 19 students across PhD, Master's, and undergraduate levels, with notable projects including synthetic data generation, LLM literacy tools, and retrieval system optimization. She leads significant grant-funded work through Amazon Research Awards and Google Academic Research Awards, focusing on deployable model generation and human-AI collaboration frameworks. Her lab develops practical tools like Promp2Model and SPHERE that bridge theoretical research with industry applications.

• Market Microstructure Theory
• Digital Finance
• FinTech
• +۳ مورد دیگر

Prof. Dr. Peter Gomber is a Professor of e-Finance at the Faculty of Economics and Business Administration , Goethe University Frankfurt, since 2004. He co-chairs the Data Science Institute (efl) and holds adjunct professorships at the University of Bamberg (2004), Mannheim (2009), and Luxembourg (2018). His roles include board memberships at the Frankfurt Stock Exchange, Clearstream Banking AG, and advisory positions for European regulatory bodies. Education : Diplom-Kaufmann in Economics, University of Gießen (1999), PhD in Business Informatics. Research Interests focus on market microstructure , FinTech , electronic trading , and regulatory impacts on financial markets. His work explores algorithmic trading , liquidity dynamics , and AI-driven compliance . Publication Trends (15 most recent) emphasize digital finance , market fragmentation , regulatory analysis , and AI applications in trading and compliance. Key subfields include blockchain , high-frequency trading , and news-driven liquidity shocks . Scientific Awards : Reuters Innovation Award (2000) Hochschulpreis des Deutschen Aktieninstituts (1999) IBM SUR Grant (2007) Best Paper Awards (multiple conferences) Best Information Systems Publications Award (2020) Advising & Grants : Teaches in executive programs (Goethe Business School, Amsterdam Institute of Finance). Secured grants from public/private institutions, including a U.S. patent for market model innovation. Labs & Teams : Leads the e-Finance professorship and contributes to the Data Science Institute (efl) , fostering industry-academia collaborations with Deutsche Börse, Capveriant, and others.

Athina E Markakiمشاهده پروفایل

استاد

• Tissue Engineering
• Biomaterials
• Regenerative Medicine
• +۳ مورد دیگر

Professor Athina E Markaki serves as Professor of Materials & Biomedical Engineering in the Department of Engineering at the University of Cambridge, leading research in advanced biomaterials and tissue engineering solutions for regenerative medicine with emphasis on vascularization and tubular scaffold development for human conduit replacement. Her academic credentials include a Diploma in Metallurgical Engineering (8.6/10) from the National Technical University of Athens and a PhD in Materials Science from the University of Cambridge. Markaki's research program centers on vascularisation techniques for clinically relevant tissue dimensions and tubular scaffolds to replace diseased or damaged human conduits, integrating biomaterials science with regenerative medicine principles. Key applications span liver tissue engineering, neural crest-derived stem cell differentiation, and vascular graft development, with strong translational focus on orthopaedic and cardiovascular medical devices. Analysis of her recent publications reveals dominant trends in biomimetic scaffold design, particularly collagen-based tubular structures and hydrogel systems for vascularized tissue constructs. Her work demonstrates interdisciplinary convergence of AI-driven retinal assessment, glioblastoma modeling, and self-healing cementitious materials, with consistent emphasis on clinically applicable regenerative solutions for liver, bone, and neural tissues. Her distinguished scientific contributions are recognized by major awards: Rosetrees Trust 2017 Interdisciplinary Award European Research Council (ERC) Starting Grant (2010) Advanced EPSRC Fellowship (2005) De Montfort Award at SET for Britain National Event (2004) Young Scientist Prize 2003 (5th Euromech Solid Mechanics Conference) Multiple academic excellence awards from Greek foundations Markaki directs a well-funded research program including ERC and EPSRC grants, mentoring graduate students in tissue engineering while teaching core engineering curricula covering plastic deformation, fracture mechanics, and medical materials design. Her group maintains strong industry and clinical partnerships to advance regenerative technologies. Her laboratory, accessible via http://www-memti.eng.cam.ac.uk/, specializes in vascularized tissue constructs and tubular scaffolds using laser-based manufacturing, biomimetic design, and hydrogel engineering to address critical challenges in tissue replacement and disease modeling.

