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ALINA LAZAR
Software Engineering (SE)
Machine Learning Algorithms For Software Engineering Datasets
Scalable Machine Learning For Large Datasets
Machine Learning Applications In Scientific Datasets
About
Dr. Alina Lazar is a professor in the department of computer science and information systems at Youngstown State University. Her research interests lie at the intersection between machine learning and data mining. Lately, she has been working on applying machine learning algorithms to software engineering related datasets and other scientific datasets. She is also interested in adapting learning algorithms to scale well in order to deal with large real data sets.
Research Performance Summary
1999-2025
Active Research Span
First Recorded Paper
Decision rule extraction from trained neural networks using rough sets
Year:
1999
Citations:
10
Venue:
Intelligent Engineering Systems Through Artificial Neural Networks 9
Latest Recorded Paper
Scaling Graph Neural Networks for Particle Track Reconstruction
Year:
2025
Citations:
0
Venue:
2025 IEEE International Parallel and Distributed Processing Symposium
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.
Publication Venues and Collaboration
Journal, Conference, and Book Publication Breakdown
Research Impact by Period
Papers
5
Citations
0
Avg. Citations / Paper
0
H-Index
0
Papers
31
Citations
299
Avg. Citations / Paper
9.6
H-Index
9
Papers
16
Citations
289
Avg. Citations / Paper
18.1
H-Index
7
Papers
9
Citations
291
Avg. Citations / Paper
32.3
H-Index
4
Papers
8
Citations
36
Avg. Citations / Paper
4.5
H-Index
4
Papers
11
Citations
163
Avg. Citations / Paper
14.8
H-Index
6
Papers
1
Citations
10
Avg. Citations / Paper
10
H-Index
1
Contact and Professional Links
Detected Research Keywords
Graph Neural Networks
Gnn Track Reconstruction
Exa Trkx Pipeline
Peachy Parallel Assignments
Data Machine Learning
Support Vector Machines
Heuristic Knowledge Discovery
Support Vector Machine
Classification Wireless Intrusion
Wireless Intrusion Detection