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"search_blob": "Robust statistics with algorithmic reach | ACM Grace Murray Hopper Award | Grace Hopper Award | Highlights a single recent generation-defining contribution from a young computing professional. | Ilias Diakonikolas | algorithms robust statistics machine learning | University of Wisconsin–Madison | Highlights algorithmic robust statistics as a fast-growing bridge between theory and practical machine learning reliability. | Algorithmic High-Dimensional Robust Statistics | 2024 | 2020s" }, { "id": "ijcai-2024-dietterich", "year": 2024, "award_slug": "ijcai-research-excellence-award", "person_names": [ "Thomas G. 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Dietterich", "decade": "2020s", "featured": false, "search_blob": "Machine learning for robust and trustworthy AI | IJCAI Research Excellence Award | IJCAI Research Excellence | Career award for major contributions to artificial intelligence research. | Thomas G. Dietterich | artificial intelligence machine learning robustness | Oregon State University | Recognized a career of influential machine learning research spanning ensemble methods, sequential decision-making, and robust AI systems. | Machine Learning for Sequential Data: A Review | 2024 | 2020s" }, { "id": "kanellakis-2024-krawczyk", "year": 2024, "award_slug": "kanellakis-award", "person_names": [ "Hugo Krawczyk" ], "person_slugs": [ "hugo-krawczyk" ], "title": "Provable security with practical impact", "kind": "laureate", "topics": [ "cryptography", "security", "protocols" ], "institutions": [ "Technion", "Amazon Web Services" ], "significance": "Shows how provable-security ideas can become durable foundations for real-world protocol and infrastructure security.", "related_works": [ { "title": "HMQV: A High-Performance Secure Diffie-Hellman Protocol", "type": "paper", "year": 2005, "url": "https://iacr.org/archive/crypto2005/36210372/36210372.pdf", "source_quality": "canonical" } ], "award_name": "Kanellakis Award", "award_category": "bridge_award", "official_program_label": "Official awards page / index", "official_program_url": "https://awards.acm.org/kanellakis", "event_source_label": null, "event_source_url": null, "source_scope": "program-level", "citation_specificity": "not-year-specific", "person_label": "Hugo Krawczyk", "decade": "2020s", "featured": false, "search_blob": "Provable security with practical impact | ACM Paris Kanellakis Theory and Practice Award | Kanellakis Award | Honors theoretical work with concrete influence on computing practice. | Hugo Krawczyk | cryptography security protocols | Technion Amazon Web Services | Shows how provable-security ideas can become durable foundations for real-world protocol and infrastructure security. | HMQV: A High-Performance Secure Diffie-Hellman Protocol | 2024 | 2020s" }, { "id": "knuth-2024-alur", "year": 2024, "award_slug": "knuth-prize", "person_names": [ "Rajeev Alur" ], "person_slugs": [ "rajeev-alur" ], "title": "Timed and hybrid models for system design", "kind": "laureate", "topics": [ "formal methods", "verification", "cyber-physical systems" ], "institutions": [ "University of Pennsylvania" ], "significance": "Celebrates foundational models that shaped verification, synthesis, and analysis for modern reactive and cyber-physical systems.", "event_source_label": "2024 Knuth Prize citation", "event_source_url": "https://sigact.org/prizes/knuth/citation2024.html", "related_works": [ { "title": "Principles of Cyber-Physical Systems", "type": "book", "year": 2015, "url": "https://mitpress.mit.edu/9780262029117/principles-of-cyber-physical-systems/", "source_quality": "canonical" } ], "award_name": "Knuth Prize", "award_category": "theory_award", "official_program_label": "Official awards page / index", "official_program_url": "https://sigact.org/prizes/knuth-prize/", "source_scope": "event-level", "citation_specificity": "year-specific-or-event-specific", "person_label": "Rajeev Alur", "decade": "2020s", "featured": false, "search_blob": "Timed and hybrid models for system design | Donald E. 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Barto", "Richard S. Sutton" ], "person_slugs": [ "andrew-g-barto", "richard-s-sutton" ], "title": "Reinforcement learning foundations", "kind": "laureate", "topics": [ "artificial intelligence", "reinforcement learning", "control" ], "institutions": [ "University of Massachusetts Amherst", "University of Alberta" ], "significance": "Recognized the concepts and methods that made reinforcement learning a durable core area of AI.", "related_works": [ { "title": "Reinforcement Learning: An Introduction", "type": "book", "year": 1998, "url": "https://incompleteideas.net/book/the-book.html", "source_quality": "contextual" } ], "featured": true, "award_name": "Turing Award", "award_category": "major_award", "official_program_label": "Official awards page / index", "official_program_url": "https://awards.acm.org/turing", "event_source_label": null, "event_source_url": null, "source_scope": "program-level", "citation_specificity": "not-year-specific", "person_label": "Andrew G. Barto, Richard S. Sutton", "decade": "2020s", "search_blob": "Reinforcement learning foundations | ACM A.M. Turing Award | Turing Award | Often described as the highest distinction in computer science, honoring lasting