Biography
Dr. Chunhua "Leo" Liao is a senior computer scientist in the Center for Applied Scientific Computing (CASC) at Lawrence Livermore National Laboratory. He leads cutting-edge research in programming models, compiler technologies, and AI-assisted tools for high-performance computing (HPC). He has made significant contributions to the performance and correctness of parallel applications through innovations in OpenMP, optimizing compilers, source-to-source translation, automatic parallelization, and programming tools. He has also been working on integrating AI into HPC software development, co-authoring recent work on leveraging large language models (LLMs) for code understanding, migration, and optimization—including Fortran2CPP, HPC-GPT, and CompilerGPT.
Dr. Liao received his Ph.D. degree in Computer Science from University of Houston in Aug. 2007. He also holds M.E. and B.E. degrees in Computer Science from Sichuan University in China.
Research Experience
Dr. Liao has been the co-principal investigator, a critical contributor, and a leading maintainer of the widely used ROSE compiler infrastructure since 2007. He is the leading author for an OpenMP implementation (XOMP) supporting multiple runtime libraries, effective source-to-source outlining, semantic-aware automatic parallelization, OpenMP accelerator support (HOMP), and DataRaceBench. He is also a critical contributor to compiler-based resilience, autotuning, runtime error checking, and so on. In 2009, the ROSE team was a recipient of the prestigious R&D 100 Award due to their significant contributions in making compiler technologies more accessible.
Dr. Liao has been one of proposal initiators, principal investigators and senior personnel for many collaborative research& development projects, including:
- Compiler-based Software Assurance Tools (2020-Present)
- HPC-FAIR: A Framework Managing Data and AI Models for Analyzing and Optimizing Scientific Applications (9/20-8/23)
- RAPIDS2: A SciDAC Institute for Computer Science, Data, and Artificial Intelligence (10/20-9/25),
- Achieving Peak Performance of HPC Applications By Optimizing Parallelism (10/20-9/23),
- XPlacer: Extensible and Portable Optimizations of Data Placement in Memory (10/17-9/20),
- RAPIDS, SciDAC Institute for Computer Science and Data (10/17-9/20),
- Data Race Free HPC Software (10/16-9/19),
- Exascale Code Generation Toolkit (10/16-3/19),
- Institute for Sustained Performance, Energy, and Resilience (SUPER) (10/11-09/16),
- DSL Technology for Exascale Computing (D-TEC) (09/12-08/15),
- FAIL-SAFE: Fault Aware Intelligent Software For Exascale (12/13-07/15),
- A Node-Level Programming Model Framework for Exascale(04/12-03/15),
- Compiled MPI: Cost-Effective Exascale Application Development (10/10-09/13),
- Thrifty: An Exascale Architecture for Energy Proportional Computing (10/10-09/13),
- CoDEx: A Hardware/Software Codesign Environment for the Exascale Era (10/10-09/13),
- Semantics-Driven Optimization of Scientific Applications (10/09-09/12)
Prior to LLNL, he was a key developer for an OpenMP reference compiler named OpenUH, an academic branch of the Open64 compiler. He was also a contributor to the Dragon Analysis Tool and OpenMP validation suite.
