Advanced Data Analytics (ADA) Lab

Introduction

As the scale, complexity, and variety of data grows (aka Big Data), the use of machine learning (ML) and artificial intelligence (AI) techniques to make sense of, and interact with, such data — collectively called advanced data analytics — is increasingly critical for data-driven applications in the enterprise, Web, science, and other domains. Alas, building and deploying ML/AI-powered data analytics applications still involves far too many bottlenecks that slow down the lifecycle of such applications, raise costs, frustrate many application users, and in some cases, make high-quality data-driven decision making almost impossible.

The mission of the ADALab is to democratize advanced data analytics by making it dramatically easier, faster, and cheaper to build and deploy ML/AI-powered data analytics applications throughout their lifecycle.

We are a part of the Department of Computer Science and Engineering (CSE) at the University of California, San Diego (UCSD). We are members of CSE's Database Lab and affiliate members of the AI Group and CNS.

Overview of Our Research

The ADA lifecycle typically revolves around data scientists or ML engineers. Based on conversations with dozens of such data-related professionals, we abstract the ADA lifecyle as follows. After identifying the tasks where ML/AI might benefit their application in terms of business impact or scientific insights, the data scientist steers three main processes, as illustrated below:

  • Data Sourcing: Identify, collect, and organize data in to a form that can be used to train ML models.

  • Model Building: Perform model selection with the data to obtain desired ML models.

  • Model Deployment: Integrate trained ML models with the application and oversee lifecycle.

 

The ADALab's approach to democratizing advanced data analytics involves accelerating the ADA lifecyle by removing bottlenecks for both the efficiency of the systems and algorithms involved and the productivity of the data scientists involved.

Towards this grand goal, we synthesize and innovate upon the fields of data management, ML/AI, systems, and human-computer interaction. Our projects target all parts of the ADA lifecycle, and our work spans the whole gamut of building new data systems, algorithms, empirical analysis, and theoretical analysis. All of our systems are released as open source software.

We also enjoy interacting with, and learning from, practitioners — data scientists, ML/software engineers, and domain scientists — and working with them to help them adopt our systems and ideas.

The list of current ADALab projects is here: Projects.

The list of ADALab publications is here: Publications.

Recent ADALab News

  • 10/17: The Hamlet++ paper is accepted to VLDB 2018. Congrats, Vraj!

  • 10/17: Anthony and Supun present short talks about their research at the Fall’17 CNS Research Review.

  • 10/17: ADALab webpage goes live!

Full list of lab news items here: News.

Members

Faculty

 

Arun Kumar
Assistant Professor, CSE
Email: arunkk [at] eng [dot] ucsd [dot] edu
Office: CSE 3218

Graduate Students

 

Lingjiao Chen
PhD at UW-Madison
(Co-advised by Paris Koutris)
Email: lchen1 [at] wisc [dot] edu

 

Supun Nakandala
PhD, CSE
Email: snakanda [at] eng [dot] ucsd [dot] edu
Office: CSE 3232

 

Vraj Shah
MS, CSE
Email: vps002 [at] eng [dot] ucsd [dot] edu
Office: CSE 3230

 

Anthony Thomas
MS, CSE
Email: ahthomas [at] eng [dot] ucsd [dot] edu
Office: CSE 3230

Undergraduate Students

 

Yaobang Deng
BS, CSE
Email: yad025 [at] ucsd [dot] edu

 

Side Li
BS, CSE
Email: s7li [at] eng [dot] ucsd [dot] edu

Alumni

  • Mingyang Wang. MS, CSE, UCSD, 2017.

Sponsors

We thank the following organizations for their generous support of our research. Any findings or opinions expressed in our research publications or articles are our own and do not necessarily reflect the views of any of these organizations.

 

About our Lab's Name

Apart from being a convenient acronym, it is also a tribute to Ada Lovelace, widely regarded as the first computer programmer. This tribute is part of our lab's commitment to help foster a diverse and inclusive community in computing, as enshrined in the UCSD Principles of Community, for people from all backgrounds, including women, under-represented minorities, and LGBTQ+ people.