Norman Sadehمشاهده پروفایل

استاد

• cybersecurity
• online privacy
• Human-AI Interaction
• +۱۱ مورد دیگر

Norman Sadeh is a Professor in the School of Computer Science at Carnegie Mellon University (CMU), where he has made significant contributions to cybersecurity, privacy, and AI research. He has co-founded and co-directed several groundbreaking graduate programs at CMU, including the Privacy Engineering Program (2012-present), the Ph.D. Program in Societal Computing (2003-2013), and the MBA track in Technology Strategy and Product Management (2005-2017). Carnegie Mellon University, School of Computer Science Software and Societal Systems Department CyLab Security and Privacy Institute Manufacturing Futures Institute Dr. Sadeh received his Ph.D. in Computer Science at CMU with a major in Artificial Intelligence and a minor in Operations Research. He holds an M.Sc. in computer science from the University of Southern California and a BS/MS degree in electrical engineering and applied physics from the Free University of Brussels (Belgium) as 'Ingénieur Civil Physicien.' Professor Sadeh's research spans cybersecurity, online privacy, Human-AI Interaction, AI governance, mobile computing, the Internet of Things, user-oriented machine learning, and language technologies. He is particularly known for his pioneering work on AI-based privacy enhancing technologies, including privacy assistants, automated privacy compliance tools, and NLP-based privacy solutions. His work has influenced the design of privacy features at major technology companies including Apple, Google, and Facebook/Meta, as well as privacy policies at regulatory agencies like the Federal Trade Commission and the California Office of the Attorney General. Analysis of his recent publications shows a strong focus on practical privacy solutions, particularly in mobile and IoT contexts, with an emphasis on making privacy more usable and understandable for end users. His work bridges technical innovation with policy implications, addressing both the technological and human aspects of privacy protection. 2018 Outstanding Entrepreneur of the Year award from the Pittsburgh Venture Capital Association Test of time award by the AAAI Conference on Web and Social Media (ICWSM) Gartner Group's Magic Quadrant leader in Security Awareness Computer-Based Training for 4 consecutive years Deloitte's Technology Fast 500 recognition for 3 consecutive years Professor Sadeh has advised numerous students, including PhD candidates like Aerin (Shikhun) Zhang, whose dissertation focused on understanding diverse privacy attitudes. His research has been funded through various grants, including NSF SaTC projects, and has resulted in technologies that protect tens of millions of users worldwide. He also founded Wombat Security Technologies, which was acquired by Proofpoint in 2018 and whose technologies are used by over 75% of Fortune 100 companies. Professor Sadeh leads several research initiatives including the Privacy Engineering Program, the Usable Privacy Policy Project, the Personalized Privacy Assistant Project, and CMU's Privacy Infrastructure for the Internet of Things. His Mobile Commerce Lab and E-Supply Chain Management Lab have produced influential research that has been commercialized by major organizations including IBM, Raytheon, Boeing, and the U.S. Army.

• Reconfigurable Computing
• Machine Learning Acceleration
• Hardware Acceleration
• +۵ مورد دیگر

Aman Arora is an Assistant Professor at Arizona State University's Ira A. Fulton Schools of Engineering, specializing in the School of Computing and Augmented Intelligence. His research focuses on reconfigurable computing, hardware acceleration of machine learning, and non-traditional computing paradigms like Processing-In-Memory. With over a decade of semiconductor industry experience, he bridges academic research and industrial applications. PhD in Computer Science from The University of Texas at Austin Research interests emphasize domain-specific acceleration through FPGA optimization , compute-in-memory architectures , and machine learning for CAD/EDA . His work addresses critical challenges in energy efficiency and throughput for AI workloads. Recent publications demonstrate trends toward compute-in-memory systems , FPGA-based deep learning acceleration , and sustainable hardware design . Key contributions include frameworks like SAF, CSR, and GAMA for dynamic hardware optimization. Laboratory Website: ADVENT Lab Teaching includes courses on digital hardware design (CSE 320) and advanced topics in machine learning acceleration (CEN 524/CSE 524). Industry experience informs his practical approach to research and education.

