I’m Pranjul Shukla, a Computer Science professional driven by an enduring passion to explore and teach the answers born out of curiosity and logic. Having completed my Master of Computer Applications (MCA), I have developed strong expertise across Artificial Intelligence, Machine Learning, Deep Learning, and core programming languages such as C, C++, DSA and Python with core CS subjects.

My academic and project journey reflects my love for connecting theory with application. Notably, I developed a Driver Drowsiness Detection System that integrates CNN, OpenCV, and dlib—a project demonstrating both analytical depth and real-world relevance. I have also contributed to projects involving data analysis and intelligent automation, each designed to transform technical understanding into practical innovation.

As an educator, I strive to make Computer Science a subject of reasoning, not memorization. I take pride in simplifying complex concepts for students and inspiring them to approach technology as a language of problem-solving. My teaching focuses on helping learners build clarity, confidence, and creativity—qualities essential for future innovators.

Beyond teaching, I actively explore research in AI-based systems and continuously refine my pedagogy through student feedback, interdisciplinary learning, and emerging technologies. My ultimate goal is to nurture minds that think critically, code logically, and innovate meaningfully, bridging the gap between academic concepts and real-world impact.

Transforming the Computer Science classroom into a lab of logic, curiosity, and creativity.

• Focused on Artificial Intelligence, Machine Learning, and Deep Learning applications aimed at improving human safety, automation, and intelligent decision-making.
• Developed and patented the Driver Drowsiness Detection System, a deep learning-based solution using CNN, OpenCV, and dlib for real-time fatigue detection and accident prevention.
• Publication in process on computer vision–based alert systems and their role in enhancing road safety and human-computer interaction.
• Exploring research directions in AI-based emotion recognition, predictive analytics, and smart automation systems with real-world impact.
• Interested in applied research that bridges the gap between theoretical models and practical implementation.
• Research Interest
• Artificial Intelligence and Machine Learning
• Deep Learning and Neural Network Optimization
• Computer Vision and Human Behavior Analysis
• Real-Time Safety and Surveillance Systems
• Predictive Analytics and Data-Driven Automation

• Realistic Tech-idea pitch presentation -- A proven winner in high-stakes tech and business pitch competitions, I have repeatedly secured top awards and proposed funding for disruptive solutions. My expertise lies in synthesizing deep technical innovation (from AI-driven platforms to quantum-resistant security) with scalable, profitable business models, validating and championing ideas that solve major industry problems and capture significant market share.