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X-ORIGINAL-URL:https://isg.ics.uci.edu
X-WR-CALDESC:Events for Information Systems Group
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TZID:America/Los_Angeles
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DTSTART:20260308T100000
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DTSTART:20261101T090000
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260130T130000
DTEND;TZID=America/Los_Angeles:20260130T140000
DTSTAMP:20260604T192401
CREATED:20260127T031809Z
LAST-MODIFIED:20260324T060539Z
UID:2302-1769778000-1769781600@isg.ics.uci.edu
SUMMARY:Andrew Chio: Building Resilient Systems for Critical Infrastructures: A Model-Driven and Data-Driven Approach
DESCRIPTION:Time & Location:\n\n\nFriday Jan 30\, 2026\, 1:00 PM – 2:00 PM\nDonald Bren Hall 3011\, ICS\, UC IrvineLunch will be provided. \n\n\nTitle:\nBuilding Resilient Systems for Critical Infrastructures: A Model-Driven and Data-Driven Approach\n\nAbstract:\nCritical infrastructures such as water\, power\, and buildings are large-scale distributed systems that serve as essential lifelines for communities worldwide. Today\, they face unprecedented resilience challenges affecting millions of people and cause billions in damage. In this talk\, I will present my research addressing fundamental computational challenges in these cyber-physical systems by combining model-driven approaches that encode physics and network constraints with data-driven techniques that learn from real-world patterns. I will demonstrate this across three critical infrastructure domains\, addressing key resilience challenges. First\, I present STEP\, a framework that solves the NP-hard sensor placement problem for detecting transient contamination events in stormwater networks. Second\, I introduce SEQUIN\, which leverages network science principles and physics-based optimization to identify sequential attack patterns. Third\, I showcase SmartSPEC\, an event-driven simulation framework that generates realistic synthetic human behavioral data by exploiting environmental semantics. Together\, these systems demonstrate how integrating models and data can address diverse resilience challenges for societal-scale systems.Bio:\nAndrew is a final PhD candidate in the Distributed Systems Middleware (DSM) Group at the University of California\, Irvine\, advised by Prof. Nalini Venkatasubramanian. He is also affiliated with the Los Alamos National Laboratory\, working with Dr. Russell Bent in the T-5 Theoretical Division Applied Mathematics and Plasma Physics Group. His research interests lie at the intersection of cyber-physical systems\, optimization\, middleware\, and artificial intelligence. His current work focuses on building systems that enhance the resilience of societal-scale cyber-physical systems such as electric power grids\, stormwater networks\, and smart buildings. His work has been published in top venues such as ACM/IEEE ICCPS\, IEEE PerCom\, ACM BuildSys\, and VLDB. He is the recipient of the NSF CPS Rising Stars Award in 2025\, the CPS-Week PhD Forum Best Poster Award in 2025\, the UC National Lab In-Residence Graduate Fellowship in 2022\, the ARCS Foundation Scholarship in 2022\, as well as the Best Paper Award in IEEE PerCom 2022. \n\n\n\n\n\n\n\n\n\n\n\n\n\nSponsors:
URL:https://isg.ics.uci.edu/event/andrew-chio-building-resilient-systems-for-critical-infrastructures-a-model-driven-and-data-driven-approach/
LOCATION:DBH 3011
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260206T130000
DTEND;TZID=America/Los_Angeles:20260206T140000
DTSTAMP:20260604T192401
CREATED:20260203T045046Z
LAST-MODIFIED:20260203T045046Z
UID:2306-1770382800-1770386400@isg.ics.uci.edu
SUMMARY:ISG seminar: "How grants and funding work in academia"
DESCRIPTION:[ISG] ISG seminar this Friday (Feb. 6): “How grants and funding work in academia” \nIn the ISG seminar this Friday (1 – 2 pm\, DBH 3011)\, the ISG faculty will give a talk on “How grants and funding work in academia.”  We will discuss how faculty write proposals\, receive awards\, and spend the funds to support students and research activities.  We will also emphasize the importance of PhD students participating in proposal writing.