M. Tamer Özsuمشاهده پروفایل

استاد

• Data Science
• Database Systems
• Distributed Data Management
• +۳ مورد دیگر

M. Tamer Özsu is a University Professor of Computer Science at the David R. Cheriton School of Computer Science, University of Waterloo, where he holds a Cheriton Faculty Fellowship. He also serves as a Distinguished Visiting Professor at Tsinghua University and is the Founding Director of Waterloo-Huawei Joint Innovation Laboratory since 2018. His extensive contributions to computing have earned him numerous prestigious awards including the 2024 ACM Presidential Award for long-standing and significant contributions to the computing field. Professor Özsu's research focuses on data engineering aspects of data science, particularly addressing data management issues with two main foci: management of non-traditional data and large-scale distributed data management. He is renowned for his seminal book "Principles of Distributed Database Systems" (co-authored with Patrick Valduriez), now in its fourth edition, and the "Encyclopedia of Database Systems" (co-edited with Ling Liu), in its second edition. His work bridges theoretical foundations with practical system implementations, targeting grand societal challenges through computational approaches. His recent publications reveal a strong trend toward graph analytics, streaming data processing, and the integration of large language models with vector data management. The research shows increasing focus on GPU-accelerated graph processing, RDF query optimization, and multimodal data analysis, reflecting the evolution of data management challenges in the era of big data and AI. His work continues to address fundamental challenges in distributed data systems while adapting to emerging technologies and application domains. Scientific Awards and Fellowships ACM Presidential Award (2024) IEEE TCDE Education Award (2024) IEEE Innovation in Societal Infrastructure Award (2022) CS Can | Info Can Lifetime Achievement Award (2018/2019) ACM SIGMOD Test-of-Time Award (2015) ACM SIGMOD Contributions Award (2006) The Ohio State University College of Engineering Distinguished Alumnus Award (2008) Fellow of the Royal Society of Canada Fellow of the American Association for the Advancement of Science (AAAS) Life Fellow of the Association for Computing Machinery (ACM) Life Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA) Elected member of the Science Academy, Türkiye Professor Özsu has been deeply involved in academic leadership and community building. As Founding Editor-in-Chief of ACM Books (2013-2019), he launched a series that by 2019 had published 28 major books with another 30 under contract. His service to ACM, particularly through SIGMOD, has been exemplary and widely recognized. He directs the Waterloo-Huawei Joint Innovation Laboratory, which focuses on cutting-edge research in data management and distributed systems, fostering strong industry-academia collaboration.

• Sustainable Machining Processes
• Tool Wear Monitoring
• Surface Roughness Optimization
• +۳ مورد دیگر

Doç. Dr. Muhammed Aras is an Associate Professor in the Department of Mechanical Engineering at Baskent University (Başkent Üniversitesi), with a research focus on sustainable machining processes, tool wear monitoring, and surface roughness optimization. His work spans advanced manufacturing technologies, energy storage systems, and biomedical device design. PhD in Manufacturing Engineering (2018), Gazi Üniversitesi MSc in Mechanical Education (2013), Gazi Üniversitesi BSc in Mechanical Engineering (2010), Tabriz Islamic Azad University Research interests include sustainable machining (dry/hard turning, cooling-lubrication strategies), tool wear analysis (CBN, ceramic and coated inserts), and surface integrity optimization using AI-based methods (firefly algorithm, TOPSIS, Grey Relational Analysis). His 15 most recent articles (2017-2024) examine topics like: Surface roughness prediction in dry hard turning Energy storage technology viability assessments Cutting parameter optimization for various steels Acoustic/vibration monitoring in machining He has received scientific awards including the Teşvik Ödülü (Encouragement Award, 2015). His patent on an automatic orthognathic surgery articulator and book chapters on tool monitoring systems demonstrate his multidisciplinary impact.

