Current Students:
  1. Zhiqiang Li, PhD (fall 2012).
  2. Supat Rattanasuksan, PhD (fall 2010).
  3. Yutaka Tsutano, PhD (fall 2008).
  4. Shakthi Bachala, PhD (spring 2014).
  5. Paul Bennett, part-time PhD (spring 2014), at Amazon.
  6. Tony Guan, part-time PhD (spring 2008), at Salesforce.
Graduated Students:
  1. Lichao Sun (jointly supervised with Qiben Yan), MS (summer 2016) at U. of Illinois at Chicago.
  2. Junjie Qian (jointly supervised with Hong Jiang and Sharad Seth), PhD (summer 2016) at Microsoft Research.
  3. Tingting Yu (jointly supervised with Gregg Rothermel), PhD (Summer 2014) at U. of Kentucky.
  4. Zhen Hu (jointly supervised with Gregg Rothermel), MS (May 2017) at Amazon.
  5. ZhongYin Zhang (jointly supervised with Gregg Rothermel), MS (Summer 2014) at Microsoft.
  6. Du Li, PhD (fall 2012), at Microsoft.
  7. Peng Du, MS (Summer 2010), at Nvidia.
  8. Xueling Chen, MS (Summer 2010) at Intel.
  9. Yu Shang (jointly supervised with Myra Cohen), MS (Spring 2009)
  10. Feng Xian (jointly supervised with Hong Jiang), PhD (Spring 2008) at Microsoft,
    Thesis Title: VM-Aware Scheduling Framework: Improving Efficiency of Java Runtime Environments.
  11. Neo Jia, MS (fall 2007) at NVIDIA,
    Thesis Title: NMFLUX: A Framework to Improve Throughput Performance of Application Servers.
  12. Mithuna Soundararaj, MS (Summer 2006) at Microsoft,
    Thesis Title: A Self Adjusting Code-Cache Manager to Balance Start-Up Time and Memory Usage in Memory Constrained Environments.
  13. Shiu-Beng Kooi (jointly supervised with Myra Cohen), MS (Summer 2006) at Netgear,
    Thesis Title: Clustering the Heap in Multi-Threaded Applications for Improved Garbage Collection.
  14. Mulyadi Oey, MS (summer 2005) at Sharpcast,
    Thesis Title: Garbage Collection in the Presence of Remote Objects: An Empirical Study.
  15. Subhani Shaik, MS (fall 2004),
    Project Title: RAMAL: Run-Time Application Monitoring at Architecture Level.
  16. Sita Tangirala, MS (fall 2003),
    Project Title: Increasing Garbage Collection Parallelism through Thread Clustering.

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