URL:https://isg.ics.uci.edu/event/isg-seminar-how-grants-and-funding-work-in-academia/
LOCATION:DBH 3011
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260213T130000
DTEND;TZID=America/Los_Angeles:20260213T140000
DTSTAMP:20260604T192401
CREATED:20260119T063942Z
LAST-MODIFIED:20260119T063942Z
UID:2300-1770987600-1770991200@isg.ics.uci.edu
SUMMARY:Santosh Hegde (Couchbase\, Inc.): From Transactions to Intelligence: Evolution of Couchbase for AI
DESCRIPTION:The Department of Computer Science\, Information Systems Group\, UC Irvine  \nWELCOMES \nSantosh Hegde \nCouchbase\, Inc. \n  \nFrom Transactions to Intelligence: Evolution of Couchbase for AI \n  \n02/13/2026\, Friday\, 1:00 – 2:00 pm \nPlace: DBH 3011 \n  \nAbstract:  When Couchbase started\, it was built to solve a very specific problem\, namely the handling of high-performance\, low-latency transactional workloads at massive scale. Over time\, however\, customer needs have evolved from simply storing and retrieving data reliably at scale\, to analyzing it in real time\, and now to reasoning over it using AI. In this talk\, we will explore the new capabilities in the Couchbase platform as it transforms from a pure NoSQL transactional database into a unified platform that supports transactions\, analytics\, and AI workloads all on the same data foundation. \n  \nBio:  Santosh Hegde is an engineering leader with over 18 years of experience in the design and development of large-scale distributed database systems. He currently serves as Vice President of Engineering at Couchbase\, where his work focuses on the intersection of database systems\, analytics\, and artificial intelligence. Previously\, he has held senior engineering leadership roles at IBM Software Labs and Visa Inc. His technical interests include query processing\, database runtimes\, columnar data systems\, large-scale data ingestion\, and database-as-a-service architectures. Santosh has contributed to the development of multiple enterprise data platforms\, including Informix\, DB2 (LUW) and Trino . More recently\, his work has focused on the evolution of data platforms to support emerging AI-driven application patterns.
URL:https://isg.ics.uci.edu/event/santosh-hegde-couchbase-inc-from-transactions-to-intelligence-evolution-of-couchbase-for-ai/
LOCATION:DBH 3011
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260220T130000
DTEND;TZID=America/Los_Angeles:20260220T140000
DTSTAMP:20260604T192401
CREATED:20260217T234405Z
LAST-MODIFIED:20260217T234405Z
UID:2308-1771592400-1771596000@isg.ics.uci.edu
SUMMARY:Ashwin Gerard Colaco (UCI): Bringing Simulators Inside the Database: A Vision for Interactive Scientific Exploration
DESCRIPTION:Time & Location:\n\n\nFriday Feb 20\, 2026\, 1:00 PM – 2:00 PM\nDonald Bren Hall 3011\, ICS\, UC Irvine \nLunch will be provided. \n\nTitle:\nBringing Simulators Inside the Database: A Vision for Interactive Scientific Exploration\n\nAbstract:\nPhysics-based simulators are essential for scientific discovery and risk assessment\, powering what-if analyses for events like wildfires and hurricanes. Yet today’s workflow is fundamentally disconnected: analysts manually run simulations\, export results\, and load them into a database before any analysis can begin. This linear pipeline is slow\, brittle\, and especially limiting when the analysis itself reveals the need for new or refined simulation data.\n\n\n\n\n\n\n\n\nIn this talk\, I present a vision for GenIE\, a new database paradigm that makes the database simulation-aware by seamlessly integrating multiple simulators as first-class components. Designed as an extension to PostgreSQL\, GenIE dynamically invokes simulators based on the user’s query\, avoids generating irrelevant data\, reuses prior results\, and supports iterative refinement at interactive speeds. I illustrate GenIE’s potential through two use cases: wildfire smoke dispersion analysis using WRF-SFIRE and HYSPLIT\, and hurricane hazard assessment combining wind\, surge\, and flood models. Our preliminary results show how GenIE can transform these traditionally slow\, static analyses into responsive explorations by intelligently managing the trade-off between simulation accuracy and runtime. I conclude by outlining the data engineering challenges and future research directions in realizing the full potential of simulation-aware databases for next-generation scientific data management.\n\n\n\n\n\n\nBio:\nAshwin Gerard Colaco is a PhD candidate in Computer Science at UC Irvine\, advised by Sharad Mehrotra. His research focuses on the intersection of database systems and machine learning\, with a focus on cost-efficient inference and simulation-driven data exploration. He’s supported by the Hasso Plattner Institute Fellowship for scalable databases for ML research.
