CV

Education

• Ph.D. in Electrical Engineering, North Carolina A&T State University, 2018-2022
  • Dissertation: “A Novel Clustering-based Online Learning Framework for Data Streams”
• M.S. in Electrical Engineering, North Carolina A&T State University, 2016-2018
  • Thesis: “Knowledge Acquisition from Streaming Data through a Novel Dynamic Clustering Algorithm”
• B.S. in Electrical Engineering, North Carolina A&T State University, 2014-2016
  • Senior Design Project: “Multi-robot Coordination and Collaboration for Humanoid Darwin Robots”

Work experience

• Feb. 2023 - Present: Workforce Analytics, Applied AI/ML Associate Sr.
  • JP Morgan Chase Co., Plano, TX
  • Duties:
    • Developed fairness-aware AI-based recommender systems for business applications (job recommendations) using structured and unstructured data.
    • Designed end-to-end NLP pipelines for topic mining in unstructured text data.
    • Implemented multi-label topic classification and online topic modeling pipelines.
    • Leveraged large language models (LLMs) for topic summary generation and quality checks.
• Aug. 2018 - Dec. 2022: Research Assistant
  • North Carolina A&T State University, Greensboro, NC
  • Advisor: Dr. Abdollah Homaifar
  • Duties:
    • Developed online machine learning techniques for autonomous vehicles.
    • Designed frameworks for feature selection and anomaly detection.
    • Conducted research on clustering-based active learning and non-stationary data streams.
• 2016-2018: Research Assistant
  • North Carolina A&T State University, Greensboro, NC
  • Advisor: Dr. Abdollah Homaifar
  • Duties:
    • Developed clustering algorithms for streaming data analysis.
    • Designed offline feature selection methods for high-dimensional data.

Skills

• Machine Learning
  • Clustering algorithms
  • Active learning
  • Deep learning
• Data Analysis
  • High-dimensional data analysis
  • Feature selection
• Autonomous Systems
  • Sensor fault diagnostics
  • Anomaly detection
• Programming Languages:
  • Python, R, SQL, C++, MATLAB, SAS, AWS, Google Colab, Massive Online Analysis (MOA), Apache Spark, Hadoop, VHDL, Git, Microsoft Office.
• Python basic packages
  • Scikit-learn, Numpy, Pandas, Pytorch, NLTK, Matplotlib, Transformers, Sentence-Transformer, Tensor- flow, Keras, Seaborn, Scipy, Orange3.

Publications

A data-driven approach for performance evaluation of autonomous evtols

Sarkar, M., Yan, X., Gebru, B., Nuhu, A. R., Gupta, K. D., Vamvoudakis, K. G., & Homaifar, A. (2024). A data-driven approach for performance evaluation of autonomous evtols. IEEE Transactions on Aerospace and Electronic Systems.

Human Stone Toolmaking Action Grammar (HSTAG): A Challenging Benchmark for Fine-grained Motor Behavior Recognition

Liu, C., Yan, X., Zhang, Z., Ding, C., Zhao, T., Jannati, S., ... & Stout, D. (2024, October). Human Stone Toolmaking Action Grammar (HSTAG): A Challenging Benchmark for Fine-grained Motor Behavior Recognition. In 2024 IEEE 11th International Conference on Data Science and Advanced Analytics (DSAA) (pp. 1-8). IEEE.

An Efficient Profit-Aware Scalable Vehicle Dispatch Framework for On-Demand Ridesharing

Lartey, B., Bedada, W., Yan, X., Homaifar, A., Karimoddini, A., & Tunstel, E. (2024). An Efficient Profit-Aware Scalable Vehicle Dispatch Framework for On-Demand Ridesharing. IEEE Transactions on Industrial Cyber-Physical Systems.

NCAT12-DET: A New Benchmark Dataset for Surface Defect Detection and a Comparative Study

Gyimah, N. K., Akinie, R., Yan, X., Nabil, M., Gupta, K. D., Homaifar, A., ... & Opoku, D. (2024). NCAT12-DET: A New Benchmark Dataset for Surface Defect Detection and a Comparative Study. IEEE Access.

An online learning framework for sensor fault diagnosis analysis in autonomous cars

Yan, X., Sarkar, M., Lartey, B., Gebru, B., Homaifar, A., Karimoddini, A., & Tunstel, E. (2023). An online learning framework for sensor fault diagnosis analysis in autonomous cars. IEEE Transactions on Intelligent Transportation Systems.

A discriminative deeplab model (ddlm) for surface anomaly detection and localization

Gyimah, N. K., Gupta, K. D., Nabil, M., Yan, X., Girma, A., Homaifar, A., & Opoku, D. (2023, March). A discriminative deeplab model (ddlm) for surface anomaly detection and localization. In 2023 IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC) (pp. 1137-1144). IEEE.

