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Dr. Lily Popova Zhuhadar

Dr. Lily Popova Zhuhadar

Director of the Center for Applied Data Analytics, Faculty Fellow for WKU Research & Creative Activity, and Associate Professor of Analytics & Information Systems. 

 

 

Awards

  • The 2023 GFCB Faculty Award for Research and Creativity 
  • The 2022 MBA Innovative Pedagogy Award
  • The 2022 GFCB Faculty Award for Teaching 
  • The 2021 GFCB Faculty Award for Student Advisement
  • The 2020 GFCB PRIDA Award 
  • The 2018 GFCB Faculty Award for Research and Creativity 
  • The 2017 GFCB PRIDA Award
  • The 2015 GFCB Dean Merits’ Award
  • The 2014 WKU Office of Sponsored Programs Award for the Most Prolific Grant Proposer by College.

Education

  • Doctor of Philosophy, in Computer Science and Computer Engineering, University of Louisville, December 2009

  • Master in Computer Science, Western Kentucky University, May 2004

Google Scholar Statistics

WKU Top Google Scholars can be accessed from the following link. Her Google ScholarProfile can be accessed from the following link. 

Biography

Dr. Zhuhadar is the Director of the WKU Center for Applied Data Analytics and an Associate Professor of Analytics and Information Systems. Her applied research focuses on collaborating with colleagues from various disciplines in the USA and Europe to solve contemporary big data problems using data mining methodologies.

Between 2014 and 2023, Dr. Zhuhadar has submitted more than 30 grant proposals, internally and externally, ranging from $3K to $2M.

As of February 8, 2023, she has been awarded 23 grants totaling around $300,000. 

The impact of her research is evident through her contributions to more than 60 publications in peer-reviewed journal articles, book chapters, and national/international conference proceedings.

She has published in many top-tier journals, including Computers in Human Behavior (Elsevier),  Journal of Ambient Intelligence and Humanized Computing (Springer), Journal of the Knowledge Economy (Springer), and Social Network Analysis and Mining (Springer). These publications have significantly impacted her ranking on Google Scholar (link). 

Dr. Zhuhadar is a fellow of several prestigious associations, including The Institute of Electrical and Electronics Engineers (IEEE), The IEEE Women in Engineering (WIE), The AACSB International, the Association for Information Systems (AIS), the Association for the Advancement of Artificial Intelligence (AAAI), and the Association for Computing Machinery (ACM).

AI & Cloud-based Platforms

Dr. Zhuhadar has an extensive track record of developing AI algorithms on cloud-based platforms. Here are some of her previous successes in designing these types of platforms:

From 2016 to 2019, Dr. Zhuhadar developed a Cloud-based Semantically Enriched Decision Support System to investigate the offshore databases leaked in the Panama Papers. She utilized Amazon Web Services to host the GraphDB server and linked it to approximately 2.7 billion DBPedia/GeoNames nodes/entities (refer to [1, 2]).

Between 2005 and 2015, she developed the HyperManyMedia1 (HMM) platform. HMM was the first MOOC platform at WKU and is considered the first worldwide Recommender System for Semantically Enriched Open Learning Resources. More than 800,000 students enrolled in HMM, contributing to over 30 articles, most of which are indexed in ACM and IEEE digital libraries (refer to [3-16]).

References

[1] L. Zhuhadar and M. Ciampa, "Leveraging learning innovations in cognitive computing with massive data sets: Using the offshore Panama papers leak to discover patterns," Computers in Human Behavior, vol. 92, pp. 507-518, 2019/03/01/ 2019, doi: https://doi.org/10.1016/j.chb.2017.12.013.

[2] L. P. Zhuhadar and M. Ciampa, "Novel findings of hidden relationships in offshore tax-sheltered firms: a semantically enriched decision support system," Journal of Ambient Intelligence and Humanized Computing, vol. 12, no. 4, pp. 4377-4394, 2021/04/01 2021, doi: https://doi.org/10.1007/s12652-019-01392-1.