URL:https://isg.ics.uci.edu/event/ashwin-gerard-colaco-uci-bringing-simulators-inside-the-database-a-vision-for-interactive-scientific-exploration/
LOCATION:DBH 3011
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260227T130000
DTEND;TZID=America/Los_Angeles:20260227T140000
DTSTAMP:20260604T192401
CREATED:20260224T215802Z
LAST-MODIFIED:20260405T015004Z
UID:2318-1772197200-1772200800@isg.ics.uci.edu
SUMMARY:Zexin Li (UCR): Unified Full-stack Co-design for On-device Machine Learning
DESCRIPTION:For this week’s ISG seminar\, we’ll have an invited speaker: Zexin Li from University of California\, Riverside to give us a talk. \nTime & Location:\nFriday Feb 27\, 2026\, 1:00 PM – 2:00 PM\nDonald Bren Hall 3011\, ICS\, UC Irvine\n(Zoom link will be shared by request) \nLunch will be provided. \nTitle:\nUnified Full-stack Co-design for On-device Machine Learning \nAbstract:\nThe integration of advanced artificial intelligence into Cyber-Physical Systems (CPS)\, such as multirotor UAVs and wheeled mobile robots\, promises a future of edge intelligence. However\, deploying complex machine learning models directly onto real-time embedded systems presents significant challenges\, primarily due to strict timing constraints\, limited memory\, and dynamically changing environments. This talk presents a unified full-stack co-design approach to manage these complex\, multidimensional trade-offs. \nBio:\nZexin Li is a Ph.D. student at the University of California\, Riverside\, advised by Cong Liu. His research interests lie in interdisciplinary fields of real-time embedded systems and on-device machine learning. \nVolunteer:\nKeming Li \nSponsors:
URL:https://isg.ics.uci.edu/event/zexin-li-ucr-unified-full-stack-co-design-for-on-device-machine-learning/
LOCATION:DBH 3011
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260306T130000
DTEND;TZID=America/Los_Angeles:20260306T140000
DTSTAMP:20260604T192401
CREATED:20260219T064700Z
LAST-MODIFIED:20260219T065044Z
UID:2311-1772802000-1772805600@isg.ics.uci.edu
SUMMARY:Zheng LUO (UCLA):  Generating Join Trees for Yannakakis Algorithm
DESCRIPTION:ISG seminar on March 6\, Friday\, 1 – 2 pm\, DBH 3011 \nTitle: Generating Join Trees for Yannakakis Algorithm \nAbstract:\nMost research on query optimization has centered on binary join algorithms like hash join and sort-merge join. However\, recent years have seen growing interest in theoretically optimal algorithms\, notably Yannakakis algorithm. These algorithms require new optimization techniques\, as they rely on join trees where each node represents a relation\, very different from the operator trees for binary joins.\nOur recent theoretical work proposes three approaches to constructing join trees for Alpha-acyclic queries:\n(1) an algorithm to enumerate all join trees\, which forms the basis of a cost-based optimizer;\n(2) a 1-shot approach to construct a unique shallowest join tree for any Berge-acyclic query\, thus enabling parallel execution of large join queries;\n(3) a simple algorithm that converts any connected left-deep linear plan of a Gamma-acyclic query into a join tree\, allowing reuse of existing optimizers developed for binary joins.\nIn this talk\, we will also discuss how the theoretical results can turbocharge query processing in modern database systems. \nBio:\nZheng LUO is a Ph.D. student at the University of California\, Los Angeles (UCLA)\, advised by Prof. Remy WANG.\nHis research interests are twofold\, spanning from theory to systems.\n(1) His current work centers on the theoretical aspects of query optimization in relational databases by examining the algorithms and data structures that improve the efficiency of query processing;\n(2) He is also exploring ways to put theory into practice by implementing theoretical results and integrating them into systems.
URL:https://isg.ics.uci.edu/event/yannakakis/
LOCATION:DBH 3011
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260417T130000
DTEND;TZID=America/Los_Angeles:20260417T140000
DTSTAMP:20260604T192401
CREATED:20260414T044342Z
LAST-MODIFIED:20260414T044342Z
UID:2397-1776430800-1776434400@isg.ics.uci.edu
SUMMARY:Sarah Asad: Teaching Data Science and AI/ML to Diverse Learners Using Apache Texera: An Experience Report
DESCRIPTION:We’ll have Sarah present her work for this week’s ISG seminar. \nTime & Location: \nFriday April 17\, 2026\, 1:00 PM – 2:00 PM\nDonald Bren Hall 3011\, ICS\, UC Irvine \nZoom: \nhttps://uci.zoom.us/j/95509222811?pwd=2V8Hnx71iP6dyfNsEPoo97NUfCFWTo.1\n\nLunch will be provided. \nTitle \nTeaching Data Science and AI/ML to Diverse Learners Using Apache Texera: An Experience Report \nAbstract \nThis talk reports on our experiences teaching data science and AI/ML through a series of hands-on programs to learners ranging from high school to graduate students and non-STEM faculty. The programs are taught using Texera\, an open-source system for collaborative data science and AI/ML using GUI-based workflows. A uniqueness of these programs is that they did not require participants to have prior coding skills. We describe the program-preparation process\, curriculum structure\, classroom experience\, and feedback collected from participants. We summarize our insights regarding student engagement\, effectiveness of interactive and collaborative learning environments\, and practical considerations for designing accessible data science programs for learners with diverse backgrounds. \nBio \nSarah Asad is a second-year PhD student in the Computer Science Department at UC Irvine\, with research interests in data systems\, data science\, and big data analysis. She is supervised by Prof. Chen Li.