Interpretable convolutional learning classifier system (C-LCS) for higher dimensional datasets

Owens, J., Gupta, K. D., Yan, X., Zeleke, L. A., & Homaifar, A. (2022, October). Interpretable convolutional learning classifier system (C-LCS) for higher dimensional datasets. In 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 846-853). IEEE.

A Data-driven Approach for Travel Time Prediction and Analysis

Lartey, B., Zeleke, L., Yan, X., Gupta, K. D., Homaifar, A., & Karimoddini, A. (2022, October). A Data-driven Approach for Travel Time Prediction and Analysis. In 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 834-839). IEEE.

A clustering-based active learning method to query informative and representative samples

Yan, X., Nazmi, S., Gebru, B., Anwar, M., Homaifar, A., Sarkar, M., & Gupta, K. D. (2022). A clustering-based active learning method to query informative and representative samples. Applied Intelligence, 52(11), 13250-13267.

A comprehensive eVTOL performance evaluation framework in urban air mobility

Sarkar, M., Yan, X., Girma, A., & Homaifar, A. (2022, August). A comprehensive eVTOL performance evaluation framework in urban air mobility. In Proceedings of SAI Intelligent Systems Conference (pp. 459-474). Cham: Springer International Publishing.

An online unsupervised streaming features selection through dynamic feature clustering

Yan, X., Homaifar, A., Sarkar, M., Lartey, B., & Gupta, K. D. (2022). An online unsupervised streaming features selection through dynamic feature clustering. IEEE Transactions on Artificial Intelligence, 4(5), 1281-1292.

Identifying Anomalous Flight Trajectories by leveraging ensembled outlier detection framework

Forney, M., Yan, X., Gupta, K. D., Mahmoud, M. N., & Homaifar, A. (2022, July). Identifying Anomalous Flight Trajectories by leveraging ensembled outlier detection framework. In 2022 International Joint Conference on Neural Networks (IJCNN) (pp. 1-8). IEEE.

Mitigating shortage of labeled data using clustering-based active learning with diversity exploration

Yan, X., Nazmi, S., Gebru, B., Anwar, M., Homaifar, A., Sarkar, M., & Gupta, K. D. (2022). Mitigating shortage of labeled data using clustering-based active learning with diversity exploration. arXiv preprint arXiv:2207.02964.

Multi-label classification with local pairwise and high-order label correlations using graph partitioning

Nazmi, S., Yan, X., Homaifar, A., & Anwar, M. (2021). Multi-label classification with local pairwise and high-order label correlations using graph partitioning. Knowledge-Based Systems, 233, 107414.

A novel search and survey technique for unmanned aerial systems in detecting and estimating the area for wildfires

Sarkar, M., Yan, X., Erol, B. A., Raptis, I., & Homaifar, A. (2021). A novel search and survey technique for unmanned aerial systems in detecting and estimating the area for wildfires. Robotics and Autonomous Systems, 145, 103848.

A supervised feature selection method for mixed-type data using density-based feature clustering

Yan, X., Sarkar, M., Gebru, B., Nazmi, S., & Homaifar, A. (2021, October). A supervised feature selection method for mixed-type data using density-based feature clustering. In 2021 IEEE International conference on systems, man, and cybernetics (SMC) (pp. 1900-1905). IEEE.

DA2-Net : Diverse & Adaptive Attention Convolutional Neural Network

Girma, A., Homaifar, A., Mahmoud, M. N., Yan, X., & Sarkar, M. (2021, October). DA 2-Net: Diverse & Adaptive Attention Convolutional Neural Network. In 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 1906-1912). IEEE.

A framework for testing and evaluation of operational performance of multi-UAV systems

Sarkar, M., Yan, X., Nateghi, S., Holmes, B. J., Vamvoudakis, K. G., & Homaifar, A. (2022). A framework for testing and evaluation of operational performance of multi-UAV systems. In Intelligent Systems and Applications: Proceedings of the 2021 Intelligent Systems Conference (IntelliSys) Volume 1 (pp. 355-374). Springer International Publishing.

A niching framework based on fitness proportionate sharing for multi-objective genetic algorithm (moga-fps)

Nuhu, A. R., Yan, X., Opoku, D., & Homaifar, A. (2021, July). A niching framework based on fitness proportionate sharing for multi-objective genetic algorithm (moga-fps). In Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 191-192).

A clustering-based framework for classifying data streams

Yan, X., Homaifar, A., Sarkar, M., Girma, A., & Tunstel, E. (2021). A clustering-based framework for classifying data streams. arXiv preprint arXiv:2106.11823.

Evolving multi-label classification rules by exploiting high-order label correlations

Nazmi, S., Yan, X., Homaifar, A., & Doucette, E. (2020). Evolving multi-label classification rules by exploiting high-order label correlations. Neurocomputing, 417, 176-186.

