Who am I?

Personal Details

  • Name: Tae Jun Ham
  • Nationality: Republic of Korea
  • Office : Computer Science 213, Princeton University
  • Email: ham.taejun (at) gmail.com

About Me

I am a fifth year Ph.D student in Electrical Engineering at Princeton University. My advisor is Professor Margaret Martonosi in Computer Science Department. I am interested in broad area of computer architecture. In particular, my current research interest is on efficient communication in accelerator-based heterogeneous systems.

My Education


2012 September - Present

Doctor of Philosophy

Master of Arts

Princeton University Princeton, New Jersey, USA

Ph.D Candidate in Electrical Engineering
Advisor : Margaret Martonosi
Research Area : Efficient communication in accelerator-based heterogeneous architecture

2008 September - 2011 December

Bachelor of Science

in Engineering

Duke University Durham, North Carolina, USA

Bachelor of Science in Electrical and Computer Engineering (GPA : 3.95 / 4.00)
Summa Cum Laude with Distinction in Electrical and Computer Engineering

Academic Researches


MICRO 2016 October

Taipei, Taiwan

Graphicionado: A High-Performance and Energy Efficient Accelerator for Graph Analytics [Link] [Slide]

Tae Jun Ham, Lisa Wu, Narayanan Sundaram, Nadathur Satish, Margaret Martonosi
49th International Symposium on Microarchitecture
Acceptance rate: 61/283=22(%)
Best Paper Award

MICRO 2015 December

Waikiki, USA

DeSC: Decoupled Supply-Compute Communication Management for Heterogeneous Architectures [Link]

Tae Jun Ham, Juan Luis Aragon, Margaret Martonosi
48th International Symposium on Microarchitecture
Acceptance rate: 61/283=22(%)
IEEE MICRO Top Picks Honorable Mention (Top 23 computer architecture papers of 2015)

HPCA 2013 February

Shenzhen, China

Disintegrated control for energy-efficient and heterogeneous memory systems [Link]

Tae Jun Ham, Bharath K.Chelepalli, Neng Xue, Benjamin C.Lee
19th International Symposium on High Performance Computer Architecture
Acceptance rate: 51/249=20(%)

My Professional Background

Work Experience

2016 May - 2016 August

Graduate Research Intern

Microsoft Research Cambridge, UK

Collaborator: Stavros Volos
Research on an efficient secure memory design with near-data computation

2015 May - 2015 November

Graduate Technical Intern

Intel Labs Santa Clara, California, USA

Collaborator: Lisa Wu
Research on a custom hardware accelerator for graph analytics application

2013 June - 2013 August

Co-op Engineer

AMD Research Austin, Texas, USA

Collaborator: Joseph L. Greathouse, Mitesh Meswani and Nuwan Jayasena
Research on a mobile high-performance energy-efficient heterogeneous system consists of large, low memory bandwidth processors
and small, high memory bandwidth processors.

2012 June - 2012 August

Research Intern

Samsung Advanced Institute of Technology Seoul, Republic of Korea

Collaborator: Woong Seo and Yeon-Gon Cho
Research on various techniques to reduce the performance/energy impact of GPU branch/memory divergence.

2011 January - 2012 May

Research Assistant

Systems Architecture Integration Lab. Duke University, Durham, North Carolina, USA

Advisor: Professor Benjamin. C. Lee
Research on efficient control and management of the heterogeneous memory system.

Honors, Patents, and Courseworks


Honors and Awards

MICRO-49 Best Paper Award (2016)

Graphicionado paper is selected as the Best Paper in MICRO 2016

IEEE MICRO Top Picks Honorable Mention (2016)

DeSC paper is selected as one of top 23 computer architecture papers of 2015

Facebook Graduate Fellowship Finalist (2016)

Gordon Y.S. Wu Fellowship (2012-2017), Princeton University

Prestigious award given to top incoming graduate students.

Samsung Scholarship (2012-2017)

Prestigious award given to Korean students studying in US.
Up to $50,000 per year for five years of graduate studies.

Summa Cum Laude (2011), Duke University

Latin honor given to top graduates of the class


Instruction, Circuits, and Logic for Graph Analytics Acceleration
(Filed April, 2016)

with Lisa Wu, Nadathur Satish, and Narayanan Sundaram

Relevant Courseworks

  • Computer Architecture
  • Advanced Computer Architecture
  • Parallel Computation
  • Operating Systems
  • Energy-Efficient Computer Systems
  • Fault Tolerant System
  • Advanced Digital System Design
  • Design of Very Large Integrated Systems
  • Advanced Computer Networks


  • Designing Real Systems