Additivity: A Selection Criterion for Performance Events for Reliable Energy Predictive Modeling. - Arsalan Shahid; Muhammad Fahad 002; Ravi Reddy; Alexey L. Lastovetsky (Supercomput. Front. Innov., 2017)

How Pre-multicore Methods and Algorithms Perform in Multicore Era. - Alexey L. Lastovetsky; Muhammad Fahad 002; Hamidreza Khaleghzadeh; Semyon Khokhriakov; Ravi Reddy; Arsalan Shahid; Lukasz Szustak; Roman Wyrzykowski (ISC Workshops, 2018)

AC-DSE: Approximate Computing for the Design Space Exploration of Reconfigurable MPSoCs. - Arsalan Shahid; Muhammad Yasir Qadri; Martin Fleury; Hira Waris; Ayaz Ahmad; Nadia N. Qadri (J. Circuits Syst. Comput., 2018)

Improving the Accuracy of Energy Predictive Models for Multicore CPUs Using Additivity of Performance Monitoring Counters. - Arsalan Shahid; Muhammad Fahad 002; Ravi Reddy Manumachu; Alexey L. Lastovetsky (PaCT, 2019)

Energy of Computing on Multicore CPUs: Predictive Models and Energy Conservation Law. - Arsalan Shahid; Muhammad Fahad 002; Ravi Reddy Manumachu; Alexey L. Lastovetsky (CoRR, 2019)

Bi-objective Optimisation of Data-parallel Applications on Heterogeneous Platforms for Performance and Energy via Workload Distribution. - Hamidreza Khaleghzadeh; Muhammad Fahad 002; Arsalan Shahid; Ravi Reddy Manumachu; Alexey L. Lastovetsky (CoRR, 2019)

Analytical models of Energy and Throughput for Caches in MPSoCs. - Arsalan Shahid; Muhammad Tayyab; Muhammad Yasir Qadri; Nadia N. Qadri; Jameel Ahmed (CoRR, 2019)

SLMAD: Statistical Learning-Based Metric Anomaly Detection. - Arsalan Shahid; Gary White; Jaroslaw Diuwe; Alexandros Agapitos; Owen O'Brien (ICSOC Workshops, 2020)

Accurate Energy Modelling of Hybrid Parallel Applications on Modern Heterogeneous Computing Platforms Using System-Level Measurements. - Muhammad Fahad 002; Arsalan Shahid; Ravi Reddy Manumachu; Alexey L. Lastovetsky (IEEE Access, 2020)

A Comparative Study of Techniques for Energy Predictive Modeling Using Performance Monitoring Counters on Modern Multicore CPUs. - Arsalan Shahid; Muhammad Fahad 002; Ravi Reddy Manumachu; Alexey L. Lastovetsky (IEEE Access, 2020)

Energy Predictive Models of Computing: Theory, Practical Implications and Experimental Analysis on Multicore Processors. - Arsalan Shahid; Muhammad Fahad 002; Ravi Reddy Manumachu; Alexey L. Lastovetsky (IEEE Access, 2021)

Improving the accuracy of energy predictive models for multicore CPUs by combining utilization and performance events model variables. - Arsalan Shahid; Muhammad Fahad 002; Ravi Reddy Manumachu; Alexey L. Lastovetsky (J. Parallel Distributed Comput., 2021)

Big Data Warehouse for Healthcare-Sensitive Data Applications. - Arsalan Shahid; Thien-An Ngoc Nguyen; M. Tahar Kechadi (Sensors, 2021)

Bi-Objective Optimization of Data-Parallel Applications on Heterogeneous HPC Platforms for Performance and Energy Through Workload Distribution. - Hamidreza Khaleghzadeh; Muhammad Fahad 002; Arsalan Shahid; Ravi Reddy Manumachu; Alexey L. Lastovetsky (IEEE Trans. Parallel Distributed Syst., 2021)

Legal, Privacy, Social and Ethical Requirements and Impact Assessment for an Artificial Intelligence Based Medical Imaging Project. - Ceara Treacy; Gilbert Regan; Arsalan Shahid; Brian Maguire (EuroSPI, 2022)

Building Trust in Conversational AI: A Comprehensive Review and Solution Architecture for Explainable, Privacy-Aware Systems using LLMs and Knowledge Graph. - Ahtsham Zafar; Venkatesh Balavadhani Parthasarathy; Chan Le Van; Saad Shahid; Aafaq Iqbal khan; Arsalan Shahid (CoRR, 2023)

Building Trust in Conversational AI: A Review and Solution Architecture Using Large Language Models and Knowledge Graphs. - Ahtsham Zafar; Venkatesh Balavadhani Parthasarathy; Chan Le Van; Saad Shahid; Aafaq Iqbal khan; Arsalan Shahid (Big Data Cogn. Comput., 2024)

The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunities. - Venkatesh Balavadhani Parthasarathy; Ahtsham Zafar; Aafaq Iqbal khan; Arsalan Shahid (CoRR, 2024)

The Future of MLLM Prompting is Adaptive: A Comprehensive Experimental Evaluation of Prompt Engineering Methods for Robust Multimodal Performance. - Anwesha Mohanty; Venkatesh Balavadhani Parthasarathy; Arsalan Shahid (CoRR, 2025)