Jonathan Külzمشاهده پروفایل

پژوهشگر

• Modular Robotics
• Robotics
• Reinforcement Learning
• +۳ مورد دیگر

Jonathan Külz is a Researcher at the Technical University of Munich (TUM) , affiliated with the Department of Informatics 6 - Chair for Cyber Physical Systems under Prof. Matthias Althoff. His research focuses on Modular Robotics , Reinforcement Learning , Cyber-Physical Systems , and Control Systems . His work includes algorithmic synthesis of modular robot compositions, model-based manipulator co-design, and unifying benchmarks for robotics. He has supervised multiple Master’s theses Bachelor’s theses Practical courses on topics like Robot Workspace Representation and Dynamic Model Identification . Notable supervised projects include Autonomous Navigation of Reachbot and Task-Based Modular Robot Configuration Synthesis . His recent publications span Robotics , Benchmarking , and Computational Social Science . Key trends include Computationally efficient assessment of robot capabilities Deep reinforcement learning for robotics Analysis of political discourse polarization Jonathan emphasizes structured thesis supervision, requiring exposés, shared folders, and protocol-driven meetings. He advocates for LaTeX in scientific writing and tools like NotebookLM and Zettlr for research documentation.

Jia Chenمشاهده پروفایل

استاد

• Urban greenhouse gas monitoring
• Atmospheric modeling
• Sensor development
• +۷ مورد دیگر

Professor Jia Chen is a Professor of Environmental Sensing and Modeling at the Technical University of Munich (TUM), holding positions in both the TUM School of Computation, Information and Technology (CIT) and the Department of Electrical and Computer Engineering, as well as the Department of Civil, Geo and Environmental Engineering. She also maintains an affiliation as an Associate at Harvard University. Her pioneering work focuses on developing novel optical sensors and atmospheric models to monitor and quantify greenhouse gas emissions in urban environments. Professor Chen's most significant contribution is the development of the differential column measurement method and the establishment of MUCCnet, the world's first permanent urban column sensor network. This groundbreaking work enables continuous, city-wide monitoring of greenhouse gases. Her research team has made notable discoveries, including quantifying methane emissions from events like the Munich Oktoberfest and identifying previously underestimated urban emission sources. Her research spans atmospheric science, environmental engineering, and climate change mitigation, with particular emphasis on: Urban greenhouse gas monitoring systems Advanced atmospheric modeling techniques Sensor network development for environmental monitoring Integration of machine learning with emission quantification Urban air quality assessment methodologies Professor Chen has received numerous prestigious awards including: Timothy Oke Award (2024) for original research in urban climatology ERC Consolidator Grant (2022) Arnold Sommerfeld-Award (2021) Germany's "Top 40 under 40" recognition by Capital Magazine (2020) Membership in the Global Young Academy (2021) She leads an extensive research group with numerous PhD students and postdoctoral researchers, and her work is supported by major funding from ERC, EU Horizon 2020, United Nations Environment Programme, NASA, ESA, German Federal Ministry of Education and Research, and German Research Foundation. Professor Chen has authored over 180 publications and 12 patents, with an h-index of 35.