URL:https://isg.ics.uci.edu/event/sarah-asad-teaching-data-science-and-ai-ml-to-diverse-learners-using-apache-texera-an-experience-report/
LOCATION:DBH 3011
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260424T130000
DTEND;TZID=America/Los_Angeles:20260424T140000
DTSTAMP:20260604T192401
CREATED:20260421T003909Z
LAST-MODIFIED:20260421T060244Z
UID:2422-1777035600-1777039200@isg.ics.uci.edu
SUMMARY:Prof. Eduard Dragut (Temple University): Toward Scalable Knowledge Extraction with Weak Supervision and Large Language Models
DESCRIPTION:Friday April 24\, 2026\, 1:00 PM – 2:00 PM\nDonald Bren Hall 3011\, ICS\, UC Irvine \nZoom:\nhttps://uci.zoom.us/j/95509222811?pwd=2V8Hnx71iP6dyfNsEPoo97NUfCFWTo.1 \nLunch will be provided. \nTitle: Toward Scalable Knowledge Extraction with Weak Supervision and Large Language Models \nAbstract: Information extraction is a foundational capability for transforming unstructured text into structured knowledge\, enabling downstream applications such as knowledge graph construction\, semantic search\, question answering\, and scientific discovery. However\, building high-quality extraction systems traditionally depends on large manually annotated datasets\, which are costly to create and often impractical in specialized domains. In this talk\, I will present recent advances toward scalable information extraction under limited supervision. I will discuss methods for improving the quality of weakly supervised training data through automatic label cleaning\, show how richer benchmarks over full scientific documents expose new challenges for scientific information extraction beyond simplified abstract-level settings\, and demonstrate how large language models can be leveraged in many-shot in-context learning regimes to perform competitive named entity recognition and generate high-quality annotations for low-resource domains. Together\, these results suggest a promising path toward scalable knowledge extraction pipelines that reduce reliance on expensive manual annotation while improving the robustness and adaptability of systems used to build next-generation knowledge graphs and AI applications. \nBio: Eduard Dragut is a Professor in the Department of Computer and Information Sciences at Temple University. He is a senior member of the IEEE. He received his Ph.D. in Computer Science from the University of Illinois at Chicago. His research focuses on data management\, information retrieval\, and applied artificial intelligence\, with an emphasis on building scalable systems for extracting and integrating knowledge from large and heterogeneous data sources. He also pursues interdisciplinary AI projects for social good\, including work on assistive technologies such as augmentative and alternative communication (AAC) and AI-driven tools for knowledge discovery. He has published widely in leading venues in databases\, natural language processing\, and data mining.
URL:https://isg.ics.uci.edu/event/prof-eduard-dragut-temple-university-toward-scalable-knowledge-extraction-with-weak-supervision-and-large-language-models/
LOCATION:DBH 3011
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260501T130000
DTEND;TZID=America/Los_Angeles:20260501T140000
DTSTAMP:20260604T192401
CREATED:20260429T054607Z
LAST-MODIFIED:20260429T054607Z
UID:2426-1777640400-1777644000@isg.ics.uci.edu
SUMMARY:Yinan & Juncheng ICDE Practice Talk
DESCRIPTION:We’ll have Yinan & Juncheng present their ICDE works for this week’s ISG Seminar. This will be a shared session. \nTime & Location: \nFriday May 1\, 2026\, 1:00 PM – 2:00 PM\nDonald Bren Hall 3011\, ICS\, UC Irvine \nZoom: \nhttps://uci.zoom.us/j/95509222811?pwd=2V8Hnx71iP6dyfNsEPoo97NUfCFWTo.1\n\nLunch will be provided. \n———————————————————————————————————————— \nSpeaker \nYinan Zhou \nTitle \nSpendableStore: A UTXO-based Decentralized Data Store \nAbstract \nThe literature on blockchain-based databases is divided into permissioned blockchains and permissionless account based blockchains. However\, the former is not fully decentralized\, and the latter suffers from challenges in scalability and practicality. We propose SpendableStore\, a hybrid on/off-chain database that operates on top of permissionless UTXO-based blockchains as a novel approach to the problem of data decentralization. Our design integrates atomic data units into individual UTXOs to create a new blockchain concept called Spendable Data Objects that perform traditional CRUD operations. The integrity\, immutability\, and ownership of these Spendable Data Objects are safeguarded directly by the blockchain peer nodes\, thus constraining the power of database administrators to achieve true data decentralization. We further support database transactions and propose an isolation mechanism called Future Now Snapshot Isolation