Naif Alkhunaizi - Senior AI & Data Consultant

About

Senior AI consultant with proven expertise in transforming organizations through strategic AI implementation

Strategic AI Leadership

Leading AI transformation initiatives for clients, defining roadmaps that align technology with business objectives and deliver measurable outcomes.

Privacy-First Solutions

Specialized in Federated Learning and privacy-preserving ML techniques, ensuring data security while maximizing AI model performance and compliance.

Research & Innovation

Published researcher with 4+ peer-reviewed papers in top-tier conferences, bridging the gap between cutting-edge research and practical applications.

Key Achievements

Quantifiable impact delivered through innovative AI solutions

$50M+

Fraud Detected

Document Digitalization with RAG Systems

Publications

2nd

GITEX Runner-Up

Professional Recognition

Runner's Up - GITEX 2021 Technology Competition
2nd Place - Table Tennis Tournament (30 participants)

Certifications

AWS Cloud Practitioner Essentials
Leading Teams: Developing as a Leader
Machine Learning in Production (DeepLearning.AI)
Neural Networks and Deep Learning

Professional Experience

Progressive career building expertise in AI consulting and implementation

Senior AI Consultant

Infosys Consulting Jan 2025 - Present

Leading AI strategy and implementation for clients across multiple industries
Building and maintaining strong client relationships as trusted advisor for AI initiatives
Overseeing full lifecycle of AI projects from requirements gathering to deployment
Communicating technical findings to both technical and non-technical stakeholders

Data Scientist II

Mozn Feb 2024 - Jan 2025

Delivered data insights and AI models for clients across diverse industry verticals
Developed automation solutions for manual processes using NLP, CV, and classical ML
Optimized ML model performance and adapted solutions to evolving business requirements
Translated complex technical findings into actionable business recommendations

Co-founder/AI Engineer

WaZii Jan 2023 - Present

Co-founded WaZii, a platform for automated trading to users using sophisticated algorithms
Built algorithmic trading platform with enhanced U.S. stock market prediction accuracy
Implemented full-stack development with modern CI/CD pipelines and deployment strategies
Deployed production ML models with automated daily retraining using MLOps practices

Researcher/AI Engineer

MBZUAI Jan 2023 - Jan 2024

Conducted ML research and published findings in top-tier international conferences
Performed data cleaning, visualization, and analysis to support research initiatives
Deployed ML systems using integrated MLOps and DevOps best practices

Graduate Teaching Assistant

MBZUAI - Advanced Machine Learning Jan 2022 - May 2022

Facilitated lab sessions to deepen students' understanding of advanced ML concepts
Hosted office hours and answered student questions on complex topics
Supported course delivery for graduate-level machine learning curriculum

AI Engineer Intern

Lockheed Martin Jun 2021 - Aug 2021

Developed Computer Vision model for enhanced aircraft inspection using lifelong learning methods
Implemented Episodic Memory to prevent catastrophic forgetting with new data distributions
Utilized Agile methodology with daily standouts showing project progress
Project was successfully completed and tested by Lockheed Martin engineers

Data Analyst

Rand International School Feb 2020 - Oct 2020

Conducted comprehensive data quality assessments, identifying and rectifying anomalies and inaccuracies
Analyzed market trends and customer behavior using advanced statistical techniques on large datasets
Utilized Python and SQL to extract meaningful insights for data-driven decision-making
Enhanced data integrity resulting in improved accuracy and reliability for analysis

Undergraduate Teaching Assistant

ASU - Random Signals Analysis Aug 2019 - Dec 2019

Answered student questions during office hours
Graded quizzes and marked student assignments
Supported undergraduate students in understanding signal analysis concepts

Core Expertise

Comprehensive skill set spanning AI strategy, implementation, and research

Programming & Frameworks

Python C++ MATLAB JavaScript TensorFlow PyTorch Scikit-learn Pandas NumPy

Cloud & DevOps

AWS Amazon SageMaker Docker Git MLOps CI/CD Nginx Linux

AI Specializations

Federated Learning Computer Vision NLP Deep Learning Statistical Modeling Time Series

Tools & Platforms

Tableau Dataiku SQLite LaTeX Conda Arduino LTspice

Key Projects & Impact

Transformative AI solutions delivering measurable business value

$50M+ Impact

Fraud Detection in Government Bidding

Led development of AI-powered fraud detection system for governmental client, successfully identifying over $50M in fraudulent bidding activities and significantly improving transparency and compliance in procurement processes.

Machine Learning Government Fraud Detection Compliance

Document Digitalization with RAG

AI Contract Digitalization

Led comprehensive document digitalization initiatives using advanced NLP and OCR technologies, enabling efficient contract management, search capabilities, and automated analysis workflows.

NLP OCR Digital Transformation Automation

Legal Case Summarization Engine

Developed AI-driven system for legal case analysis and summarization, providing intelligent recommendations to assist legal teams in decision-making and documentation review processes.

NLP Legal Tech Summarization

Budget Forecasting using GFS Code

Built predictive algorithm for accurate GFS code classification, enabling precise budget estimations and financial planning for government operations and resource allocation.

Forecasting Government Financial Planning

Research Publications

Contributing to the advancement of AI through peer-reviewed research

Probing the Efficacy of Federated Parameter-Efficient Fine-Tuning of Vision Transformers for Medical Image Classification

DeCaF - MICCAI 2024 Conference Paper

Advanced federated learning techniques for medical image analysis with privacy preservation, focusing on parameter-efficient fine-tuning of Vision Transformers in healthcare applications.

FeSViBS: Federated Split Learning of Vision Transformer with Block Sampling

MICCAI 2023 Conference Paper

Novel approach to federated learning using Vision Transformers with optimized block sampling techniques for improved efficiency and performance in distributed learning scenarios.

FedSIS: Federated Split Learning with Intermediate Representation Sampling for Privacy-preserving Generalized Face Presentation Attack Detection

IEEE IJCB 2023 Conference Paper

Privacy-preserving face anti-spoofing solution using federated split learning architecture with intermediate representation sampling for enhanced security and generalization.

Suppressing Poisoning Attacks on Federated Learning for Medical Imaging

MICCAI 2022 Conference Paper

Defense mechanisms against adversarial attacks in federated medical imaging systems, ensuring robust and secure learning in healthcare AI applications.

Naif Tayseer Alkhunaizi

Upcoming Role

Co-founder