Paula Lauren

Assistant Professor, Department of Mathematics and Computer Science

College of Arts and Sciences, Lawrence Technological University, Southfield, Michigan, USA

+1 (248) 204-3653
plauren@ltu.edu

Office: S121D

Google Scholar: https://scholar.google.com/citations?user=Orb_5tQAAAAJ&hl=en&oi=ao




About Me

In 2018, I successfully earned a Ph.D. in Computer Science from Oakland University. With a rich background encompassing more than a decade of full-time industry experience in computing, my roles have spanned from computer programmer to software engineering manager.

I am deeply engaged in academia, where I take pride in teaching database systems at both the undergraduate and graduate levels. I am particularly passionate about MCS 1243, a foundational computer science course that I designed and developed. Additionally, I have also created and refined the course on Text Mining and Analytics that will be taught for the six consecutive year in Fall 2023.

My research interests are primarily focused on data (text) mining, information extraction, natural language processing, and computer science education. Furthermore, I am keenly interested in exploring interdisciplinary research opportunities, particularly with cognitive psychology and the humanities.

As an actively contributing member of the academic community, I regularly review peer journal papers. Moreover, I maintain my professional affiliations with esteemed organizations such as ACM, IEEE, and Sigma Xi, where I continue to enhance my knowledge and contribute to the advancement of the field.

Research Interests

Data Mining

The delineation between types of data is often regarded as unstructured, structured, and semi-structured with the latter being a combination of unstructured and structured data. Data mining contains methods to be used for predictive analysis on structured data, such as classification and clustering. There is a plethora of numerical data such as financial and genetic data, to name just a few.  I'm interested in ways to improve the interpretation of these models especially with neural networks, which is regarded for the most part as a black box. 

Information Extraction

Information extraction is primarily concerned with methods to extract meaningful data from text.  There are many sub-problems in this space with overlap in natural language processing. Some problems involve Named Entity Recognition and Word Sense Disambiguation. I'm interested in automatically identifying entities from text using various types of data  and statistical methods. 

Natural Language Processing

Natural Language Processing is regarded as a sub-field in artificial intelligence pertaining to the interaction between humans and the computer in the form of natural language. My interest is in conversational user interfaces using custom and open source approaches. 

Text Mining

Text mining is a sub-field within data mining, which also incorporates information extraction and natural language processing.  One of the key differences between text mining and data mining pertains to the initial data representation. With text mining the data is typically unstructured and has to be put into a numerical representation for processing. My interest is in text categorization and text summarization, as well as question answer systems.

Computer Science Education

Computer science is an exciting and challenging field. I'm interested in exploring ways to improve the delivery of computing especially to undergraduate students.  Some approaches incorporate project-based and active-learning.  

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I'm interested in working with computer science students in any of the aforementioned research areas. Please reach out to me and let me know what area(s) you are interested in pursuing.  Note that at LTU, we do have a limited about of Graduate Research Student Assistantships for graduate students, as well.   

Research Project Highlight

A Conversational User Interface for Stock Analysis

Utilizing open source toolkits,  financial API's, and customized Python scripts. 

Presented at IEEE Big Data                                          December 2019, Los Angeles, California

Top image(top)  illustrates a high level overview of the system. The image(bottom) illustrates the stockbot application with an example interaction for the stock history module of the system. 

 

Teaching

MCS1243 Foundations of Computer Science

Foundational knowledge of computing concepts from algorithms to artificial intelligence.

MCS1142 - Introduction to C

Fundamentals of C programming from variables to pointers.

MCS1514 - Computer Science I

Fundamentals of object-oriented programming using C++. 

MCS 4993/ MCS5993 Special Topics: Text Mining & Analytics

Text Mining concepts from numeric representations of text to methods such as text categorization and clustering.

MCS 3543/MCS 5303 Introduction to Database Systems

Introduction to relational database system concepts including theoretical aspects using relational algebra/calculus along with application using SQL in a database administration environment.


Education

Doctor of Philosophy in Computer Science and Informatics

School of Engineering and Computer Science, Oakland University, Rochester, Michigan

Ph.D. Thesis:  Optimization of Word Embeddings in Text Categorization

Master of Science in Computer and Information Science 

College of Engineering and Computer Science, The University of Michigan-Dearborn

Bachelor of Science in Business - Management Information Systems

School of Business, Wayne State University, Detroit, Michigan

Associate in Arts

Oakland Community College, Royal Oak, Michigan

Current Interests

            https://openai.com/

 

          https://opennlp.com/

© Copyright Paula Lauren