Personal Information
Unternehmen/Arbeitsplatz
Columbia, South Carolina United States
Beruf
Assistant Professor
Branche
Education
Webseite
pooyanjamshidi.github.io/
Info
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.
Tags
machine learning
cloud architecture
transfer learning
self-adaptive software
performance tuning
highly configurable software
configuration optimization
devops
artificial intelligence
big data
cloud computing
software engineering
software architecture
uncertainty
auto-scaling
machine learning systems
performance analysis
performance engineering
apache storm
apache cassandra
microservices
migration pattern
elasticity
ai
causality
causal inference
systems
robotics
model learning
model prediction
predictive models
bayesian optimization
response surface
stream processing system
design of experiment
apache kafka
apache hadoop
gaussian process
fuzzy control
cloud resource provisioning
adaptive system
autonomic computing
multi-cloud
cloud architecture pattern
windows azure
cloud migration
software architecture evolution
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
dynamic resource provisioning
amazon cloud
application modernization
openstack
google cloud
cloud design pattern
method engineering
elastic software
evidence-based and empirical study
systematic literature review
architecture-centric software evolution
software evolution
change pattern
pattern-based software evolution
model driven development
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Präsentationen
(36)Gefällt mir
(15)ISSTA 2017 Impact Paper Award Presentation
Alex Orso
•
Vor 6 Jahren
Quality of Service Control Mechanisms in Cloud Computing Environments
Soodeh Farokhi
•
Vor 8 Jahren
A Semantics-based User Interface Model for Content Annotation, Authoring and Exploration
Ali Khalili
•
Vor 9 Jahren
Dagstuhl14 intro-v1
CS, NcState
•
Vor 9 Jahren
Building and Managing Scalable Applications on AWS: 1 to 500K users
Amazon Web Services
•
Vor 10 Jahren
Introduction to Amazon Web Services - How to Scale your Next Idea on AWS : A Love Story - Jinesh Varia (Updated Jan 2014)
Amazon Web Services
•
Vor 13 Jahren
How to Get My Paper Accepted at Top Software Engineering Conferences
Alex Orso
•
Vor 10 Jahren
How to Write Research Papers
Tao Xie
•
Vor 10 Jahren
What Would Steve Do? 10 Lessons from the World's Most Captivating Presenters
HubSpot
•
Vor 11 Jahren
ICSE 2009 keynote
Carlo Ghezzi
•
Vor 11 Jahren
Paderborn
Carlo Ghezzi
•
Vor 11 Jahren
Whither Software Engineering Research? (keynote talk at APSEC 2012)
David Rosenblum
•
Vor 11 Jahren
empirical software engineering, v2.0
CS, NcState
•
Vor 13 Jahren
SIGSOFT Impact Award: Reflections and Prospects (invited talk at SIGSOFT FSE 2008)
David Rosenblum
•
Vor 11 Jahren
Lionel Briand ICSM 2011 Keynote
ICSM 2011
•
Vor 12 Jahren
Personal Information
Unternehmen/Arbeitsplatz
Columbia, South Carolina United States
Beruf
Assistant Professor
Branche
Education
Webseite
pooyanjamshidi.github.io/
Info
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.
Tags
machine learning
cloud architecture
transfer learning
self-adaptive software
performance tuning
highly configurable software
configuration optimization
devops
artificial intelligence
big data
cloud computing
software engineering
software architecture
uncertainty
auto-scaling
machine learning systems
performance analysis
performance engineering
apache storm
apache cassandra
microservices
migration pattern
elasticity
ai
causality
causal inference
systems
robotics
model learning
model prediction
predictive models
bayesian optimization
response surface
stream processing system
design of experiment
apache kafka
apache hadoop
gaussian process
fuzzy control
cloud resource provisioning
adaptive system
autonomic computing
multi-cloud
cloud architecture pattern
windows azure
cloud migration
software architecture evolution
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
dynamic resource provisioning
amazon cloud
application modernization
openstack
google cloud
cloud design pattern
method engineering
elastic software
evidence-based and empirical study
systematic literature review
architecture-centric software evolution
software evolution
change pattern
pattern-based software evolution
model driven development
Mehr anzeigen