In 2002, the University established a branch campus in Silicon Valley to connect Carnegie Mellon’s many distinctive technology education programs to the innovative business community located in Silicon Valley and northern California. Carnegie Mellon Silicon Valley offers a variety of graduate degree programs designed to educate students to become leaders in global technology innovation and management. Each program provides the appropriate mix of technical, business, and organizational skills critical to successful career advancement. Together, the academic program and related research centers at Carnegie Mellon Silicon Valley reflect a distinctive mix of education characterized by the University’s ongoing focus on creating and implementing solutions for real problems.
Submissions from 2012
Towards Scalable Evaluation of Mobile Applications through Crowdsourcing and Automation (CMU-CyLab-12-006), Shahriyar Amini, Jialiu Lin, Jason Hong, Joy Zhang, and Janne Lindqvist
Changes in Transferable Knowledge Resulting from Study in a Graduate Software Engineering Curriculum, Ray Bareiss, Todd Sedano, and Ed Katz
Data and Network Optimization Effect on Web Performance, Steven Rosenberg, Surbhi Dangi, and Isuru Warnakulasooriya
Towards Teaching Software Craftsmanship, Todd Sedano
Leveraging Fragmental Semantic Data to Enhance Services Discovery, Jia Zhang, Jian Wang, Patrick C.K. Hung, Zheng Li, Jianxiao Liu, and Keqing He
Submissions from 2011
Semantic Geotagging: A Location-Based Hypermedia Approach to Creating Situational Awareness, Ray Bareiss, Martin Griss, Steven Rosenberg, and Yu Zhang
An Exploration of Knowledge and Skills Transfer from a Formal Software Engineering Curriculum to a Capstone Practicum Project, Ray Bareiss and Ed Katz
Contextualized Mobile Support for Learning by Doing in the Real World, Ray Bareiss, Natalie Linnell, and Martin Griss
Contextualized Mobile Support for Learning by Doing in the Real World, Ray Bareiss, Natalie Linnell, and Martin L. Griss
Toward the Next Generation of Emergency Operations Systems, Art Botterell and Martin Griss
Symbolic Execution for Software Testing in Practice – Preliminary Assessment, Cristian Cadar, Microsoft Research, Sarfraz Khurshid, Corina Pasareanu, Koushik Sen, Microsoft Research, and Willem Visser
A Tutorial on Bayesian Networks for System Health Management, Arthur Choi, Lu Zheng, Adnan Darwiche, and Ole J. Mengshoel
Visualizing and Understanding Large-Scale Bayesian Networks, Michele Cossalter, Ole J. Mengshoel, and Ted Selker
A Granular Concurrency Control for Collaborative Scientific Workflow Composition, Xubo Fei, Shiyong Lu, and Jia Zhang
Comparing Extreme Programming and Waterfall Project Results, Feng Ji and Todd Sedano
TRIAGE: Applying Context to Improve Timely Delivery of Critical Data in Mobile Ad Hoc Networks for Disaster Response, Faisal Luqman
Collaborative Scientific Workflows Supporting Collaborative Science, Shiyong Lu and Jia Zhang
Software Health Management with Bayesian Networks, Ole J. Mengshoel and Johann M. Schumann
Initialization and Restart in Stochastic Local Search: Computing a Most Probable Explanation in Bayesian Networks, Ole J. Mengshoel, David C. Wilkins, and Dan Roth
Interface Decomposition for Service Compositions, Corina Pasareanu, Dimitra Giannakopoulou, and Dominico Bianculli
SensorFly: Controlled-mobile Sensing Platform for Indoor Emergency Response Applications, Aveek Purohit, Zheng Sun, Frank Mokaya, and Pei Zhang
Verification and Validation of System Health Management Models using Parametric Testing, Erik Reed, Johann Schumann, and Ole J. Mengshoel
Integrating Probabilistic Reasoning and Statistical Quality Control Techniques for Fault Diagnosis in Hybrid Domains, Brian Ricks, Craig Harrison, and Ole J. Mengshoel
Integrated Software and Sensor Health Management for Small Spacecraft, Johann Schumann, Ole J. Mengshoel, and Timmy Mbaya
