AI/ML Engineer & Data Scientist
I build intelligent systems that are not only smart and scalable, but also secure and production-ready. Passionate about AI Security, Federated Learning, and Cloud-Native ML Pipelines, I deliver real-world, high-impact AI solutions that solve complex challenges at scale.
I specialize in building intelligent systems across multiple domains
Basic Qualification and Certifications
Work, Internship and Volunteership
As the Vice President of FORCES (Forum of Computer Engineering Students) at PES College of Engineering, I played a pivotal role in leading and coordinating a wide range of technical events, seminars, and student engagement activities. My responsibilities included planning and executing national-level coding competitions, workshops on emerging technologies such as AI, cybersecurity, and web development, as well as facilitating expert guest lectures and industry interaction sessions. I actively collaborated with faculty, industry professionals, and fellow students to ensure each event was impactful and educational. Under my leadership, FORCES saw increased student participation and recognition within and beyond the campus. Additionally, I spearheaded initiatives to foster innovation, such as hackathons and mini-project showcases, encouraging a culture of hands-on learning and technical excellence among the student community.
As a dedicated volunteer, I have successfully collected approximately ₹34,000 INR for the NGO through various fundraising initiatives and community outreach efforts. This amount reflects my commitment to supporting the organization's mission and making a positive impact on the lives of those in need. My involvement included engaging with donors, organizing awareness campaigns, and contributing to the planning and execution of fundraising events, all carried out on a voluntary basis.
A showcase of my work across AI/ML, web development, mobile apps, and open-source contributions
Advanced NLP models for healthcare data analysis achieving 90%+ accuracy using transformer architectures and explainable AI components.
Advanced security analytics system processing 10,000+ network flows per minute using distributed computing for real-time threat detection.
Deep learning system for detecting anomalies in manufacturing using CNN architectures with 95%+ accuracy in real-time processing.
Machine learning model predicting customer churn with 88% accuracy, helping businesses retain customers through targeted interventions.
Cross-platform mobile application using Flutter that tracks health metrics and provides AI-driven insights for personalized wellness recommendations.
Android application with speech recognition and NLP features to help users learn new languages through interactive conversations.
Scalable data pipeline processing millions of financial transactions with automated data quality checks and real-time analytics.
Time series forecasting model using LSTM networks to predict sales trends with 92% accuracy for retail businesses.
Advanced clustering analysis using K-means and DBSCAN to identify customer segments for targeted marketing campaigns.
Real-time fraud detection using ensemble methods and anomaly detection algorithms for financial transactions.
Research paper on assistive haptic technology solutions for people with disabilities, published in academic journal with practical implementations.
Research on novel defense strategies against adversarial attacks on machine learning models with focus on explainable AI and robustness.
Comprehensive analysis of privacy-preserving techniques in machine learning including differential privacy and secure multi-party computation.
Research on optimizing federated learning algorithms for improved convergence and reduced communication overhead in distributed environments.
Open-source Python library providing tools for testing and securing machine learning models against various attack vectors.
Comprehensive collection of LeetCode problem solutions with detailed explanations, multiple approaches, and complexity analysis.
Collection of fine-tuned transformer models for various NLP tasks, shared on Hugging Face with comprehensive documentation.
Repository of high-performing solutions from various Kaggle competitions with detailed notebooks and methodology explanations.
I am available on almost every social media. You can message me, I will reply within 24 hours.
hello@waquashashmi.com
Cambridge, UK
Available on request
ML, AI, React, Android, Cloud and Opensource Development
I like to document some of my experiences in professional career journey as well as some technical knowledge sharing.
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