Shadi A. Noghabi

Ph.D. Candidate
Department of Computer Science
University of Illinois at Urbana-Champaign

I am currently a Ph.D. candidate in the Department of Computer Science at the University of Illinois at Urbana-Champaign. I work conjunctly with Prof. Roy H. Campbell in the Systems Research Group (SRG) and Prof. Indranil Gupta in the Distributed Protocols Research Group (DPRG).

My research focuses on Distributed Systems, Cloud Computing and Big Data. I am currently working on geo-distributed large-scale objects stores, and stream processing systems. You can find my CV here.

Email: abdolla2 [at] illinois [dot] edu

My profiles in social media:

Education

  • present University of Illinois at Urbana-Champaign

    PhD in Computer Science 2013 - present
  • 2013 Sharif University of Technology

    Bachelors in Computer Engineering
    2009 - 2013

Publications


SIGMOD

2016

Shadi A. Noghabi, Sriram Subramanian, Priyesh Narayanan Sivabalan Narayanan, Gopalakrishna Holla, Mammad Zadeh, Tianwei Li Indranil Gupta, Roy H. Campbell, Ambry: LinkedIn’s Scalable Geo-Distributed Object Store


VLDB

2016

Shadi A. Noghabi, Roy Campbell, Indranil Gupta Building a Scalable Distributed Online Media Processing Environment, PhD Workshop


ANCS

2016

Sayed Hadi Hashemi, Shadi A. Noghabi, John Bellessa, Roy Campbell, Toward Fabric: A Middleware Implementing High-level Description Languages on a Fabric-like Network


PDSW

2013

Mayank Pundir, John Bellessa, Shadi A. Noghabi, Cristina L. Abad, Roy H. Campbell, Towards Enabling Cooperation Between Scheduler and Storage Layer to Improve Job Performance


Technical Report

2015

Shadi A. Noghabi, Read Sprabery, John Bellessa, Mohammad Ahmad, Indranil Gupta, Roy H. Campbell, Real Time Adaptive Profiling in Storm Topologies


Technical Report

2014

Mayank Pundir, Cristina L. Abad, Shadi A. Noghabi, Indranil Gupta, John Bellessa, Roy H. Campbell, Using Context to Improve Performance of Cloud Stacks


Technical Report

2012

Shadi A. Noghabi, Sahel Sharifi-Moghadam, Reza Entezari-Maleki, Ali Movaghar, New Model for Grid Task Scheduling Based on Priorities and Deadlines


Technical Report

2012

Shadi A. Noghabi, Sahel Sharifi-Moghadam, Reza Entezari-Maleki, Ali Movaghar, A Communication Cost Aware Scheduling Algorithm for Heterogeneous Environments

Honors and Awards

  • Recipient of SIGMOD Student Grant, SIGMOD, 2016.
  • Recipient of Grad Cohort Workshop - CRA Women Scholorship, CRA-W, 2016
  • Recipient of ANCS Student Grant, ANCS, 2016
  • Selected to join the Honor Society of Phi Kappa Phi (the nation’s oldest, largest, and most selective all-discipline academic honor society) for 3 consecutive years, 2014-2016
  • Selected as "Active Member" in Women in Computer Science (WCS) association, UIUC, 2015
  • Ranked in top 5% based on Cumulative GPA among about 120 students of the department. Class of 2013 students. Recipient of Honorary Admission for Graduate Study, Department of Computer Engineering, Sharif University of Technology, 2009-2013
  • Ranked 7th in Nationwide Graduate Entrance Qualification Exam (Konkoor for graduate study) among more than 17,000 participants, Iran, 2012
  • Ranked 297th in Nationwide University Entrance Exam (Konkoor) among more than 200,000 participants, Iran, 2009

Experience

Research Assistant

University of Illinois at Urbana-Champaign
Urbana, IL
Aug 2013 - present

I have been researching in the area of Distributed Systems and Cloud computing under Prof. Roy H. Campbell and Prof. Indranil Gupta at University of Illinois at Urbana-Champaign. My main interests are in Big Data Storage and Processing systems, specifically Stream Processing systems.