Sara Dolnicarمشاهده پروفایل

استاد

• Sustainable Tourism
• Market Segmentation
• Social Marketing
• +۷ مورد دیگر

Professor Sara Dolnicar is an ARC Australian Laureate Fellow at the School of Business, Faculty of Business, Economics and Law, University of Queensland. With degrees in psychology and business administration from Wirtschaftsuniversität Wien, she specializes in market segmentation, sustainable tourism, social marketing, and environmental behavior. Born in Slovenia, raised in Austria, now based in Australia Over 300 refereed publications and 16 ARC grants Recipient of TTRA Distinguished Researcher Award (2017) and Slovenian Ambassador of Science (2016) Her research improves market segmentation methodology, addresses environmental sustainability in tourism, and develops behavioral interventions for eco-friendly tourist practices. She pioneered perceptions-based market segmentation and introduced bi-clustering techniques for improved data analysis. Recent publications focus on towel reuse interventions, buffet waste reduction, and smart sensor systems for hotel sustainability. She supervises PhD students in environmental behavior, tourism carbon emissions, and IoT applications for sustainability. Current grants include 'Mechanisms of Behaviour Change Theory' (2025-2028) and 'Reducing plate waste in hotels' (2021-2025). Key research areas: Sustainable tourism, market segmentation, social marketing Supervised over 15 PhD students in environmental behavior and disability employment Collaborates with industry partners like Energy Queensland and disability organizations

Ayse Coskunمشاهده پروفایل

استاد

• Energy-efficient computing
• Cloud computing
• High performance computing
• +۷ مورد دیگر

Ayse Coskun is a Professor in the Electrical and Computer Engineering Department at Boston University's College of Engineering. She serves as Director of the Center for Information and Systems Engineering (CISE) and as interim Associate Dean for Research and Faculty Development. Her research focuses on the intersection of computer systems, energy efficiency, and AI. Dr. Coskun received her PhD from the University of California, San Diego in 2009. Prior to joining academia, she worked at Sun Microsystems (now Oracle). Her research spans energy-efficient computing, cloud computing, high performance computing, computer architecture, and embedded systems, with recent work focusing on AI's impact on data center energy demands. Her publication record shows consistent innovation across multiple domains, with recent work emphasizing AI applications for improving cloud security (through frameworks like DeltaSherlock and Praxi) and transforming data centers into grid-responsive assets (Emerald AI project). Her research bridges theoretical advances with practical applications, resulting in tools adopted by industry partners including IBM. IBM Faculty Award (2020) Ernest S. Kuh Early Career Award (2017) NSF CAREER Award (2012-2017) Multiple best paper and artifact awards at top conferences As an educator, Dr. Coskun teaches courses including EC327 Introduction to Software Engineering, EC535 Introduction to Embedded Systems, and EC713 Advanced Computing Systems and Architecture. She has advised numerous PhD students including Mert Toslali, Anthony Byrne, and Burak Aksar. Her lab maintains strong industry partnerships with IBM, Intel, AMD, and Oracle, and collaborates with academic institutions worldwide including Brown University, MIT, EPFL, and CEA-Tech in France. Dr. Coskun leads the Coskun Lab, which secured a $500K grant from Sandia National Labs for AI-based analytics in high performance computing systems, demonstrating the practical impact of her research on critical computing infrastructure.

• Computer Learning
• Fuzzy Sets and Systems
• Decision Support Systems
• +۳ مورد دیگر

