Background

Bin Nie is a fourth-year Ph.D. candidate in the Department of Computer Science at the College of William and Mary, under the supervision of Prof. Evgenia Smirni. Before joining W&M, she received her bachelor degree in Software Engineering from Xiamen University in 2012, and master degree in Computer Science from Fordham University in 2014. Her research interests include GPGPU Reliability, Machine Learning, Time Series Analysis, Data Analysis, Heterogeneous System Logs Analysis (HPC, Data Centers, IT systems), Natural Language Processing, and Performance Advertising.

Skills

  • Programming Languages:  Python, Java, C/C++, SQL, Matlab, C#, Shell, SQL
  • Open Source Tools:  TensorFlow, PyTorch, Scikit-learn, LibSVM/LibLinear, Pandas, GPGPU-Sim

Professional Experience

  • 2018/5 - 2018/8 Research Intern, NEC Labs America Princeton, NJ
  • 2017/5 - 2017/8 Research Intern, NEC Labs America Princeton, NJ
  • 2016/5 - 2016/8 Research Intern, Hewlett Packard Enterprise Palo Alto, CA
  • 2015/5 - 2015/8 Research Intern, Oak Ridge National Laboratory Oak Ridge, TN
  • 2014/8 - Present Research Assistant, College of William and Mary Williamsburg, VA
  • 2012/8 - 2014/5 Research Assistant, Fordham University New York, NY

Publications

Error Site Pruning for Practical Reliability Analysis of GPGPU Applications [PDF]

Bin Nie, Lishan Yang, Adwait Jog, and Evgenia Smirni

In the Proceedings of 51st International Symposium on Microarchitecture (MICRO), Fukuoka, Japan, October 2018

(Acceptance rate ≈ 21%) (to appear)

Machine Learning Models for GPU Error Prediction in a Large Scale HPC System [PDF]

Bin Nie, Ji Xue, Saurabh Gupta, Tirthak Patel, Christian Engelmann, Evgenia Smirni, and Devesh Tiwari

In the 48th International Conference on Dependable Systems and Networks (DSN), Luxembourg City, Luxembourg, June 2018

(Acceptance rate ≈ 25%)

Fill-in the Gaps: Spatial-Temporal Models for Missing Data [PDF]

Ji Xue, Bin Nie, and Evgenia Smirni

In the 13th International Conference on Network and Service Management (CNSM), Tokyo, Japan, November 2017

(Acceptance rate ≈ 17.6%)

Characterizing Temperature, Power, and Soft-Error Behaviors in Data Center Systems: Insights, Challenges, and Opportunities [PDF]

Bin Nie, Ji Xue, Saurabh Gupta, Christian Engelmann, Evgenia Smirni, and Devesh Tiwari

In the 25th IEEE International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), Banff, AB, Canada, September 2017

(Acceptance rate ≈ 30.9%)

A Large-Scale Study of Soft-Errors on GPUs in the Field [PDF]

Bin Nie, Devesh Tiwari, Saurabh Gupta, Evgenia Smirni, and James H. Rogers

In the 22nd IEEE International Symposium on High Performance Computer Architecture (HPCA), Barcelona, Spain, March 2016

(Acceptance rate ≈ 22%)

Leveraging Online Social Friendship to Improve Data Swarming Performance

Honggang Zhang, Benyuan Liu, Bin Nie, Zhiyong Xu, Xiayin Weng, and Chao Yu

Computer Networks, 2014

Social Interaction Based Video Recommendation: Recommending YouTube Videos to Facebook Users [PDF]

Bin Nie, Honggang Zhang, and Yong Liu

In 2014 Proceedings IEEE INFOCOM Workshops, Toronto, ON, Canada, April 2014.

Research Projects

College of William and Mary August 2015 - Present

Research Assistant
Advisor: Prof. Evgenia Smirni
Project #1: GPGPU Reliability Analysis at the Application Level
  • Built an error-injection model to investigate error resilience features for GPGPU applications
  • Reduced the number of error sites by more than 90% per error-injection campaign for fast and accurate reliability analysis
Project #2: GPGPU Reliability Analysis at the System Level
  • Analyzed the impact of temperature/power on GPU single-bit errors (SBEs) in the Titan supercomputer
  • Developed ML-based prediction models for effective reliability prediction
  • Designed a similarity-based sample reduction model to address the imbalanced data set problem

System Research at NEC Labs America May 2018 - August 2018

Research Intern
Mentor: Dr. Jianwu Xu
  • Conducted knowledge discovery and anomaly detection in large scale discrete event sensor time series
  • Identified and analyzed system pairwise invariant relationship with deep learning neural machine translation (seq2seq model) technology
  • Delivered system anomaly detection and fault diagnosis based on invariant graph leveraging global and local connection relationships

System Research at NEC Labs America May 2017 - August 2017

Research Intern
Mentor: Dr. Jianwu Xu and Dr. Hui Zhang
  • Designed a predictive analytics framework for a large scale, complex cloud computing system based on a LSTM model and natural language processing for heterogeneous system logs
  • Built a unique local linear surrogate model to predict system failure and associated causalities for interpreting black box AI results

Analytics Lab at Hewlett Packard Enterprise (HPE) May 2016 - August 2016

Research Intern
Mentor: Dr. Mehran Kafai and Dr. Kave Eshghi
  • Evaluated the effects of various feature engineering and machine learning models for click-through rate prediction
  • Developed a linear model utilizing CROHash and Logistic Regression on TF-IDF weighted categorical data

Oak Ridge National Laboratory (ORNL) May 2015 - August 2015

Research Intern
Mentor: Dr. Devesh Tiwari
  • Led a large-scale characterization study of soft-errors on GPU nodes on the Titan* supercomputer
  • Investigated performance on soft-error-affected and error-free GPU nodes
  • Studied temporally-varying user/application behaviors and their indications on errors
  • Devised machine learning models for GPU failure prediction on the Titan
  • * Titan supercomputer, hosted in ORNL, is the world's second fastest supercomputer (as of Nov 2015 Top500 Supercomputer rankings).

Fordham University August 2012 - May 2014

Research Assistant
Advisor: Prof. Honggang Zhang
  • Analyzed how social interactions on Facebook relate to video popularity on YouTube
  • Designed a social-interaction-based video recommendation algorithm and improved accuracy by 25%
  • Built a crawling platform (for data retrieval from Facebook & YouTube) and social network analysis modules

TA Experience

  • CSCI420 Human Computer Interface Design --- Spring 2016
  • CSCI426 Simulation --- Fall 2015
  • CSCI141 Computational Problem Solving in Python --- Fall 2014, Spring 2015

Awards

  • Student Travel Grant for DSN 2018, awarded by IEEE --- 2017
  • Student Travel Grant for CNSM 2017, awarded by IFIP --- 2017
  • Student Travel Grant for HPCA 2016, awarded by IEEE --- 2016
  • OGSR/Graduate Student Association Conference Funds, awarded by College of William and Mary --- 2016
  • Conference Travel Fund Award, awarded by College of William and Mary --- 2016
  • GHC (Grace Hopper Celebration of Women in Computing) Scholarship --- 2015
  • Graduate Studies Advisory Board Fellowship, awarded by W&M Graduate Studies Advisory Board --- 2014, 2015
  • National Scholarship, awarded to top 2% undergraduate students by Ministry of Education of China --- 2010

Last updated in August, 2018