Selected Software Releases
Publications
2025 3 publications
Patrick Serrano, Luwen Huangfu, Chunhua Liao, Dongqing Lin, Kai Williams, Jaden Perleoni, and Thomas Brettin. LLM-Driven Document Clustering: Improving Real-time Security Intelligence Extraction and Threat Analysis. The 2025 IEEE International Conference on Intelligence and Security Informatics (ISI), July 12–13, 2025, Hong Kong, China. LLNL-CONF-2001933
Xiangwei Wang, Xinning Hui, Chunhua Liao, and Xipeng Shen. Reductive Analysis with Compiler-Guided Large Language Models for Input-Centric Code Optimizations. The 46th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2025), Seoul, South Korea, June 16–20, 2025. LLNL-CONF-868729
Peter Pirkelbauer and Chunhua Liao. CompilerGPT: Leveraging Large Language Models for Analyzing and Acting on Compiler Optimization Reports. Presented at the Fifth Workshop on Compiler-assisted Correctness Checking and Performance Optimization for HPC (C3PO-HPC), held in conjunction with ISC 2025, June 10–13, Hamburg, Germany. LLNL-CONF-2001471
2024 6 publications
Le Chen, Bin Lei, Dunzhi Zhou, Pei-Hung Lin, Chunhua Liao, Caiwen Ding, Ali Jannesari, Fortran2CPP: Automating Fortran-to-C++ Migration using LLMs via Multi-Turn Dialogue and Dual-Agent Integration, 27 Dec 2024 arxiv.2305.14979
Xingyao Yi, Anjia Wang, Yonghong Yan, Chunhua Liao, Developing an Interactive OpenMP Programming Book with Large Language Models, International Workshop on OpenMP, 2024
Naveed Sekender, Pei-Hung Lin, Chunhua Liao, Finding Equivalent OpenMP Fortran and C/C++ Code Snippets Using Large Language Models, International Workshop on OpenMP, 2024
Chunhua Liao, Xipeng Shen, Murali Emani, Tristan Vanderbruggen, Pei-Hung Lin, HPC-FAIR: A Framework Managing Data and AI Models for Analyzing and Optimizing Scientific Applications, Technical Report, LLNL 2024
Peter Pirkelbauer, Chunhua Liao, Pei-Hung Lin, David Wright, Charles Reynolds, Daniel Quinlan, Supporting Ada in the ROSE compiler, ACM SIGAda Ada Letters, 2024
Alnis Murtovi, Giorgis Georgakoudis, Konstantinos Parasyris, Chunhua Liao, Ignacio Laguna, Bernhard Steffen, Enhancing Performance Through Control-Flow Unmerging and Loop Unrolling on GPUs, 2024 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)
2023 4 publications
Le Chen, Xianzhong Ding, Murali Emani, Tristan Vanderbruggen, Pei-Hung Lin, and Chunhua Liao. Data Race Detection Using Large Language Models. In Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis (SC-W 2023), November 12--17, 2023, Denver, CO, USA. ACM, New York, NY, USA 9 Pages.
Xianzhong Ding, Le Chen, Murali Emani, Chunhua Liao, Pei-Hung Lin, Tristan Vanderbruggen, Zhen Xie, Alberto Cerpa, and Wan Du. HPC-GPT: Integrating Large Language Model for High-Performance Computing. In Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis (SC-W 2023), November 12--17, 2023, Denver, CO, USA. Association for Computing Machinery, New York, NY, USA, 951–960. LLNL-CONF-853156
Bin Lei, Caiwen Ding, Le Chen, Pei-Hung Lin, and Chunhua Liao. Creating a Dataset Supporting Translation Between OpenMP Fortran and C++ Code. IEEE High Performance Extreme Computing, Sept.25-29, 2023, LLNL-PROC-851836 (Outstanding Student Paper)
Le Chen, Pei-Hung Lin, Tristan Vanderbruggen, Chunhua Liao, Murali Emani, and Bronis de Supinski, LM4HPC: Towards Effective Language Model Application in High-Performance Computing, IWOMP, University of Bristol, UK, Sept. 12-15, 2023 LLNL-CONF-849438
2022 7 publications
Winson Chen, Tristan Vanderbruggen, Pei-Hung Lin, Chunhua Liao, Murali Emani, Early Experience with Transformer-Based Similarity Analysis for DataRaceBench, the Sixth International Workshop on Software Correctness for HPC Applications (Correctness 2022), LLNL-CONF-838838
Zifan Nan, Mithil Dave, Xipeng Shen, Chunhua Liao, Tristan Vanderbruggen, Pei-Hung Lin, Murali Emani, Interactive NLU-Powered Ontology-Based Workflow Synthesis for FAIR Support of HPC, the 2022 IEEE/ACM 9th International Workshop on HPC User Support Tools (HUST-22) held in conjunction with SC '22, LLNL-CONF-833524
Pei-Hung Lin, Chunhua Liao, Winson Chen, Tristan Vanderbruggen, Murali Emani and Hailu Xu, Making Machine Learning Datasets and Models FAIR for HPC: A Methodology and Case Study, 1st Workshop on Trustable and Ethical Machine Learning, During Transdisciplinary AI, Laguna Hills, CA, USA, 19-21 September 2022, LLNL-CONF-832022
