I am a Research Scientist at the Computation Institute of the University of Chicago. I also hold a Joint Appointment at the Data Science and Learning division of Argonne National Laboratory. I closely work with Dr. Rajkumar Kettimuthu and Prof. Ian Foster. Before this, I was a Postdoctoral Appointee in the Mathematics and Computer Science Division at Argonne National Laboratory.
I received my bachelor’s degree in Manufacturing Engineering of Flight Vehicles in 2010 and my master’s degree in Guidance, Navigation and Control in 2013, both from the Northwestern Polytechnic University, China; and my Ph.D. in Computer Science (awarded the highest honor Summa Cum Laude; and International doctoral research component mention) in 2016, from the Universitat Autònoma de Barcelona, Spain, under the supervision of Prof. Emilio Luque.
At Argonne, I work on the DOE RAMSES (Robust Analytic Models for Science at Extreme Scales) project that focuses on developing end-to-end analytical performance models to transform understanding of the behavior of science workflows in extreme-scale science environments. These models are developed to predict the behavior of a science workflow before it is implemented, to explain why performance does not meet design goals, and to architect science environments to meet workflow needs. Powered by the ability of explain and predict performance.
I also work on the DOE AMASE (Architecture and Management for Autonomic Science Ecosystems) project that explores the architecture, methods, and algorithms needed to support future scientific computing systems that are capable of self-configuration, self-optimization and self-manage etc. We propose to make the science ecosystem smart by incorporating the functions of sensing, intelligence, and control.
I am interested in Computer Science related research, mostly include:
- Wide-area data transfer, GridFTP/Globus.org, explaining, modeling & optimizing data transfer
- Data Science and Learning for Infrastructure
- High Performance Computing, Big-Data and Data Mining, Feature Engineering
- Machine Learning and Artificial Intelligence
- Embedded Technique, Real-Time Operating System
- Decision Support System, Operations Research
Recent Professional Service:
- Co-Chair 14th SRMPDS 2018; 13th SRMPDS 2017;
- Technical Program Committee: SIMUL 2016; SIMUL 2015; DAAC 2017.
- Subreviewer: COMPUTATION TOOLS 2015; Euro-Par 2017; CLUSTER 2017; HiPC 2017; WoWS 2017; IPDPS 2018;
- Journal Reviewer: Algorithms-MDPI; Sustainability–MDPI
- Proficient in C/C++, Python, MATLAB and Embedded C Programming.
- Extensive experience with Parallel software development, including MPI and programming models for multicore and heterogeneous architectures (e.g. CUDA, OpenMP, OpenCL).
- Familiar with cluster computing framework (e.g., Apache Spark) and massive datasets mining (e.g., numpy, pandas, scikit-learn and matplotlib).
- Extensive development experience with backend software on Linux.
- Extensive experience with embedded system, real-time OS, hardware and firmware development.
- Simulation with NS3, Netlogo etc.
Professional Training & Certifications:
- Online Course Sequence Models by deeplearning.ai on Coursera. Certificate earned on February 4, 2018
- Online Course Convolutional Neural Networks by deeplearning.ai on Coursera. Certificate earned on November 30, 2017
- Online Course Structuring Machine Learning Projects by deeplearning.ai on Coursera. Certificate earned on August 17, 2017
- Online Course Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization by deeplearning.ai on Coursera. Certificate earned on August 15, 2017
- Online Course Neural Networks and Deep Learning by deeplearning.ai on Coursera. Certificate earned on August 14, 2017
- Online Course DAT203x: Data Science and Machine Learning Essentials HONOR CODE CERTIFICATE from edX by Microsoft.
- The 10th Marathon of Parallel Programming Contest, The First Place, Results.
- The 5th Spanish Parallel Progamming Contest, The First Place, Results, Certificate.
- Online Course Scalable Machine Learning Statement of Accomplishment (SoA) from edX by University of California, Berkeley.
- Online Course Mining Massive Datasets Statement of Accomplishment (SoA) from Coursera by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Stanford University.
- Online Course Machine Learning Statement of Accomplishment (SoA) from Coursera by Andrew Ng, Stanford University.
- The IV Spanish Parallel Progamming Contest , The Second Place, Results, Certificate, how.
NEWS: We are looking for intern students, contact me if you have experience or are interested in any one of: performance modeling, simulation, high performance computing, distributed systems, workflow over distributed infrastructure and smart computing/storage/network.