Software Engineering Intern

LinkedIn Corp
Mountain View, CA
May - Aug 2015

In this role I was working with the Apache Samza team at LinkedIn. My project was on Auto-scaling Samza adaptively on the fly. The code, design documents, and evaluation of this work can be found in SAMZA-719 and SAMZA-755 tickets. In this project I had the chance to work with a top-notch Apache project with a large community. I gained many valuable experiences including team-work, high quality coding, and learning how to build a system that works in large scale.


Software Engineering Intern

LinkedIn Corp
Mountain View, CA
May - Aug 2014

This role was great experience for me to work as a team, and work on a large distributed system. I was working on LinkedIn's blob store, i.e., a distributed storage of blobs (any media content such as images). My responsibilities included re-balancing the system with minimum data movement. The time I joined the team had only 3 other engineers and I had a chance to have a big impact on the project. Currently, the team is roughly 10 people, and the system is used fully in production with more than hounders of millions of users. I am currently working with the team on a paper of the system.


Teaching Assistant

Cloud Computing Applications
Coursera
Jul - Nov 2015

I have been a Teaching assistant for a Coursera course on Big Data with more than 9,000 students. My responsibilities involved designing tutorials, machine problems with automated grading, and quizes, along with helping students in discussion forums.

Projects

Ambry

May'14 - present

Ambry: LinkedIn's Scalable Geo-Distributed Object Store, Collaboration between LinkedIn and University of Illinois at Urbana-Champaign, Under Prof. Roy Campbell and Prof. Indy Gupta.

The infrastructure beneath a worldwide social network has to serve billions of variable-sized media objects such as photos, videos, and audios, continually. These objects must be stored and served with low latency and high throughput by a system that is geo-distributed, highly scalable, and load-balanced. To meet these goals we developed Ambry, a production-quality system for storing large immutable data. Ambry has been running in LinkedIn's production environment for the past 2 years, serving up to 10K requests per second across more than 400 million users.


Toward Fabric (ToF)

Jan'15 - present

Towards Fabric: A Middleware Implementing High-level Description Languages on a Fabric-like Network, System Research Group, Under Prof. Roy Campbell

Current SDN technologies provide powerful and flexible APIs, but can be unreasonably complex for implementing nontrivial network control logic, and very error-prone. We have developing a middleware layer for implementing policies and behaviors from high-level network descriptions on top of a more structured network (i.e., Fabric network). Based on our results, we reach near linear scalability with respect to the number of addresses routed over the network, all while introducing minimal performance overhead and requiring no changes to packet structure.


Adaptive Storm

Jan'14 - May'15

Real Time Adaptive Profiling in Storm Topologies, System Research Group, University of Illinois at Urbana-Champaign, Under Prof. Roy Campbell and Prof. Indy Gupta.

The layout of stream processing job and its parallelism is statically defined before execution and is not tuned by the Storm runtime. The bursty workloads of real time streams combined with the unstructured nature of big data presents unique challenges. Here we are working a dynamic profiling engine that runs within Storm and generates improved topologies, optimizing for throughput and latency on a given set of resources.


Context Passing in Cloud

Dec'13 - May'14

Using Context to Improve Performance of Cloud Stacks, System Research Group, University of Illinois at Urbana-Champaign, Under Prof. Roy Campbell and Prof. Indy Gupta.

General-purpose cluster management substrates such as YARN, Mesos, and HDFS, make it easier to run arbitrary systems atop them. Unfortunately, the generalized APIs supported by these substrates suffer from performance limitations and inefficiencies. This is primarily because these APIs do not support passing contextual information with requests and responses. As evidence of this gap, we have found several JIRA issues from these substrates. Also, we associating annotations with requests and responses in several ways to fix this gap.


Mimesis

Nov'13 - May'14

Mimesis Namespace Generetor, System Research Group, University of Illinois at Urbana-Champaign, Under Prof. Roy Campbell.

This project is a namespace generator that can create large and realistic hierarchical namespaces. This tool preserves many distributions of the hierarchy including: directories at each depth, subdirectories per directory, files at each depth, files per directory, file sizes, file creation stamps. Additionally, it includes configurations based on a large Hadoop (HDFS) cluster, as well as several configurations based on statistics collected at several HPC deployments.