Eloghosa Anderson Ikponmwoba

Professional Summary

PhD researcher with 4+ years of experience bridging AI, energy optimization, and public safety. Expertise in developing AI solutions for complex engineering systems and digital forensics applications. Proven ability to innovate at the intersection of machine learning, scientific computing, and societal impact.

Currently focused on:

• Reinforcement learning for engineering design optimization
• AI-powered tools for child protection
• Contributing to INTERPOL’s global law enforcement initiatives

Education

Doctor of Philosophy in Mechanical Engineering

Louisiana State University | Louisiana, USA
January 2022 – December 2026 (Expected)

Research Focus: Engineering Design Optimization with Artificial Intelligence

Bachelor of Engineering in Mechanical Engineering

University of Benin | Benin City, Nigeria
November 2014 – December 2019

Thesis: Numerical evaluation of nanofluid models under different heat and flow conditions

Professional Experience

Graduate Research Assistant

Louisiana State University | Louisiana, USA
January 2022 — Present

Reinforcement Learning-Accelerated Combustion Systems

• Developed novel RL algorithms for adaptive CFD simulation control
• Achieved significant computational efficiency gains in combustion modeling
• Created intelligent solver parameter selection systems

DeepHive Optimization Framework

• Co-developed multi-agent reinforcement learning system for automated discovery of swarm-based optimization policies
• Published methodology demonstrates superior performance on engineering optimization benchmarks

AI-Enhanced Scientific Computing

• Integrated machine learning approaches with OpenFOAM for combustion CFD simulations
• Created adaptive workflows that intelligently adjust numerical methods based on real-time simulation states

Interdisciplinary Research Impact

• Applied machine learning to enhance Raman spectroscopy analysis for cancer cell detection

Summer Research Intern

Halliburton Energy Services | Texas, USA
May 2025 — August 2025

• Designed Graph Neural Network-based reinforcement learning system for reservoir field development optimization
• Engineered scalable training environment integrating proprietary simulation tools
• Developed multi-objective optimization frameworks for field development planning
• Filed patent application for novel deep reinforcement learning approach

Machine Learning Engineer

RIGR AI | Cork, Ireland
April 2021 — August 2022

Assessing Risk Indicators of Child Sexual Abuse (ARICA)

• Developed AI-based adaptive scrapers for dark web forums
• Supported international law enforcement agencies in child protection investigations

Government Contract AI Systems

• Engineered enterprise-grade semantic search engine for U.S. government contracts
• Processed millions of documents using VESPA AI

Advanced Text Summarization Platform

• Built scalable, serverless solution using AWS and Azure services
• Implemented GPU-accelerated LLM models

AI Researcher

Xigma Input and Output Technology | Benin City, Nigeria
November 2015 – September 2019

• Co-founded innovative research startup developing AI applications
• Trained ML algorithms for COVID-19 detection using advanced CNNs
• Developed comprehensive machine learning curriculum for 200+ students

Research Assistant

Onyiriuka Lab, University of Benin | Nigeria
March 2018 – December 2019

• Conducted numerical modeling for nanofluid heat transfer using ANSYS Fluent
• Developed ML models for predicting nanofluid heat transfer coefficients
• Published peer-reviewed research on nanofluid applications

Publications

Total Citations: 30+

1. Ikponmwoba, E., & Owoyele, O. (2024). “DeepHive: A multi-agent reinforcement learning approach for automated discovery of swarm-based optimization policies.” Algorithms, 17(11), 500.

2. Ikponmwoba, E., et al. (2022). “A Machine Learning Framework for Detecting COVID-19 Infection Using Surface-Enhanced Raman Scattering.” Biosensors, 12(8), 589. [18 citations]

3. Onyiriuka, E. J., & Ikponmwoba, E. A. (2019). “A numerical investigation of mango leaves-water nanofluid under laminar flow regime.” Nigerian Journal of Technology, 38(2), 348-354. [11 citations]

4. Levine, B., Kumar, J. J., Farid, H., Dixon, E., & Ikponmwoba, E. (2021). “Indication of Child Sexual Abuse Revealed in App Store.” SOUPS 2022 Workshop on Kids’ Online Privacy and Safety. [2 citations]

Patent Applications

OIL AND GAS FIELD DEVELOPMENT PLANNING USING A DEEP REINFORCEMENT LEARNING APPROACH WITH RESERVOIR-INVARIANT TRANSFER LEARNING
U.S. Patent Application Pending (2025)

Technical Skills

Programming & Tools

• Languages: Python, C++, SQL
• ML/AI: PyTorch, TensorFlow, Scikit-learn, Reinforcement Learning
• Scientific Computing: OpenFOAM, ANSYS Fluent, NumPy, SciPy
• Cloud & DevOps: AWS, Azure, Docker, Git
• Databases: VESPA AI, PostgreSQL

Specializations

• Deep Reinforcement Learning
• Graph Neural Networks
• Natural Language Processing
• Computer Vision
• CFD Simulation
• Optimization Algorithms

Awards & Recognition

• NASA Space Apps Challenge — Galactic Problem Solver (2020)
• APSA Science Challenge — Top 10 African Finalist, Ethiopia (2018)
• United Nations Academic Impact — Millennium Fellow (2018)
• Edo State/Siemens Energy Hackathon — Winner (2019)
• HULT Prize — Campus Champion & National Finalist (2017)
• Petroleum Trust Development Fund (PTDF) — Full Undergraduate Scholarship (2017-2019)

Professional Affiliations

• International Association of Engineers (IAENG) — Member
• Society of Petroleum Engineers (SPE) — Student Member
• American Physical Society (APS) - Member
• IEEE Computer Society — Member
• INTERPOL DevOps Community — Active Technical Contributor

Volunteer Experience

• INTERPOL DevOps Technical Working Group (2024 – Present)
• Crimes Against Children (CAC) Unit 14th DevOps Meeting — Arlington, VA (March 2025)
• 13th DevOps Meeting — Reading, UK (October 2024)

Editorial & Review Services

• Applied Soft Computing — Technical Reviewer
• Journal of Emerging Investigators — Technical Reviewer