technical contributions across the field. | Andrew G. Barto Richard S. Sutton | artificial intelligence reinforcement learning control | University of Massachusetts Amherst University of Alberta | Recognized the concepts and methods that made reinforcement learning a durable core area of AI. | Reinforcement Learning: An Introduction | 2024 | 2020s" }, { "id": "vonneumann-2024-manning", "year": 2024, "award_slug": "john-von-neumann-medal", "person_names": [ "Christopher D. Manning" ], "person_slugs": [ "christopher-d-manning" ], "title": "Statistical and neural language understanding", "kind": "laureate", "topics": [ "natural language processing", "machine learning", "representation learning" ], "institutions": [ "Stanford University" ], "significance": "Recognized work spanning statistical NLP, large-scale language resources, and neural representation methods that reshaped modern language AI.", "related_works": [ { "title": "GloVe: Global Vectors for Word Representation", "type": "paper", "year": 2014, "url": "https://doi.org/10.3115/v1/D14-1162", "source_quality": "canonical" } ], "featured": true, "award_name": "von Neumann Medal", "award_category": "major_award", "official_program_label": "Official awards page / index", "official_program_url": "https://www.ieee.org/about/awards/medals/von-neumann.html", "event_source_label": null, "event_source_url": null, "source_scope": "program-level", "citation_specificity": "not-year-specific", "person_label": "Christopher D. Manning", "decade": "2020s", "search_blob": "Statistical and neural language understanding | IEEE John von Neumann Medal | von Neumann Medal | Recognizes career-level leadership and impact spanning computing science and engineering, from core systems to modern computational methods. | Christopher D. Manning | natural language processing machine learning representation learning | Stanford University | Recognized work spanning statistical NLP, large-scale language resources, and neural representation methods that reshaped modern language AI. | GloVe: Global Vectors for Word Representation | 2024 | 2020s" }, { "id": "hopper-2023-mittal", "year": 2023, "award_slug": "grace-murray-hopper-award", "person_names": [ "Prateek Mittal" ], "person_slugs": [ "prateek-mittal" ], "title": "Cross-layer internet privacy and security", "kind": "laureate", "topics": [ "security", "privacy", "internet" ], "institutions": [ "Princeton University" ], "significance": "Recognized foundational work on protecting internet privacy and security through cross-layer methods spanning networks, anonymity, and machine learning.", "event_source_label": "2023 ACM technical awards announcement", "event_source_url": "https://awards.acm.org/about/2023-technical-awards", "related_works": [ { "title": "Prateek Mittal research profile", "type": "profile", "year": 2023, "url": "https://www.cs.princeton.edu/~pmittal/", "source_quality": "contextual" } ], "award_name": "Grace Hopper Award", "award_category": "major_award", "official_program_label": "Official awards page / index", "official_program_url": "https://awards.acm.org/hopper", "source_scope": "event-level", "citation_specificity": "year-specific-or-event-specific", "person_label": "Prateek Mittal", "decade": "2020s", "featured": false, "search_blob": "Cross-layer internet privacy and security | ACM Grace Murray Hopper Award | Grace Hopper Award | Highlights a single recent generation-defining contribution from a young computing professional. | Prateek Mittal | security privacy internet | Princeton University | Recognized foundational work on protecting internet privacy and security through cross-layer methods spanning networks, anonymity, and machine learning. | Prateek Mittal research profile | 2023 | 2020s" }, { "id": "knuth-2023-tardos", "year": 2023, "award_slug": "knuth-prize", "person_names": [ "Éva Tardos" ], "person_slugs": [ "eva-tardos" ], "title": "Algorithms, approximation, and game theory", "kind": "laureate", "topics": [ "algorithms", "approximation algorithms", "algorithmic game theory" ], "institutions": [ "Cornell University" ], "significance": "Recognized career-defining contributions to combinatorial optimization, approximation algorithms, and algorithmic game theory.", "event_source_label": "2023 Knuth Prize citation", "event_source_url": "https://sigact.org/prizes/knuth/citation2023.html", "related_works": [ { "title": "Algorithm Design", "type": "book", "year": 2005, "url": "https://www.cs.princeton.edu/~wayne/kleinberg-tardos/", "source_quality": "contextual" } ], "award_name": "Knuth Prize", "award_category": "theory_award", "official_program_label": "Official awards page / index", "official_program_url": "https://sigact.org/prizes/knuth-prize/", "source_scope": "event-level", "citation_specificity": "year-specific-or-event-specific", "person_label": "Éva Tardos", "decade": "2020s", "featured": false, "search_blob": "Algorithms, approximation, and game theory | Donald E. Knuth Prize | Knuth Prize | Celebrates landmark achievements in theoretical computer science across a career. | Éva Tardos | algorithms approximation algorithms algorithmic game theory | Cornell University | Recognized career-defining contributions to combinatorial optimization, approximation algorithms, and algorithmic game theory. | Algorithm Design | 2023 | 2020s" }, { "id": "vldb-2023-distributed-graphlab", "year": 