About

I'm a fourth year PhD student of Computer Science in University of Illinois at Urbana Champaign. I work with Prof. Indranil Gupta and Distributed Protocols Research Group (DPRG). My research mainly revolves around all aspects of distributed systems and application. Currently I'm working on improving elasticity of stream processing systems. See my CV and list of publications here.

Education

I started my study in University of Illinois at Urbana Champaign since 2009 and received BS in Math and Computer Science in 2013, followed by a Master Degree in Computer Science in 2015. As I enjoy some of my ongoing projects (besides sweet corns), I'm continuing for a PhD starting from 2015.

Publication

[10/2018] Kalim, Faria, Le Xu, Sharanya Bathey, Richa Meherwal, Indranil Gupta. "Henge: Intent-driven Multi-Tenant Stream Processing" SoCC 2018. pdf pptx technical report

An intent-driven mechanism to unify user-defined performance objectives and improve cluster-wise overall satisfaction in multi-tenant stream processing system.

[06/2018] Mai, Luo, et al. "Chi: a scalable and programmable control plane for distributed stream processing systems." VLDB 2018. pdf pptx

A generalized control plane and control message design for stream processing systems that allows a wide range of functionalities being implemented and efficiently executed.

[04/2018] Ghosh, Mainak, et al. "Popular is Cheaper: Curtailing Memory Costs in Interactive Analytics Engines." EuroSys 2018. pdf pptx technical report

Replication and routing strategy designed for popularity-driven workloads for interactive analytics engines.

[08/2017] Kim, Mijung, et al. "Sparkle: Optimizing Spark for large memory machines and analytics." 2017 SoCC (poster track). (2017). pdf

A shared-memory shuffle engine and off-heap memory store that optimize Spark in the scale-up setting.

[04/2016] Xu, Le, Boyang Peng, and Indranil Gupta. "Stela: Enabling stream processing systems to scale-in and scale-out on-demand." IC2E, 2016. pdf pptx

Exploring topology-aware algorithms for migrating real time tasks to optimize distributed stream processing system throughput during cluster configuration changes.My M.S. thesis was also based on this project.

[05/2015] Xu, Le. "Stela: on-demand elasticity in distributed data stream processing systems." Master Thesis pdf

[03/2015] Wang, Wenting, Le Xu, and Indranil Gupta. "Scale Up vs. Scale Out in Cloud Storage and Graph Processing Systems." IWCA 2015pdf pptx

Constructing cluster's linear pricing model for both scale up and scale out cluster based on pricing scheme provided by major cloud providers.

Industry Experiences

Microsoft: May 2017 - Aug 2017

Supporting efficient and flexible online reconfiguration in stream processing engine

Hewlett Packard Labs: May 2016 - Aug 2016

Achieving performance objectives of Spark: Scale-out or Scale up?

Salesforce, Service Cloud Performance Team: May 2015 - Aug 2015

Platform benchmark

Yahoo! Sunnyvale: Cloud Services and Organization Team: May 2014 - Aug 2014

Server log-processing framework for server log retrieval and analysis (Pig, Hive and Oozie)

Teaching

Teaching Assistant

  • Coursera: Cloud Application Concepts: Spring 2015, Spring 2016
  • CS 425: Distributed Systems: Fall 2014, Spring 2014

Honors, Memberships, Awards

  • 2016: David J. Kuck Outstanding M.S. Thesis Award
  • 2015: Grace Hopper Celebration Travel Fund
  • 2015: Conference Travel Grant
  • 2015: Outstanding Teaching Assistant
  • 2011: Member of PI MU EPSILON: National Math Honor Society
  • 2010: Edmund J James Scholar

Cloud-free

  • Sometimes I blah about random thoughts. ATTENTION: you are about to enter a cloud-free zone!
  • Occationally I tweet (or retweet) about things (not entirely cloud-free).