José Wesley de Souza Magalhães, Chunhua Liao, Fernando Magno Quintão Pereira, Automatic Inspection of Program State in an Uncooperative Environment, Software: Practice and Experience, 2022, LLNL-JRNL-826460
Hailu Xu, Pei-Hung Lin, Murali Emani, Liting Hu, Chunhua Liao, X-Unified: A Framework for Guiding Optimal Use of GPU Unified Memory, IEEE Access, 2022, LLNL-CONF-798297
Patrick Flynn, Tristan Vanderbruggen, Chunhua Liao, Pei-Hung Lin, Murali Emani and Xipeng Shen, Finding Reusable Machine Learning Components to Build Programming Language Processing Pipelines, 2nd International Workshop on Software Architecture and Machine Learning, 2022, https://arxiv.org/abs/2208.05596, LLNL-CONF-837414
Giorgis Georgakoudis, Thomas Scogland, Chunhua Liao and Bronis de Supinski, Extending OpenMP to Support Automated Function Specialization Across Translation Units, IWOMP 2022, Chattanooga, TN, Sept. 27-30, 2022, LLNL-CONF-837685
2021 7 publications
Yaying Shi, Anjia Wang, Yonghong Yan, Chunhua Liao, RDS: A Cloud-Based Metaservice for Detecting Data Races in Parallel Programs, 14th IEEE/ACM International Conference on Utility and Cloud Computing, University of Leicester, Leicester, UK, December 6-9, 2021 LLNL-CONF-809187
Pei-Hung Lin, Chunhua Liao. High-Precision Evaluation of Both Static and Dynamic Tools using DataRaceBench. International Workshop on Software Correctness for HPC Applications (Correctness), St. Louis, MO, Nov. 2021, LLNL-CONF-825647
Gaurav Verma, Murali Emani, Chunhua Liao, Pei-Hung Lin, Tristan Vanderbruggen, Xipeng Shen, Barbara Chapman, HPCFAIR: Enabling FAIR AI for HPC Applications, 2021 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC), LLNL-CONF-826435
Chunhua Liao, Anjia Wang, Giorgis Georgakoudis, Bronis R. de Supinski,Yonghong Yan, David Beckingsale, and Todd Gamblin, Extending OpenMP for Machine Learning-Driven Adaptation, Eighth Workshop on Accelerator Programming Using Directives (WACCPD), Nov. 2021, LLNL-CONF-826432
Chunhua Liao, Pei-Hung Lin, Gaurav Verma, Tristan Vanderbruggen, Murali Emani, Zifan Nan, Xipeng Shen, HPC Ontology: Towards a Unified Ontology for Managing Training Datasets and AI Models for High-Performance Computing, 2021 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC), LLNL-CONF-826494
Xinyao Yi, David Stokes, Yonghong Yan, Chunhua Liao, CUDAMicroBench: Microbenchmarks to Assist CUDA Performance Programming, 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 17-21 June 2021, Portland, OR, USA, LLNL-CONF-819919
Zifan Nan, Hui Guan, Xipeng Shen, and Chunhua Liao. Deep NLP-based co-evolvement for synthesizing code analysis from natural language. In Proceedings of the 30th ACM SIGPLAN International Conference on Compiler Construction, pp. 141-152. 2021. LLNL-CONF-794949
2020 3 publications
Gleison Mendonca, Chunhua Liao and Fernando Duarte, AutoParBench: A Unified Test Framework for OpenMP-based Parallelizers, International Conference on Supercomputing, June 29-July 2 2020, Barcelona, Spain, LLNL-CONF-795158
Peter Pirkelbauer, Pei-Hung Li, Tristan Vanderbruggen, Chunhua Liao, XPlacer: Automatic Analysis of CPU/GPU Access Patterns, IPDPS 2020, LLNL-CONF-795057
Anjia Wang, Alok Mishra, Chunhua Liao, Yonghong Yan, and Barbara Chapman, FreeCompilerCamp.org: Training for OpenMP Compiler Development from Cloud, Volume 11, Issue 1, pp. 53 - 60, Journal of Computational Science Education, Jan. 2020
2019 5 publications
Anjia Wang, Alok Mishra, Chunhua Liao, Yonghong Yan, Barbara Chapman, FreeCompilerCamp.org: Training for OpenMP Compiler Development from Cloud, Sixth SC Workshop on Best Practices for HPC Training and Education: BPHTE19, 2019 LLNL-CONF-791339
Pei-Hung Lin, Chunhua Liao, Markus Schordan, Ian Karlin, Exploring Regression of Data Race Detection Tools Using DataRaceBench, Third International Workshop on Software Correctness for HPC Applications (Correctness 2019)
Anjia Wang, Yaying Shi, Xinyao Yi, Yonghong Yan, Chunhua Liao and Bronis R. de Supinski, "ompparser: A Standalone and Unified OpenMP Parser," Fifteenth International Workshop on OpenMP (IWOMP 2019), Auckland, New Zealand, September 11–13, 2019. (LLNL-CONF-774801).
