Research & Innovation

Advancing AI research in web security automation and pharmaceutical quality assurance

Active

AI-Powered Web Vulnerability Detection

Advanced machine learning models that identify complex web application vulnerabilities including SQL injection, XSS, and authentication bypass.

Web SecurityML DetectionPenetration Testing
Active

NLP for Pharmaceutical Compliance

Natural language processing algorithms to automatically review and validate batch records against FDA and GMP regulations.

NLPPharma QACompliance
In Progress

Deep Learning for Code Analysis

Training deep neural networks to understand code patterns and identify security vulnerabilities during development.

Code AnalysisDeep LearningDevSecOps
Active

Automated Quality Trend Analysis

Machine learning systems that detect quality trends and predict batch failures before they occur in pharmaceutical manufacturing.

Predictive AnalyticsQuality ControlManufacturing
Research

Real-Time Threat Intelligence

Aggregating and analyzing global threat data to provide real-time vulnerability updates for web applications.

Threat IntelReal-TimeSecurity
Active

Explainable AI for QA Decisions

Making AI quality assurance decisions transparent and interpretable for regulatory compliance and audit trails.

Explainable AITransparencyCompliance

Publications & Papers

Our research is published in leading conferences and journals

OWASP AppSec 2024
AI-Driven Vulnerability Detection
PharmaLab Conference
AI in Quality Assurance Automation
IEEE AI & Security
Neural Networks for Code Analysis

Interested in Collaboration?

We welcome partnerships with academic institutions and research organizations

Get in Touch