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Columbia, South Carolina United States
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Assistant Professor
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I am an assistant professor in the Computer Science and Engineering Department at the University of South Carolina. My goal is to advance a scientific, principled understanding of machine learning systems, with an eye towards computer systems analysis (e.g., understanding their performance behavior, reasoning about qualities and making tradeoff) informed by careful empirical work. Naturally, I am also interested in connections among software engineering, computer systems, and machine learning.
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machine learning
cloud architecture
transfer learning
self-adaptive software
performance tuning
highly configurable software
devops
configuration optimization
cloud computing
software architecture
software engineering
big data
artificial intelligence
uncertainty
auto-scaling
performance analysis
elasticity
apache cassandra
apache storm
migration pattern
performance engineering
machine learning systems
microservices
cloud architecture pattern
multi-cloud
gaussian process
autonomic computing
adaptive system
apache hadoop
fuzzy control
apache kafka
design of experiment
stream processing system
response surface
cloud resource provisioning
software architecture evolution
ai
causality
causal inference
systems
cloud migration
robotics
model learning
model prediction
bayesian optimization
predictive models
windows azure
model driven development
pattern-based software evolution
change pattern
software evolution
dynamic resource provisioning
architecture-centric software evolution
amazon cloud
application modernization
systematic literature review
evidence-based and empirical study
openstack
google cloud
cloud design pattern
elastic software
method engineering
uai2020
chain graphs
thesis
dissertation
viva
phd
planning
ai security
deep learning
adversarial machine learning
highly-configurable systems
model-based adaptation
darpa brass
architectural tradeoffs
distributed systems
software performance models
exploratory study
sensitivity analysis
adaptive robotic software
auto-tuning
cassandra
software testing
storm
feedback-driven development
continuous delivery
knowledge sharingcloud computing
reinforcement learning
knowledge evolution
self-learning
software connectors
cloud auto-scaling
runtime adaptation
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