5 papers
Constraint-Aware Neurosymbolic Uncertainty Quantification with Bayesian Deep Learning for Scientific Discovery
Shahnawaz Alam, Mohammed Mudassir Uddin, Mohammed Kaif Pasha
Scientific Artificial Intelligence (AI) applications require models that deliver trustworthy uncertainty estimates while respecting domain constraints. Existing uncertainty quantif…
DriftGuard: A Hierarchical Framework for Concept Drift Detection and Remediation in Supply Chain Forecasting
Shahnawaz Alam, Mohammed Abdul Rahman, Bareera Sadeqa
Supply chain forecasting models degrade over time as real-world conditions change. Promotions shift, consumer preferences evolve, and supply disruptions alter demand patterns, caus…
SecureCAI: Injection-Resilient LLM Assistants for Cybersecurity Operations
Mohammed Himayath Ali, Mohammed Aqib Abdullah, Mohammed Mudassir Uddin +1
Large Language Models have emerged as transformative tools for Security Operations Centers, enabling automated log analysis, phishing triage, and malware explanation; however, depl…
AgentCompress: Task-Aware Compression for Affordable Large Language Model Agents
Zuhair Ahmed Khan Taha, Mohammed Mudassir Uddin, Shahnawaz Alam
Large language models hold considerable promise for various applications, but their computational requirements create a barrier that many institutions cannot overcome. A single ses…
Cost-effective Deep Learning Infrastructure with NVIDIA GPU
Aatiz Ghimire, Shahnawaz Alam, Siman Giri +1
The growing demand for computational power is driven by advancements in deep learning, the increasing need for big data processing, and the requirements of scientific simulations f…