Data Systems Seminars (2019-2020)

The Data Systems Seminar Series provides a forum for presentation and discussion of interesting and current database issues. It complements our internal database meetings by bringing in external colleagues. The talks that are scheduled for this year are listed below.

The talks are usually held on a Monday at 10:30 am in room DC 1302. Exceptions are flagged.

We will try to post the presentation notes, whenever that is possible. Please click on the presentation title to access these notes.


The Database Seminar Series is supported by


Guoliang Li
Marco Serafini
Saif Mohammad
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David Doermann
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George Fletcher
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-

10 September 2019, 10:30 am, DC 1302

Title: AI-Native Database notes video
Speaker: Guoliang Li, Tsinghua University
Abstract:

In big data era, database systems face three challenges. Firstly, the traditional heuristics-based optimization techniques (e.g., cost estimation, join order selection, knob tuning) cannot meet the high-performance requirement for large-scale data, various applications and diversified data. We can design learning-based techniques to make database more intelligent. Secondly, many database applications require to use AI algorithms, e.g., image search in database. We can embed AI algorithms into database, utilize database techniques to accelerate AI algorithms, and provide AI capability inside databases. Thirdly, traditional databases focus on using general hardware (e.g., CPU), but cannot fully utilize new hardware (e.g., ARM, AI chips). Moreover, besides relational model, we can utilize tensor model to accelerate AI operations. Thus, we need to design new techniques to make full use of new hardware. 

To address these challenges, we design an AI-native database. On one hand, we integrate AI techniques into databases to provide self-configuring, self-optimizing, self-healing, self-protecting and self-inspecting capabilities for databases. On the other hand, we can enable databases to provide AI capabilities using declarative languages, in order to lower the barrier of using AI.  

In this talk, I will introduce the five levels of AI-native databases and provide the open challenges of designing an AI-native database. I will also take automatic database knob tuning, deep reinforcement learning based optimizer, machine-learning based cardinality estimation, automatic index/view advisor as examples to showcase the superiority of AI-native databases. 

 

Guoliang Li is a tenured full Professor of Department of Computer Science, Tsinghua University, Beijing, China. His research interests include AI-native database, big data analytics and mining, crowdsourced data management, big spatio-temporal data analytics, large-scale data cleaning and integration. He has published more than 100 papers in premier conferences and journals, such as SIGMOD, VLDB, ICDE, SIGKDD, SIGIR, TODS, VLDB Journal, and TKDE. He is a PC co-chair of DASFAA 2019, WAIM 2014, WebDB 2014, and NDBC 2016. He servers as associate editor for IEEE Transactions and Data Engineering, VLDB Journal, ACM Transaction on Data Science, IEEE Data Engineering Bulletin. He has regularly served as the (senior) PC members of many premier conferences, such as SIGMOD, VLDB, KDD, ICDE, WWW, IJCAI, and AAAI. His papers have been cited more than 6000 times. He got several best paper awards in top conferences, such as CIKM 2017 best paper award, ICDE 2018 best paper candidate, KDD 2018 best paper candidate, DASFAA 2014 best paper runner-up, APWeb 2014 best paper award, etc. He received VLDB Early Research Contribution Award 2017, IEEE TCDE Early Career Award 2014, The National Youth Talent Support Program 2017, ChangJiang Young Scholar 2016, NSFC Excellent Young Scholars Award 2014, CCF Young Scientist 2014.

