SCS Recruiting Seminar: Anand Iyer

Event Details
  • Date/Time:
    • Thursday April 4, 2019 - Friday April 5, 2019
      11:00 am - 11:59 am
  • Location: KACB 1116W
  • Phone:
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Tess Malone, Communications Officer


Summary Sentence: Scalable Systems for Large-Scale Dynamic Connected Data Processing

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  • Anand Iyer Anand Iyer

TITLE: Scalable Systems for Large-Scale Dynamic Connected Data Processing


As the proliferation of sensors rapidly make the Internet-of-Things (IoT) a reality, the devices and sensors in this ecosystem —such as smartphones, video cameras, home automation systems, and autonomous vehicles — constantly map out the real-world producing unprecedented amounts of connected data that captures complex and diverse relations. Unfortunately, existing big data processing and machine learning frameworks are ill-suited for analyzing such dynamic connected data and face several challenges when employed for this purpose.
In this talk, I will present my research that focuses on building scalable systems for dynamic connected data processing. I will discuss simple abstractions that make it easy to operate on such data, efficient data structures for state management, and computation models that reduce redundant work. I will also describe how bridging theory and practice with algorithms and techniques that leverage approximation and streaming theory can significantly speed up computations. The systems I have built achieve more than an order of magnitude improvement over the state-of-the-art and are currently under evaluation in the industry for real-world deployments. I will end the talk with my vision for building the next generation data intensive systems that incorporates both the cloud and the edge.



Anand Iyer is a Ph.D. candidate at the University of California, Berkeley advised by Professor Ion Stoica. His research interests are in cloud computing, systems for big data analytics, and mobile systems with a current focus on enabling efficient analysis and machine learning on large-scale dynamic, connected data. He is a recipient of the best paper award at SIGMOD GRADES-NDA 2018 for his work on approximate graph analytics. Before coming to Berkeley, he was a member of the mobility, networking, and systems group at Microsoft Research India. He completed his M.S at the University of Texas at Austin.  


Additional Information

In Campus Calendar

College of Computing, School of Computer Science

Invited Audience
Faculty/Staff, Postdoc, Public, Graduate students, Undergraduate students
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  • Created By: Tess Malone
  • Workflow Status: Published
  • Created On: Mar 21, 2019 - 1:29pm
  • Last Updated: Mar 21, 2019 - 1:30pm