Yonghong Yan, Anjia Wang, Chunhua Liao, Tom Scogland and Bronis R. de Supinski, Extending OpenMP Metadirective Semantics for Runtime Adaptation, Fifteenth International Workshop on OpenMP (IWOMP 2019), Auckland, New Zealand, September 11–13, 2019. (LLNL-CONF-774899)
Jie Ren, Chunhua Liao and Dong Li, Opera: Data Access Pattern Similarity Analysis To Optimize OpenMP Task Affinity, 24th International Workshop On High-level Parallel Programming Models And Supportive Environments (HIPS), Held in Conjunction With 33rd IPDPS International Parallel & Distributed Processing Symposium, May 20-24, 2019, Rio De Janeiro, Brazil
2018 3 publications
Pei-Hung Lin, Chunhua Liao, Markus Schordan, Ian Karlin: Runtime and Memory Evaluation of Data Race Detection Tools. In International Symposium on Leveraging Applications of Formal Methods, pp. 179-196. Springer, Cham, 2018.
M.Bari, L. Stoltzfus, P. Lin, C. Liao, M. Emani, B.Chapman, Is Data Placement Optimization Still Relevant on Newer GPUs? The 9th International Workshop on Performance Modeling, Benchmarking, and Simulation of High-Performance Computer Systems (PMBS18), Dallas, TX, Nov 12th, 2018
- Chunhua Liao, Pei-Hung Lin, Markus Schordan and Ian Karlin, A Semantics-Driven Approach to Improving DataRaceBench's OpenMP Standard Coverage, IWOMP 2018: 14th International Workshop on OpenMP, Barcelona, Spain, September 26-28, 2018, Proceedings. 189-202. Springer Link, LLNL copy, slides
2017 1 publication
- Chunhua Liao, Pei-Hung Lin, Joshua Asplund, Markus Schordan and Ian Karlin, DataRaceBench: A Benchmark Suite for Systematic Evaluation of Data Race Detection Tools, The International Conference for High Performance Computing, Networking, Storage and Analysis, Denver, CO, Nov. 12-17, 2017 (Best Paper Nominee). LLNL copy, slides
2016 3 publications
- A Proposal to OpenMP for Addressing the CPU Oversubscription Challenge, Yonghong Yan, Jeff R. Hammond, Chunhua Liao, and Alexandre E. Eichenberger, IWOMP 2016, Oct 6-7, 2016 Nara, Japan Springer Link
- Pei-Hung Lin, Qing Yi, Daniel Quinlan, Chunhua Liao and Yongqing Yan, Automatically Optimizing Stencil Computations on Many-core NUMA Architectures, The 29th International Workshop on Languages and Compilers for Parallel Computing (LCPC 2016) September 28-30, 2016 Rochester NY, USA pdf
- Yue Zhao, Guoyang Chen, Chunhua Liao and Xipeng Shen, Towards Ontology-Based Program Analysis, The European Conference on Object-Oriented Programming (ECOOP), July 17-22, 2016 Rome, Italy. pdf slides poster
2015 3 publications
- Chunhua Liao, Pei-Hung Lin, Daniel J. Quinlan, Yue Zhao, and Xipeng Shen. 2015. Enhancing domain specific language implementations through ontology. In Proceedings of the 5th International Workshop on Domain-Specific Languages and High-Level Frameworks for High Performance Computing (WOLFHPC '15). ACM, New York, NY, USA ACM Link slides
- Pei-Hung Lin, Chunhua Liao, Daniel Quinlan and Stephen Guzik, Experiences of Using the OpenMP Accelerator Model to Port DOE Stencil Applications, 11th International Workshop on OpenMP, Oct 1-2, 2015, Aachen, Germany pdf slides