25 October 2019, 2:00 pm, DC 1302 (Please note the unusual day and time)

Title: TBDnotesvideo
Speaker: Marco Serafini, University of Massachusetts Amherst
Abstract: TBD
Bio:

TBD

28 October 2019, 10:30 am, DC 1302 

Title: The Search for Emotions, Creativity, and Fairness in Language notesvideo
Speaker: Saif F. Mohammad, National Research Council of Canada
Abstract: Emotions are central to human experience, creativity, and behavior. They are crucial for organizing meaning and reasoning about the world we live in. They are ubiquitous and everyday, yet complex and nuanced. In this talk, I will describe our work on the search for emotions in language -- by humans (through data annotation projects) and by machines (in automatic emotion detection systems). I will outline ways in which emotions can be represented, challenges in obtaining reliable annotations, and approaches that lead to high-quality annotations. The lexicons thus created have entries for tens of thousands of terms. They provide fine-grained scores for basic emotions as well as for valence, arousal, and dominance (argued by some to be the core dimensions of meaning). They have wide-ranging applications in natural language processing, psychology, social sciences, digital humanities, and computational creativity. I will highlight some of the applications we have explored in literary analysis and automatic text-based music generation. I will also discuss new sentiment analysis tasks such as inferring fine-grained emotion intensity and stance from tweets, as well as detecting emotions evoked by art. I will conclude with work on quantifying biases in the way language is used and the impact of such biases on automatic emotion detection systems. From social media to home assistants, from privacy concerns to neuro-cognitive persuasion, never has natural language processing been more influential, more fraught with controversy, and more entrenched in everyday life. Thus as a community, we are uniquely positioned to make substantial impact by building applications that are not only compelling and creative but also facilitators of social equity and fairness.
Bio: Dr. Saif M. Mohammad is Senior Research Scientist at the National Research Council Canada (NRC). He received his Ph.D. in Computer Science from the University of Toronto. Before joining NRC, Saif was a Research Associate at the Institute of Advanced Computer Studies at the University of Maryland, College Park. His research interests are in Emotion and Sentiment Analysis, Computational Creativity, Psycholinguistics, Fairness in Language, and Information Visualization. Saif has served as General Chair for the Canada--UK Symposium on Ethics in AI, co-chair of SemEval (the largest platform for semantic evaluations), and co-organizer of WASSA (a sentiment analysis workshop). He has also served as the area chair for ACL, NAACL, and EMNLP in Sentiment Analysis and Fairness and Bias in NLP. His work on emotions has garnered media attention, with articles in Time, Washington Post, Slashdot, LiveScience, The Physics arXiv Blog, PC World, Popular Science, etc.

18 November 2019, 10:30 pm, DC 1304 (Please note room change)

Title:

TBD notesvideo

Speaker: TBD
Abstract: TBD
Bio: TBD

2 December 2019, 10:30 am, DC 1302

Title: The Evolving Challenges of Media Forensics in a GAN Worldnotes
Speaker: David Doermann, University at Buffalo
Abstract:

TBD

Bio: TBD

13 January 2030, 10:30 am, DC 1302

Title:

TBD notesvideo

Speaker: TBD
Abstract:

TBD

Bio: TBD

13 April 2020, 10:30 am, DC 1302

Title:

TBD notesvideo

Speaker: George Fletcher, Eindhoven University of Technology
Abstract: TBD
Bio: George Fletcher (PhD, Indiana University Bloomington) is an associate professor of computer science and chair of the Database Group at Eindhoven University of Technology, the Netherlands. His research interests span query language design and engineering, foundations of databases, and data integration. His current focus is on management of massive graphs such as social networks and knowledge graphs. He was a co-organizer of the EDBT Summer School on Graph Data Management (2015) and is currently a member of the LDBC Graph Query Language Standardization Task Force and Property Graph Schema Language Standardization Task Force. His other recent activities include co-organizing an NII Shonan seminar on Graph Database Systems (2018), chairing the Demo PC for EDBT 2020, and serving on the program committees of SIGMOD, VLDB, ISWC, ICDE, and IJCAI.

25 May 2020, 10:30 am, DC 1302

Title: TBD notesvideo
Speaker: TBD
Abstract:  
Bio:  

22 June 2020, 10:30 am, DC 1302

Title: TBD notesvideo
Speaker: TBD
Abstract: TBD
Bio: TBD