Mumbai (Maharashtra) [India], September 25: The biggest challenges in technology today aren’t just raw computing power; they’re about trust. Can a system defend against cyberattacks? Can it process massive data streams fast enough to save lives? And, perhaps most importantly, can it be designed so that everyone, no matter where they are, can use it? These are the questions that MD Shadman Soumik, a driven and innovative researcher, is determined to answer. His work connects artificial intelligence (AI), cybersecurity, and human-computer interaction, with a goal to design systems that are not just intelligent, but also resilient, ethical, and accessible to all.
From Circuits to Systems: A Path of Purpose
Soumik’s academic journey began with a Bachelor’s in Electrical and Electronic Engineering from North South University, Bangladesh (2017). This gave him a solid foundation in hardware, shaping how he approaches technology at its core. His perspective broadened during his Master’s in Information Technology at Washington University of Science and Technology, Virginia (2025). He learned that designing advanced systems wasn’t enough; they must also be secure, trustworthy, and usable for people worldwide, including those in regions with fewer resources.
Industry Lessons in Resilience
From 2020 to 2022, Soumik worked as an IT System Engineer and Data Security Specialist at Frontier Semiconductor in Dhaka. There, he managed critical IT infrastructure, protected intellectual property, and developed disaster recovery strategies to keep global operations running smoothly. More importantly, he worked closely with people—training teams to make security awareness a habit. This blend of technical expertise and human-centered thinking has shaped his research philosophy, showing that the strongest systems are those that integrate technology and people effectively.
Research With Global Impact
Soumik’s research isn’t confined to theory; it’s about solving real-world problems in healthcare, finance, and cybersecurity. His work sits at the intersection of AI, security, and usability, delivering solutions that have tangible global benefits:
1. Designing Secure and Usable Systems: The Intersection of Human-Computer Interaction, Cybersecurity, and Machine Learning
Journal: International Journal of Computer Applications, Foundation of Computer Science (FCS), NY, USA
Vision and Global Impact:
Soumik’s research addresses the challenge of balancing cybersecurity with user-friendly design. It envisions systems that protect without overwhelming users, which is crucial in regions with low digital literacy. By combining machine learning and human-computer interaction, his approach ensures accessibility, trust, and security across various global contexts.
Output Result:
The study found that the Convolutional Neural Network (CNN) model outperformed others, achieving 95.3% accuracy, 94.5% precision, and 96% recall. The user-friendly security system resulted in high satisfaction scores (4.7), trust (4.9), and a low false alarm rate of 2.1%, demonstrating the real-world applicability of secure, usable systems. The research highlights the potential of CNNs to enhance cybersecurity while maintaining usability, paving the way for more inclusive digital environments.
Read the full paper
2. Applying Artificial Intelligence for Enhanced Precision in Early Disease Diagnosis from Healthcare Dataset Analytics
Conference: 2025 3rd International Conference on Data Science and Information System (ICDSIS)
Vision and Global Impact:
The research demonstrates how AI can revolutionize healthcare by enabling early disease detection. Particularly in regions with limited healthcare infrastructure, AI can provide a vital tool for early diagnosis, improving outcomes and reducing medical costs on a global scale.
Output Result:
The Bi-LSTM model outperformed traditional models, achieving 98.85% accuracy, 98% precision, 94% recall, and 96% F1-score. This demonstrates the significant potential of machine learning in diagnosing diseases like diabetes early, offering hope for better healthcare delivery worldwide.
3. A Comparative Analysis of Network Intrusion Detection (NID) Using Artificial Intelligence Techniques for Increased Network Security
Journal: International Journal of Science and Research Archive (IJSRA), 2024
Vision and Global Impact:
Soumik’s research in network intrusion detection seeks to enhance global cybersecurity by using AI to detect and mitigate network threats. The ability to safeguard critical infrastructure worldwide—from financial systems to energy grids—has direct implications for global stability and security.
Output Result:
The Random Forest (RF) model achieved an impressive 99.90% accuracy, 97.78% precision, and 97.08% recall. This performance surpassed other models like Decision Tree, Stacked LSTM, and AdaBoost, making RF an ideal tool for real-time network intrusion detection. Future work will refine feature engineering and explore hybrid AI models to improve detection capabilities.
4. Enhanced Network Anomaly Detection Using Convolutional Neural Networks in Cybersecurity Operations
Journal: International Journal of Computer Applications, Foundation of Computer Science (FCS), NY, USA
Vision and Global Impact:
The study advances network anomaly detection, crucial for protecting sensitive data and maintaining cybersecurity in an increasingly interconnected world. With growing cyber threats, Soumik’s work aims to fortify global networks and secure digital infrastructures, providing real-time solutions for industries worldwide.
Output Result:
The CNN model demonstrated a high accuracy rate of 96% in anomaly detection, significantly improving the ability to identify threats in real-time. This system, tested in both offline and online modes, shows the practical application of deep learning models in real-world cybersecurity operations.
Read the full paper
5. Prediction of the Financial Stock Market: A Comprehensive Analysis of Artificial Intelligence
Journal: International Journal of Advanced Research in Science, Communication and Technology (IJARSCT), 2024
Vision and Global Impact:
Soumik’s research aims to stabilize global financial markets by using AI to predict stock market trends. By providing accurate predictions, his work could reduce risks, guide smarter investments, and support both large institutions and individual investors in making informed decisions worldwide.
Output Result:
The LSTM model achieved the highest accuracy at 93%, outperforming other machine learning models like ANN, CNN, and KNN. This success in predicting stock market fluctuations demonstrates the potential of AI to enhance financial forecasting and investment strategies on a global scale.
Recognition and Rising Influence
In recognition of his contributions, Soumik received the “Excellent & Dedicated Professional Achievement Award – 2025” under Dr. C. V. Raman Excellence in Education Awards. This accolade highlights his growing influence as a young researcher combining academic rigor with real-world impact.
Vision of a Younger Researcher
Soumik envisions a world where AI systems are trustworthy, ethical, and inclusive—strengthening digital infrastructure, democratizing healthcare, and supporting fairer financial systems worldwide. His mission is clear: to build technology that is secure by design but simple enough for everyone to use, ensuring that breakthroughs in AI and cybersecurity benefit all nations, not just the most developed.
“Smarter systems are only meaningful when they are safe and trusted. My mission is to create technology that protects, empowers, and includes everyone.” — MD Shadman Soumik
He sees technology as a global equalizer, but only if researchers and policymakers prioritize accessibility and equity. Soumik’s work addresses critical points in modern systems—cyber defense, healthcare diagnostics, and economic forecasting—fields that directly impact global stability and quality of life. By creating resilient, usable, and inclusive solutions, he is helping shape a future where intelligent systems are not only advanced but also reliable, ethical, and empowering for people everywhere.