- Yonghong Yan, Pei-Hung Lin, Chunhua Liao, Bronis R. de Supinski, and Daniel J. Quinlan. 2015. Supporting multiple accelerators in high-level programming models. In Proceedings of the Sixth International Workshop on Programming Models and Applications for Multicores and Manycores (PMAM '15), Pavan Balaji, Minyi Guo, and Zhiyi Huang (Eds.). ACM, New York, NY, USA, 170-180. ACM link
2014 1 publication
- Jacob Lidman, Sally McKee, Daniel Quinlan and Chunhua Liao, An Automated Performance-Aware Approach to Reliability Transformations, Euro-Par 2014, 25-29 August, Porto, Portugal pdf
2013 2 publications
- Hongyi Ma, Steve R. Diersen, Liqiang Wang, Chunhua Liao, Daniel Quinlan, and Zijiang Yang. 2013. Symbolic Analysis of Concurrency Errors in OpenMP Programs. In Proceedings of the 2013 42nd International Conference on Parallel Processing (ICPP '13). IEEE Computer Society, Washington, DC, USA, 510-516. IEEE Link
- Chunhua Liao, Yonghong Yan, Bronis R. de Supinski, Daniel J. Quinlan and Barbara Chapman, Early Experiences With The OpenMP Accelerator Model, 9th International Workshop on OpenMP (IWOMP), Canberra, Australia, Sept. 16-18,2013 pdf slides
2012 2 publications
- Jacob Lidman, Daniel J. Quinlan, Chunhua Liao and Sally A. McKee, ROSE::FTTransform::A Source-to-Source Translation Framework for Exascale Fault-Tolerance Research, Fault-Tolerance for HPC at Extreme Scale (FTXS 2012), Boston, June 25-28, 2012. slides
Sara Royuela, Alejandro Duran, Chunhua Liao and Daniel J. Quinlan, Auto-scoping for OpenMP tasks, The 8th International Workshop on OpenMP (IWOMP 2012), Rome, June 11-13, 2012.
2011 2 publications
- Peter Pirkelbauer, Chunhua Liao, Thomas Panas and Dan Quinlan, Runtime Detection of C-Style Errors in UPC Code, Fifth Partitioned Global Address Space Conference (PGAS), Galveston, TX, Oct. 2011 pdf
Ananta Tiwari, Jeffrey K Hollingsworth, Chun Chen, Mary Hall, Chunhua Liao, Daniel J Quinlan, and Jacqueline Chame. Auto-tuning full applications: A case study. International Journal of High Performance Computing Applications, Volume 25, Issue 3 (August 2011), Pages 286-294.
2010 2 publications
- Chunhua Liao, Daniel J. Quinlan, Thomas Panas and Bronis de Supinski, A ROSE-based OpenMP 3.0 Research Compiler Supporting Multiple Runtime Libraries, international Workshop on OpenMP (IWOMP) 2010, accepted in March. 2010 LLNL-CONF-422873 pdf
- Chunhua Liao, Daniel J. Quinlan, Jeremiah J. Willcock and Thomas Panas, Semantic-Aware Automatic Parallelization of Modern Applications Using High-Level Abstractions, Journal of Parallel Programming, Accepted in Jan. 2010 pdf
2009 3 publications
- Chunhua Liao, Daniel J. Quinlan and Thomas Panas, Towards an Abstraction-Friendly Programming Model for High Productivity and High Performance Computing, Workshop on Non-Traditional Programming Models for High-Performance Computing, Los Alamos Computer Science Symposium (LACSS) 2009, Santa Fe, New Mexico, October 13-14, 2009 LLNL-CONF-417691 pdf.
- Chunhua Liao, Daniel J. Quinlan, Richard Vuduc and Thomas Panas, Effective Source-to-Source Outlining to Support Whole Program Empirical Optimization, The 22nd International Workshop on Languages and Compilers for Parallel Computing, Newark, Delaware, USA. October 8-10, 2009. pdf.
