AI Researcher | MSc AI (Distinction), University of Nottingham | Deep Learning ⚙️ | Explainable AI 🔍
- 🎓 MSc in Computer Science (AI) with Distinction — University of Nottingham
- 💼 Currently working as Machine Learning Engineer at IntelliDigest, Edinburgh
- 🧠 Researcher in Deep Learning, Explainable AI, IoT, and Secure Systems
- 🧑🔬 Past affiliations: Samsung R&D, Atheropoint (USA), Ministry of Rural Development (India)
- 📝 Final dissertation: MARes – Multi-Attentive Residual Loss Function for plant disease detection
- 📘 Developed XAI-based flood prediction, drone detection, and secure health protocols
- 💬 Ask me about: PyTorch, Vision Transformers, Secure AI, Super Resolution, Vision LLM, IoT
- 📫 How to reach me: jaskaran.jsk2001@gmail.com
- 🧩 Fun fact: I enjoy badminton 🏸 and hiking 🥾
- 🔬 MARes-Explainable-Plant-Disease-Identification – Novel multi-loss plant disease detection model with CAM/XAI
- 🩺 TAUSR-CO – Adaptive super-resolution for ultrasound imaging
- 🧠 FuzzyMedUrgency – Medical emergency classification using fuzzy logic and visual rules
- 🌾 IntelliDigest ML Platform – Nutritional recommendation and satellite-based crop detection
- 🥇 Winner, Smart India Hackathon 2022
- 🌍 Delegate, UNESCO India-Africa Hackathon
- 🧑🏫 Keynote Speaker, APVIC XV & ISWAB’23
- 🏅 Bank of Baroda National Achievers Award 2023
- 🎓 Developing Solutions Masters Scholarship – UoN
| Title | Journal / Conference |
|---|---|
| ASCP-IoMT: AI-enabled lightweight secure communication protocol for internet of medical things | IEEE Access |
| Machine learning security attacks and defense approaches for emerging cyber physical applications: A comprehensive survey | Computer Communications |
| SINN-RD: Spline interpolation-envisioned neural network-based ransomware detection scheme | Computers and Electrical Engineering |
| Security in IoMT-driven smart healthcare: A comprehensive review and open challenges | Security and Privacy (Wiley) |
| Attention-enabled ensemble deep learning models and their validation for depression detection: A domain adoption paradigm | Diagnostics |
| An ensemble-based machine learning-envisioned intrusion detection in industry 5.0-driven healthcare applications | IEEE Transactions on Consumer Electronics |
| Secure blockchain-enabled authentication key management framework with big data analytics for drones in networks beyond 5G applications | Drones |
| DermAI 1.0: A robust, generalized, and novel attention-enabled ensemble-based transfer learning paradigm for multiclass classification of skin lesion images | Diagnostics |
| An embedded LSTM based scheme for depression detection and analysis | Procedia Computer Science |
| Explainable artificial intelligence envisioned security mechanism for cyber threat hunting | Security and Privacy (Wiley) |
| GeneAI 3.0: powerful, novel, generalized hybrid and ensemble deep learning frameworks for miRNA species classification of stationary patterns from nucleotides | Scientific Reports (Nature) |
| A secure signature-based access control and key management scheme for fog computing-based IoT-enabled big data applications | Security and Privacy (Wiley) |
| An Ensemble-Based IoT-Enabled Drones Detection Scheme for a Safe Community | IEEE Open Journal of the Communications Society |
| Explainable Deep Learning-Enabled Malware Attack Detection for IoT-Enabled Intelligent Transportation Systems | IEEE Transactions on Intelligent Transportation Systems |
| Unmasking Depression via Attention-modulated Text Analysis using Deep Learning | International Conference on Communication, Security and Artificial Intelligence (ISWAB’23) |
| An effective intrusion detection scheme for Distributed Network Protocol 3 (DNP3) applied in SCADA-enabled IoT applications | Computers and Electrical Engineering |
| VBSF-TLD: Validation-Based Approach for Soft Computing-Inspired Transfer Learning in Drone Detection | arXiv |
| Design of a Contextual IoT Framework for the Improved User Experience and Services | Springer Book Chapter |