to reason about transactional correctness in SpendableStore. We performed experiments on a major blockchain’s Mainnet and observed up to 16x better throughput compared to a state-of-the-art blockchain-based database. \n———————————————————————————————————————— \nSpeaker \nJuncheng Fang \nTitle \nImmortalChopper: Real-Time and Resilient Distributed Transactions in the Edge-Cloud \nAbstract \nEmerging applications in the areas of real-time Internet of Things (IoT) and edge technologies require fast processing and response times. This motivates the utilization of edge nodes for storing and processing data close to the user. In settings with a vast number of edge nodes\, the state of the data is distributed across a large number of edge nodes. This makes it expensive to perform distributed transactions as these transactions would span edge nodes that are connected via less reliable and relatively slow network infrastructure. It is prohibitive to use existing protocols like 2PC that require many rounds of communication across participants.\nIn this talk\, we discuss ImmortalChopper\, a distributed transaction processing protocol designed for the edge-cloud environment. The goal of ImmortalChopper is to provide One-Node Response (1n-Response)\, a guarantee of transaction commitment by contacting only one node without waiting for coordination with the other nodes. To achieve this\, we build on and extend the literature of transaction chopping and lazy replication. However\, combining transaction chopping and lazy replication without special care can lead to transactions operating on a stale state and potentially violating serializability. We present a new transaction chopping theory called ChopperGraph that integrates the notion of lazy replication and speculative execution. It ensures 1n-Response while preserving serializability. \nBio \nJuncheng Fang is a 5th-year Ph.D. candidate in the Computer Science Department at UC Irvine\, supervised by Prof. Faisal Nawab. His current research focuses on distributed transaction processing\, specifically improving the concurrency by exploiting the semantics of transactions. \n————————————————————————————————————————
URL:https://isg.ics.uci.edu/event/yinan-juncheng-icde-practice-talk/
LOCATION:DBH 3011
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260508T130000
DTEND;TZID=America/Los_Angeles:20260508T140000
DTSTAMP:20260604T192401
CREATED:20260505T192616Z
LAST-MODIFIED:20260505T192616Z
UID:2430-1778245200-1778248800@isg.ics.uci.edu
SUMMARY:Pratyoy (UCI): SmartRabbit An Interactive Query Processor
DESCRIPTION:For this week’s ISG seminar\, Pratyoy will do his SIGMOD practice talk.\n\n\nTime & Location:\n\n\nFriday May 8\, 2026\, 1:00 PM – 2:00 PM\nDonald Bren Hall 3011\, ICS\, UC Irvine\n\n\nTitle: SmartRabbit: An Interactive Query Processor.\n\nAbstract:Traditional relational database systems optimize analytical queries to minimize their end-to-end latency. The resulting optimal plans are usually blocking\, forcing users to wait until full query completion before seeing any results. This execution model precludes interactivity\, i.e.\, users cannot observe partial results or gain early insights for long-running queries. Query optimizers rarely choose plans that promote interactivity\, since such plans either incur prohibitively large latencies or involve operators for which interactive alternatives are unavailable. We introduce a novel interactive query processor SmartRabbit that promotes interactivity of answers while matching the end-to-end latency of blocking execution plans. We achieve this by first designing a plan optimized for interactivity for a given query\, and then simultaneously executing this plan alongside a traditional blocking plan. The two executions are carefully synchronized to maintain the correct order of answers and prevent duplicates. We implement SmartRabbit in AsterixDB and show that SmartRabbit consistently delivers early and continuous results across various analytical queries\, data scales\, and parallel (multi-node\, multi-partition) system instances\, while matching the latencies of the standalone blocking executions.\n\nBio: Pratyoy is a 4th year PhD student under Professor Sharad Mehrotra. His research focuses on query optimization and query execution with specific interests in adaptive\, interactive and progressive query optimization. Pratyoy had previously interned in the query optimization team of Amazon Redshift and was a Software Engineer at Microsoft before joining UC Irvine.\n\n\nZoom:\nhttps://uci.zoom.us/j/95509222811?pwd=2V8Hnx71iP6dyfNsEPoo97NUfCFWTo.1\n\nLunch will be provided.
URL:https://isg.ics.uci.edu/event/pratyoy-uci-smartrabbit-an-interactive-query-processor/
LOCATION:DBH 3011
END:VEVENT
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