[3] L. Zhuhadar and O. Nasraoui, "Augmented ontology-based information retrieval system with external open source resources," in Information Technology: New Generations (ITNG), 2010 Seventh International Conference on, 2010: IEEE, pp. 144-149. https://ieeexplore.ieee.org/document/5501440

[4] L. Zhuhadar, O. Nasraoui, and R. Wyatt, "Automated Discovery, Categorization and Retrieval of Personalized Semantically Enriched E-learning Resources," International Conference on Semantic Computing, vol. 0, pp. 414-419, 2009. https://ieeexplore.ieee.org/document/5298656

[5] L. Zhuhadar, O. Nasraoui, R. Wyatt, and E. Romero, "Cluster to User Profile Ontology Mapping," in S3T: the International Conference on SOFTWARE, SERVICES & SEMANTIC TECHNOLOGIES, Sofia, Bulgaria., October 28-29 2009.

[6] L. Zhuhadar, O. Nasraoui, and R. Wyatt, "Dual Representation of the Semantic User Profile for Personalized Web Search in an Evolving Domain," in Proceedings of the AAAI 2009 Spring Symposium on Social Semantic Web, Where Web 2.0 meets Web 3.0, 2009, pp. 84-89. 

[7] L. Zhuhadar, O. Nasraoui, and R. Wyatt, "A Comparsion Study Between Generic and Metadata Search Engines in an E-learning Environment," in IKE, 2008, pp. 500-505.

[8] L. Zhuhadar and R. Yang, "Cyberlearners and learning resources," in Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, 2012: ACM, pp. 65-68.

[9] L. Zhuhadar, E. Romero, and R. Wyatt, "The effectiveness of personalization in delivering e-learning classes," in Advances in Computer-Human Interactions, 2009. ACHI'09. Second International Conferences on, 2009: IEEE, pp. 130-135. https://ieeexplore.ieee.org/document/4782503

[10] L. Zhuhadar and O. Nasraoui, "Evaluating a Cross-Language Semantically Enriched Search Engine," in Information Technology: New Generations (ITNG), 2010 Seventh International Conference on, 2010: IEEE, pp. 1074-1079. https://www.computer.org/csdl/proceedings-article/itng/2010/3984b074/12OmNwDj0Wn

[11] L. Zhuhadar and O. Nasraoui, "Evaluating usability and precision of visual search engine," in Proceedings of the 2010 Spring Simulation Multiconference, New York, NY, USA, 2010: ACM, in SpringSim '10, pp. 239:1-239:4. [Online]. Available: http://doi.acm.org/10.1145/1878537.1878786.

[12] L. Zhuhadar, O. Nasraoui, and R. Wyatt, "Metadata as seeds for building an ontology driven information retrieval system," International Journal of Hybrid Intelligent Systems, vol. 6, no. 3, pp. 169-186, 2009. https://dl.acm.org/doi/abs/10.5555/1735964.1735969

[13] L. Zhuhadar, O. Nasraoui, and R. Wyatt, "Visual ontology-based information retrieval system," in Information Visualisation, 2009 13th International Conference, 2009: IEEE, pp. 419-426.

[14] L. Zhuhadar, R. Yang, and O. Nasraoui, "Toward the design of a recommender system: visual clustering and detecting community structure in a web usage network," in Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology-Volume 01, 2012: IEEE Computer Society, pp. 354-361. https://ieeexplore.ieee.org/abstract/document/6511908

[15] L. Zhuhadar, S. R. Kruk, and J. Daday, "Semantically enriched Massive Open Online Courses (MOOCs) platform," Computers in Human Behavior, vol. 51, pp. 578-593, 2015. https://doi.org/10.1016/j.chb.2015.02.067

[16] L. Zhuhadar, "A synergistic strategy for combining thesaurus-based and corpus-based approaches in building ontology for multilingual search engines," Computers in Human Behavior, vol. 51, pp. 1107-1115, 2015. https://doi.org/10.1016/j.chb.2015.03.021

Dr. Zhuhadar's Scholarly Profiles:

Dr. Zhuhadar's Google Scholar

Dr. Zhuhadar's Research Gate Profile

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 Last Modified 11/4/23