- Chunhua Liao, Daniel J. Quinlan, Jeremiah J. Willcock and Thomas Panas, "Extending Automatic Parallelization to Optimize High-Level Abstractions for Multicore," In Proceedings of the 5th international Workshop on OpenMP: Evolving OpenMP in An Age of Extreme Parallelism (Dresden, Germany, June 03 - 05, 2009). pdf.
2007 2 publications
Chunhua Liao, A Compile-Time OpenMP Cost Model, Ph.D. dissertation, University of Houston, Texas, 2007.
Chunhua Liao, Oscar Hernandez, Barbara Chapman, Wenguang Chen and Weimin Zheng, OpenUH: An Optimizing, Portable OpenMP Compiler, Concurrency and Computation: Practice and Experience, Special Issue: Current Trends in Compilers for Parallel Computers, Vol. 19, no. 18, p 2317 - 2332, April. 2007.
2006 1 publication
Lei Huang, Barbara Chapman, Chunhua Liao, An Implementation and Evaluation of Thread Subteam for OpenMP Extensions, PMUP'06 (Programming Models for Ubiquitous Parallelism) workshop, Seattle, Washington, Sept. 16, 2006.
2005 1 publication
Chunhua Liao, Zhenying Liu, Lei Huang and Barbara Chapman, Evaluating OpenMP on Chip MultiThreading Platforms. First International Workshop on OpenMP (IWOMP). Eugene, Oregon USA. June 1-4, 2005.
2004 2 publications
Oscar Hernandez, Chunhua Liao and Barbara Chapman, A Tool to Display Array Access Patterns in OpenMP Programs, PARA'04 workshop on state-of-the-art in scientific computing, Lyngby, Copenhagen, Denmark, June 20-23, 2004.
Oscar Hernandez, Chunhua Liao and Barbara Chapman, Dragon: A static and dynamic tool for OpenMP, Workshop on OpenMP Applications and Tools (WOMPAT) 2004, pp.53-66, 2004.
Other 6 publications
Ethan Dorta, Chunhua Liao, Yonghong Yan, Generating and Analyzing Program Call Graphs using Ontology, Workshop on Programming and Performance Visualization Tools, held in conjunction with SC'22, LLNL-CONF-838827
Justin Gosselin, Anjia Wang, Peter Pirkelbauer, Chunhua Liao, Yonghong Yan, and Damian Dechev, Extending FreeCompilerCamp.org as an Online Self-Learning Platform for Compiler Development, EduHPC, SC20 workshops
Gaurav Verma, Yaying Shi, Chunhua Liao, Barbara Chapman, and Yonghong Yan, Enhancing DataRaceBench for Evaluating DataRace Detection Tools, Correctness SC20 workshops
Hailu Xu, Murali Emani, Pei-Hung Lin, Liting Hu, Chunhua Liao, Machine Learning Guided Optimal Use of GPU Unified Memory, MCHPC '19: Workshop on Memory Centric High Performance Computing. (LLNL-CONF-793704)
Alok Mishra, Anjia Wang, Chunhua Liao, Yonghong Yan, Barbara Chapman, FreeCompilerCamp: Online Training for Extending Compilers, SC'19 Research Poster submission, accepted (also selected as a Best Poster nominee).
Larisa Stoltzfus, Murali Emani, Pei-Hung Lin, and Chunhua Liao. Data Placement Optimization in GPU Memory Hierarchy using Predictive Modeling. In Proceedings of the Workshop on Memory Centric High Performance Computing (MCHPC'18). ACM, New York, NY, USA, 45-49.
Awards
2018 DDS&T Excellence in Publication Award for the publication "DataRaceBench: A Benchmark Suite for Systematic Evaluation of Data Race Detection Tools", Lawrence Livermore National Laboratory
Outstanding Mentor, Lawrence Livermore National Laboratory, 2017
R&D 100 Award for the ROSE compiler, 2009
Computation Directorate Noteworthy Achievement Award, Lawrence Livermore National Laboratory, 2009
Computer Science Department Scholarship, University of Houston, 2006 - 2007
Computer Science Department Scholarship, University of Houston, 2005 - 2006
Shell Scholarship, University of Houston, 2004 – 2005


