Parisa Kordjamshidi
Email:
kordjams@msu.edu
Phone:
(517) 355-8389
Room:
2140
Postal:
Engineering Building 428 S. Shaw Lane, East Lansing, MI 48824.
Departmental Page
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About me
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Software: Sual
Spatial Role Labeling
IHMC
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Courses
University of California Los Angeles
COM SCI-269: Current Topics in Artificial Intelligence: Neuro-symbolic Reasoning with Large Language Models (Fall 2025)
Michigan State University
CSE-895: Selected Topics on Large Language Models (Spring 2025)
CSE-404: Introduction to Machine Learning (Fall 2024)
CSE-891: Selected Topics on Large Language Models (Spring 2024)
CSE-842: Natural Language Processing (Fall 2023)
CSE-404: Introduction to Machine Learning (Spring 2023)
CSE-842: Natural Language Processing (Fall 2022)
CSE-404: Introduction to Machine Learning (Spring 2022)
CSE-842: Natural Language Processing (Fall 2021)
CSE-440: Introduction to AI (Spring 2021)
CSE-891: Structured Machine Learning and Natural Language Processing (Spring 2020)
CSE-440: Introduction to AI (Fall 2019)
Tulane University (2016-2019)
CMPS 4720/6720: Machine Learning (Spring 2019)
CMPS 1600: Intro to Computer Science II (Fall 2018)
CMPS 4720/6720: Machine Learning (Spring 2018)
CMPS 3240/6240: Introduction to Machine Learning (Fall 2017)
CMPS 4720/6720: Machine Learning (Spring 2017)
CMPS 3240/6240: Introduction to Machine Learning (Fall 2016)
2015 and Earlier
UIUC, CS446: Machine learning, two guest lectures on Learning Based Java (Fall 2015)
KU Leuven, Text-based information retrieval, a guest lecture on structured output prediction, Master of Computer Science (Spring 2013)
KU Leuven, Machine Learning and Inductive Inference, teaching exercises, Master of Artificial Intelligence (2009-2012)
Ilam University & Shahid Chamran University (2000-2007)
Theory of machines and languages
Principles of data base design
System analysis and design
Machine learning
Machine language and system programming (assembly)
Advanced programming in c++
Programming in Pascal
Basics of computer programming
Digital circuits lab.
Database lab.
Supervision Principles