Software development, Computer Architecture simulation/modeling
Resume:
Mao-Lin Li
**** ****** ***. ***. ***, Pittsburgh, PA
*********@*****.***
Linkedin: http://goo.gl/T3oPQ9
SUMMARY
An experienced researcher/programmer with more than four years of previous experience in software
development. Academic publications and implementation projects include computer architecture
simulation/modeling and relationship analysis in academic social network. Knowledgeable about machine
learning, natural language processing with solid working experience.
CORE SKILLS
• Programming Languages:
C/C++, SystemC, Java, Python, Matlab, Shell Script
• Systems:
Developed a personal healthcare system which adapting component-based design approach in Slow
Intelligence System (provided by Computer Science Department in University of Pittsburgh).
- Established multiple components which controlling different sensors (Blood Pressure, ECG, SPO2…).
- Design an integrated control panel GUI to manipulate and monitor the status of various sensors.
• Professional Research:
Computer Architecture simulation/modeling - Bus, Memory, Nanophotonic Interconnection.
Social Network Analysis - Academic social network modeling and relationship evaluation.
EXPERIENCE
Research Assistant, University of Pittsburgh; Pittsburgh, PA 2014-Present
• Developed a personal healthcare system that monitoring patients’ health status in real-time.
• Implemented system with component-based approach in Java, including graphic users interface (GUI),
server/client communication, remote database manipulation and multiple sensor controlling.
Teaching Assistant, University of Pittsburgh; Pittsburgh, PA 2012-2014
• Introduction to Computer Architecture
• Intermediate Programming using Java
• Introduction to Computer Programming (Python)
Research Assistant, National Tsing Hua University; Taiwan 2008-2011
• Designed a two-phase arbiter model that speed up simulation performance 20 times than traditional
simulation approach in Multiprocessor System on Chip platform.
• Implemented in C++ with SystemC library.
• Related publication won Outstanding Paper Award out of 72 papers in international workshop.
PATENT
Full Bus Transaction Level Modeling Approach for Fast and Accurate Contention Analysis
United States 201********, publication date: 02/28/2013
AWARDS
• Art & Science Graduate Fellow in University of Pittsburgh, 2012-2013.
• Outstanding Paper Award in SASIMI International Workshop 2012 (out of 72 papers)
“ A Formal Full Bus TLM Modeling for Fast and Accurate Contention Analysis”
• Excellent work in Undergraduate Special Topic Project Competition, 2007
“Digital Frame Application in ARM-s3c2410 Development Board”
PUBLICATIONS (HTTP://GOO.GL/T3OPQ9)
• Computer Architecture Simulation and Modeling Related: (Journal: 1, Conference: 6)
• Social Network Analysis Related: (Journal: 1, Conference: 1)
PROJECTS
Performance Prediction in MLB Game (Machine Learning)
• Adapted three machine learning algorithms: Naïve Bayes, Alternating Decision Tree and Adaptive Boost
with wrapper feature selection to predict the performance of Pittsburgh Pirates baseball team.
• Implemented in Python with Weka toolset.
• Achieved more than 70% accuracy in prediction.
Automatic Grading System (Natural Language Processing)
• Developed an automatic grading system which combing bag-of-word, latent semantic analysis and textual
entailment techniques to grade short-answer question.
• Implemented in Python and Java with Weka toolset.
• Achieved 50% accuracy in final result.
A Sensor-Cloud Simulation Platform with Slow Intelligence System (Software Engineering)
• Created a sensor-cloud platform with component-based approach that simulates the multiple sensors to
collect temperature information within Pittsburgh area and upload it to database for further analysis.
• Personally implemented component from scratch in Java.
Two-Pass Token Stream Arbitration on Nanophotonic Interconnection (Nanophotonic Interconnection)
• Implemented a nanophtonic interconnection model in a 64 cores system that supporting multiple-reader,
multiple writer (MWMR) with two-pass token stream arbitration policy.
• Designed a centralized software architecture and implemented in C++ with SystemC library.
• Achieved 100 % cycle-accurate simulation accuracy.
A Genetic Algorithm-based Approach to Maximize Application Throughput in Multicore System
(Multicore System Optimization)
• Designed a genetic algorithm-based approach that optimizing the thread assignment to maximize application
throughput in Multi-core system (64 cores).
• Implemented in Python and Bash script.
• Achieved 50% converge time compares with brutally searching
An Automatic TLM Bus Generator for Communication Architecture Exploration (Transaction Level
Modeling)
• Designed a transaction level model bus generator that can automatically generates cycle-accurate (CA) and
cycle count accurate (CCA) level bus model simultaneously.
• Proposed CCA bus model achieves 20 times speedup in simulation performance with 100% accuracy.
• Won Outstanding Paper award in SASIMI workshop 2012 (out of 72 papers).
EDUCATIONS
• University of Pittsburgh, Pittsburgh, PA M.S. in Computer Science, 2014
• National Tsing Hua University, Taiwan M.S. in Computer Science, 2011
• National Sun-Yat Sen University, Taiwan B.S. in Computer Science and Engineering, 2008
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