An efficient unsupervised feature selection procedure through feature clustering

Yan, X., Nazmi, S., Erol, B. A., Homaifar, A., Gebru, B., & Tunstel, E. (2020). An efficient unsupervised feature selection procedure through feature clustering. Pattern Recognition Letters, 131, 277-284.

Driver identification based on vehicle telematics data using LSTM-recurrent neural network

Girma, A., Yan, X., & Homaifar, A. (2019, November). Driver identification based on vehicle telematics data using LSTM-recurrent neural network. In 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI) (pp. 894-902). IEEE.

A novel streaming data clustering algorithm based on fitness proportionate sharing

Yan, X., Razeghi-Jahromi, M., Homaifar, A., Erol, B. A., Girma, A., & Tunstel, E. (2019). A novel streaming data clustering algorithm based on fitness proportionate sharing. IEEE Access, 7, 184985-185000.

Unsupervised feature selection through fitness proportionate sharing clustering

Yan, X., Homaifar, A., Awogbami, G., & Girma, A. (2018, October). Unsupervised feature selection through fitness proportionate sharing clustering. In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 1355-1360). IEEE.

Multi-label classification using genetic-based machine learning

Nazmi, S., Yan, X., & Homaifar, A. (2018, October). Multi-label classification using genetic-based machine learning. In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 675-680). IEEE.

An evidence theory based multi sensor data fusion for multiclass classification

Awogbami, G., Agana, N., Nazmi, S., Yan, X., & Homaifar, A. (2018, October). An evidence theory based multi sensor data fusion for multiclass classification. In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 1755-1760). IEEE.

A novel clustering algorithm based on fitness proportionate sharing

Yan, X., Homaifar, A., Nazmi, S., & Razeghi-Jahromi, M. (2017, October). A novel clustering algorithm based on fitness proportionate sharing. In 2017 IEEE International conference on systems, man, and cybernetics (SMC) (pp. 1960-1965). IEEE.

Talks

Human Stone Toolmaking Action Grammar (HSTAG): A Challenging Benchmark for Fine-grained Motor Behavior Recognition.

October 07, 2024

Conference proceedings talk at The 11th IEEE International Conference on Data Science and Advanced Analytics 2024., San Diego, CA

Mitigating shortage of labeled data using clustering-based active learning with diversity exploration

July 22, 2022

Conference proceedings talk at International Conference on Machine Learning Workshop on Adaptive Experimental Design and Active Learning in the Real World 2022, Baltimore, MA

A supervised feature selection method for mixed-type data using density-based feature clustering

October 10, 2021

Conference proceedings talk at IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC), Virtual at Zoom

A clustering-based framework for classifying data streams

August 19, 2021

Conference proceedings talk at International Joint Conference on Artificial Intelligence (IJCAI) 2021, virtual at Zoom

Service and leadership

• Peer Reviewer:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • IEEE Transactions on Knowledge and Data Engineering
  • IEEE Transactions on Neural Network and Learning Systems
  • IEEE Transactions on Intelligent Transportation Systems
  • IEEE Transactions on Industrial Informatics
  • IEEE Transactions on Evolutionary Computation
  • IEEE/CAA Journal of Automatica Sinica
  • IEEE Transactions on Multimedia
  • IEEE Transactions on Big Data
  • IEEE Transactions on Systems, Man and Cybernetics: Cybernetics
  • IEEE Transactions on Systems, Man and Cybernetics: Systems
  • IEEE Transactions on Emerging Topics in Computational Intelligence
  • IEEE Transactions on Signal Processing
  • IEEE Transactions on Intelligent Vehicles
  • IEEE Transactions on Information Forensics & Security
  • IEEE Transactions on Artificial Intelligence
  • IEEE Transactions on Fuzzy Systems
  • IEEE Sensors
  • IEEE Access
  • ACM Computing Survey
  • Expert Systems with Applications, Elsevier
  • Swarm and Evolutionary Computation, Elsevier
  • Engineering Applications of Artificial Intelligence, Elsevier
  • Journal of King Saud University - Computer and Information Sciences, Elsevier
  • Neurocomputing, Elsevier
  • Knowledge-based Systems, Elsevier
  • Computers & Security, Elsevier
  • PeerJ Computer Science
  • Journal of Intelligent & Fuzzy Systems, Springer Nature
• Conference Services:
  • IEEE International Conference on Data Science and Advanced Analytics (DSAA) 2024 Special Session on Computational Imaging, Vision, and Language (CIVIL): Presenting Chair
  • International Joint Conference on Artificial Intelligence (IJCAI) 2025: PC Member
  • European Conference on Artificial Intelligence (ECAI) 2025: PC Member
• Professional Memberships:
  • IEEE Member
  • IEEE Society of Systems, Man, and Cybernetics