2023, "award_slug": "vldb-ten-year-award", "person_names": [ "Yucheng Low", "Joseph Gonzalez", "Aapo Kyrola", "Danny Bickson", "Carlos Guestrin", "Joseph M. Hellerstein" ], "person_slugs": [ "yucheng-low", "joseph-gonzalez", "aapo-kyrola", "danny-bickson", "carlos-guestrin", "joseph-m-hellerstein" ], "title": "Distributed GraphLab for machine learning in the cloud", "kind": "paper_award", "topics": [ "machine learning systems", "distributed systems", "databases" ], "institutions": [ "Carnegie Mellon University", "University of California, Berkeley" ], "significance": "Recognized a test-of-time systems paper that helped shape large-scale graph-parallel machine learning and cloud analytics infrastructure.", "event_source_label": "VLDB 2023 conference awards", "event_source_url": "https://vldb.org/2023/?conference-awards", "related_works": [ { "title": "Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud", "type": "paper", "year": 2012, "url": "https://www.vldb.org/pvldb/vol5/p716_yuchenglow_vldb2012.pdf", "source_quality": "canonical" } ], "award_name": "VLDB 10-Year Award", "award_category": "paper_award", "official_program_label": "Official awards page / index", "official_program_url": "https://www.vldb.org/awards.html", "source_scope": "event-level", "citation_specificity": "year-specific-or-event-specific", "person_label": "Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, Joseph M. Hellerstein", "decade": "2020s", "featured": false, "search_blob": "Distributed GraphLab for machine learning in the cloud | VLDB 10-Year Best Paper Award | VLDB 10-Year Award | Recognizes database papers whose importance is clear over a ten-year horizon. | Yucheng Low Joseph Gonzalez Aapo Kyrola Danny Bickson Carlos Guestrin Joseph M. Hellerstein | machine learning systems distributed systems databases | Carnegie Mellon University University of California, Berkeley | Recognized a test-of-time systems paper that helped shape large-scale graph-parallel machine learning and cloud analytics infrastructure. | Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud | 2023 | 2020s" }, { "id": "aaai-classic-2020-junker", "year": 2020, "award_slug": "aaai-classic-paper-award", "person_names": [ "Ulrich Junker" ], "person_slugs": [ "ulrich-junker" ], "title": "Preferred explanations in over-constrained systems", "kind": "paper_award", "topics": [ "artificial intelligence", "constraint satisfaction", "preference reasoning" ], "institutions": [ "ILOG" ], "significance": "Recognized influential work on formalizing and computing user-preferred failure explanations in over-constrained problems.", "related_works": [ { "title": "QuickXPlain: Preferred Explanations and Relaxations for Over-Constrained Problems", "type": "paper", "year": 2004, "url": "https://aaai.org/Papers/AAAI/2004/AAAI04-027.pdf", "source_quality": "canonical" } ], "award_name": "AAAI Classic Paper", "award_category": "paper_award", "official_program_label": "Official awards page / index", "official_program_url": "https://aaai.org/about-aaai/aaai-awards/aaai-classic-paper-award/", "event_source_label": null, "event_source_url": null, "source_scope": "program-level", "citation_specificity": "not-year-specific", "person_label": "Ulrich Junker", "decade": "2020s", "featured": false, "search_blob": "Preferred explanations in over-constrained systems | AAAI Classic Paper Award | AAAI Classic Paper | Revisits AI conference papers whose importance becomes more visible over time. | Ulrich Junker | artificial intelligence constraint satisfaction preference reasoning | ILOG | Recognized influential work on formalizing and computing user-preferred failure explanations in over-constrained problems. | QuickXPlain: Preferred Explanations and Relaxations for Over-Constrained Problems | 2020 | 2020s" }, { "id": "turing-2020-compilers", "year": 2020, "award_slug": "turing-award", "person_names": [ "Alfred V. Aho", "Monica S. Lam", "Ravi Sethi", "Jeffrey D. Ullman" ], "person_slugs": [ "alfred-v-aho", "monica-s-lam", "ravi-sethi", "jeffrey-d-ullman" ], "title": "Compilers and education at scale", "kind": "laureate", "topics": [ "compilers", "programming languages", "computer science education" ], "institutions": [ "Columbia University", "Stanford University" ], "significance": "Honored the theory, textbooks, and compiler methods that trained generations of software engineers.", "related_works": [ { "title": "Compilers: Principles, Techniques, and Tools", "type": "book", "year": 1986, "url": "https://www.informit.com/store/compilers-principles-techniques-and-tools-9780321486813", "source_quality": "canonical" } ], "award_name": "Turing Award", "award_category": "major_award", "official_program_label": "Official awards page / index", "official_program_url": "https://awards.acm.org/turing", "event_source_label": null, "event_source_url": null, "source_scope": "program-level", "citation_specificity": "not-year-specific", "person_label": "Alfred V. Aho, Monica S. Lam, Ravi Sethi, Jeffrey D. Ullman", "decade": "2020s", "featured": false, "search_blob": "Compilers and education at scale | ACM A.M. Turing Award | Turing Award | Often described as the highest distinction in computer science, honoring lasting technical contributions across the field. | Alfred V. Aho Monica S. Lam Ravi Sethi Jeffrey D. 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