Prof. Sadettin Emre Alptekin is a full Professor of Industrial Engineering at Galatasaray University, Faculty of Engineering and Technology, where he also serves as Vice Dean. Since joining the university as a research assistant in 2000, he has steadily advanced through the academic ranks, becoming an Assistant Professor (2006–2010), Associate Professor (2010–2023), and finally Professor in 2023. Education: PhD (Dr), Industrial Engineering, Istanbul Technical University, Institute of Science and Technology, 2001–2006 MSc, Industrial Engineering, Galatasaray University, Faculty of Engineering and Technology, 1999–2001 BSc, Industrial Engineering, Istanbul Technical University, Faculty of Management, 1995–1999 Languages: Advanced English (C1), Upper-Intermediate French (B2), Advanced German (C1) Research Interests: Prof. Alptekin’s research focuses on Computer Learning , Fuzzy Sets and Systems , and Decision Support Systems . His work integrates artificial intelligence, machine learning, and soft-computing techniques to solve complex industrial and managerial problems in areas such as supply chain management, quality function deployment, blockchain adoption, and mental-health prediction. Publication Trends: Across more than 50 refereed publications, Prof. Alptekin has consistently explored hybrid intelligent models that combine fuzzy logic, machine learning, and multi-criteria decision-making. Recent articles emphasize deep-learning-based anomaly detection in industrial time-series data, blockchain adoption in supply chains, and machine-learning applications in subjective well-being and mental-health modeling. Scientific Awards & Honors: No specific awards or medals are listed in the provided documents. Research Leadership & Funding: Since 2008 he has been the principal investigator (executive) of 12 nationally funded projects, covering topics such as Industry 4.0 sub-system design, Internet of Things applications, artificial neural networks in organizational decision-making, big-data analytics, and strategic decision processes. Graduate Advising: He has formally supervised at least 8 master’s theses and numerous undergraduate projects. Representative thesis titles include Gaussian-process-regression-based man-hour prediction, machine-learning-driven human-behavior modeling, recommender-system design for e-commerce, thyroid-nodule diagnosis from scintigraphic images, software-effort estimation via neural networks, spreadsheet heuristics for joint-replenishment problems, cross-selling decision systems in insurance, and profitability analyses of Turkish banks under disinflation. Laboratories & Teams: While no dedicated laboratory name is disclosed, his continuous role as Vice Dean and principal investigator implies active leadership of the Industrial Engineering department’s research clusters in intelligent systems and decision support technologies.

Ion Stoicaمشاهده پروفایل

استاد

• Distributed Systems
• Cloud Computing
• AI Systems
• +۳ مورد دیگر

Ion Stoica is a Professor in the Electrical Engineering and Computer Sciences Department at the University of California, Berkeley, where he holds the Xu Bao Chancellor Chair. He serves as Director of the Sky Computing Lab and is Executive Chairman of both Databricks and Anyscale. His research spans distributed systems, cloud computing, and AI systems, with significant contributions to large-scale data processing frameworks. Stoica's research interests focus on the intersection of AI and systems, with emphasis on developing practical implementations that bridge theoretical foundations with real-world deployability. His work addresses fundamental challenges in distributed computing, resource management, and large-scale machine learning systems. Current projects include Ray (a distributed execution framework), vLLM (a high-throughput inference engine for LLMs), Chatbot Arena (an open platform for human preference evaluations), and SkyPilot (a framework for running AI workloads across clouds). His research output demonstrates a consistent trajectory toward more efficient, scalable systems for modern AI workloads, particularly focusing on optimizing inference performance, resource utilization, and cross-cloud deployment. Recent publications reflect growing interest in large language model serving, video generation optimization, and agent-based systems. ACM Fellow SIGOPS Hall of Fame Award (2015) SIGCOMM Test of Time Award (2011) ACM Doctoral Dissertation Award (2001) Member of National Academy of Engineering Honorary Member of the Romanian Academy Stoica has advised an extensive number of doctoral students who have gone on to prominent positions in academia and industry, including assistant professorships at Stanford, MIT, Carnegie Mellon, and other top institutions. He has received significant research funding through his lab activities and startup ventures. His research group has been particularly successful in translating academic research into widely adopted open-source technologies and commercial products. Stoica leads the Sky Computing Lab at UC Berkeley, which focuses on developing systems for AI workloads across multiple clouds. His research group has produced numerous influential open-source projects including Apache Spark, Apache Mesos, and Alluxio, which have become industry standards for large-scale data processing. The lab maintains strong industry partnerships while pursuing fundamental research in distributed systems and AI infrastructure.