Lamis Ghoualmi, PhD
Skills & Technologies
About Me
I am an AI & ML Solutions Engineer specializing in designing intelligent, scalable analytics systems that transform complex institutional data into actionable intelligence. I architect end-to-end data engineering pipelines and agentic AI solutions using Microsoft Fabric, Azure AI Foundry, and Power BI — embedding AI directly at the data foundation layer to drive enterprise-grade decision-making.
Holding a PhD in Computer Science awarded With High Honors, with a research foundation in bio-inspired AI, biometric authentication, and machine learning optimization, I bring rare depth to every system I build. My work spans healthcare analytics, environmental health data engineering, and enterprise AI integration across higher education institutions.
A published researcher across IEEE, Elsevier, and Springer with 160+ citations and an h-index of 6, and a recognized conference speaker with 5 professional IT presentations, I uniquely bridge rigorous academic research and hands-on enterprise AI engineering — translating cutting-edge AI advances into scalable, governed, production-ready systems.
Experience
Data & AI Solutions Engineer (Software Analyst III)
University of Tennessee, Knoxville · Full-time
- Designed and led end-to-end Project Management Dashboard development leveraging Microsoft Fabric architecture.
- Built and deployed multiple Power BI dashboards spanning Project Management, Enrollment Management, Human Resources, and more — providing actionable insights for decision-making.
- Developed robust ETL pipelines using Oracle Data Integrator (ODI), PL/SQL, and SQL Server; created data marts, views, procedures, and jobs for Oracle and SQL Server environments.
- Automated data workflows leveraging Fabric pipelines and ODI for efficient, scalable processing.
- Presented proof-of-concept projects and end-to-end architectures at internal symposiums and external conferences, showcasing AI and ML integration for higher education challenges.
- Partnered with operations, IT teams, and senior stakeholders to identify requirements, resolve data integration issues, and ensure seamless implementation of analytics solutions.
- Applied advanced data cleaning, transformation, and AI-driven analytics to enhance data integrity, generate predictive insights, and support strategic institutional decisions.
AI & ML Research Scientist (Biometrics & Healthcare Analytics)
University Abdelhamid MEHRI Constantine 2 · Contract
- Architected an end-to-end data engineering pipeline on the UCI Chronic Kidney Disease dataset; performed EDA to surface actionable insights and clinically relevant patterns.
- Designed and trained a deep learning model for kidney disease prediction, applying advanced feature engineering and model optimization to maximize diagnostic accuracy.
- Built automated ML pipelines for heart disease prognosis using the 2020 CDC dataset, engineering predictive features and fine-tuning classification architectures for clinical decision support.
- Engineered a multi-objective optimization framework for palm vein biometric authentication, jointly optimizing accuracy and feature vector compactness through a custom AI-driven loss function.
- Implemented bio-inspired metaheuristic optimizers (PSO, ABC) for hyperparameter tuning and feature subset selection.
Postdoctoral Research Associate (AI-Driven Environmental Exposome & Cardiovascular Health Analytics)
University of Tennessee, Knoxville · Contract
- Led end-to-end data engineering and ML pipeline on large-scale public health exposome (PHE) data at the Langston Laboratory, investigating environmental impacts on population health.
- Architected a robust preprocessing pipeline handling duplicates, missing values, outliers, and low-variance features.
- Designed an intelligent feature selection framework using Mutual Information and Decision Trees to identify statistically significant PHE variables.
- Applied Pearson correlation analysis to surface multicollinearity patterns and validate feature independence.
- Engineered a graph-theoretic paraclique representation layer providing a novel topological view of environmental feature interactions.
Assistant Professor
University Abdelhamid MEHRI Constantine 2 · Full-time
- Delivered lectures to sophomore and freshman students; advised multiple undergraduate students through their projects.
- Courses: Theory of Formal Languages, Multimedia Image Processing, Network Fundamentals, Introduction to Algorithmics.
Portfolio
This portfolio showcases selected projects spanning enterprise analytics, data science, machine learning, and AI engineering — drawn from professional work, academic research, and independent exploration. Several ongoing projects are not yet listed here.
Scientific Research Publications
Google ScholarTeaching Experience
View Page
Marketing dataset (Python, SQL, Tableau)
Customer Anaysis (Tableau)
Mexico Restaurant Ratings (SQL and Tableau)
SQL queries for diffrents projects.
upcoming project
DATA ANALYSIS PROJECTS
Telecom Customer Churn (Power Bi)
App: Exploratory Data Analysis App (Python)
Canvas Coockie Performance (Power Bi)
Human Ressource analysis (Power Bi)
App: Statistical description of a dataset for data cleanning (Python)
Covid 19 deaths visualization (Tableau)
Standard data cleanning (Python)
upcoming project
DATA SCIENCE PROJECTS
App: Chatbot made with openAI and streamlit (Python)
App: Translate natural language to SQL queries (Python)
App: Personal Key Indicators of Heart Disease, machine learning model (Python)
Chronic kidney disease prediction (Python)
Heart disease prediction (Python)
Diabetes prediction (Python)
Feature selection of load-digit dataset Python (Sklearn)
upcoming project
