Summary
Overview
Work History
Education
Skills
Accomplishments
Websites
Publications
Timeline
Generic

Kingsley Udeh

Hamden

Summary

Postdoctoral Research Data Scientist at Eversource Energy Center specializing in predictive modeling and web application deployment. Developed over five power outage prediction models to support data-driven decision-making. Expertise in machine learning and data visualization, with a strong history of collaborative research and innovative solutions. Enhanced utility operations through advanced algorithms, significantly improving outage prediction accuracy.

Overview

7
7
years of professional experience

Work History

Postdoctoral Research Data Scientist

Eversource Energy Center, UConn
Storrs
10.2022 - Current
  • Performed exploratory analysis on large datasets using R and Python libraries, such as Data Frame, Geopandas, and TMAPS.
  • Developed machine learning algorithms and methods to predict electric utility trouble spots.
  • Integrated trained outage-predicted models into web applications using TMAPS and Leaflet frameworks.
  • Deployed trained outage predictive models into the production system.
  • Followed industry innovations and emerging trends through scientific articles, conference papers or self-directed research.

Reasearch and Graduate Assistant

University of Connecticut
Storrs
02.2018 - 10.2024
  • Facilitated communication between faculty members, departmental staff, and students through continual system support.
  • Collaborated with other researchers from various fields in the research and publication of research papers and conference presentations on power outage-related topics.
  • Performed a significant managerial role in overseeing the user management of a department-wide software application for academic and research purposes.
  • Provided quality IT support services for day-to-day academic, research, and administrative activities to a broad range of faculty, staff, and students.

Education

Ph.D. - Computer Science & Engineering

Univrsity of Connecticut
Storrs
12-2022

Skills

  • Machine learning
  • Data visualization
  • Statistical analysis
  • Predictive modeling
  • Web application development
  • Research collaboration

Accomplishments

  • Outdoor activities and community-based activities
  • Volunteer - Google, American Red Cross
  • Member, IEEE Young Professionals

Publications

  • K. Udeh, D. W. Wanik, D. Cerrai, E. N. Anagnostou and D. Aguiar, "Probabilistic Storm and Electric Utility Customer Outage Prediction," in IEEE Access, vol. 12, pp. 126285-126295, 2024, doi: 10.1109/ACCESS.2024.3446311.
  • K. Udeh, D. W. Wanik, D. Cerrai, D. Aguiar and E. Anagnostou, "Autoregressive Modeling of Utility Customer Outages with Deep Neural Networks," 2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC), 2022, pp. 0406-0414, doi: 10.1109/ CCWC54503.2022.9720799.
  • K. Udeh, D. W. Wanik, N. Bassill and E. Anagnostou, "Time Series Modeling of Storm Outages with Weather Mesonet Data for Emergency Preparedness and Response," 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York City, NY, USA, 2019, pp. 0499-0505, doi:10.1109/UEMCON47517.2019.8992951.

Timeline

Postdoctoral Research Data Scientist

Eversource Energy Center, UConn
10.2022 - Current

Reasearch and Graduate Assistant

University of Connecticut
02.2018 - 10.2024

Ph.D. - Computer Science & Engineering

Univrsity of Connecticut