
Arsalan ShahidUniversity College Dublin | UCD · CeADAR - Ireland's Centre for Applied AI
Arsalan Shahid
PhD MBA
About
54
Publications
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319
Citations
Introduction
Additional affiliations
August 2020 - February 2022
September 2016 - May 2020
Education
March 2021 - March 2022
Quantic School of Business and Technology
Field of study
- Business
September 2016 - May 2020
Publications
Publications (54)
This study investigates glucose conditions preceding and following various hypoglycemia levels in individuals with type 1 diabetes using open-source automated insulin delivery (AID) systems. It also seeks to evaluate relationships between hypoglycemia and subsequent glycemic variability. Methods: Analysis of continuous glucose monitor (CGM) data fr...
This report examines the fine-tuning of Large Language Models (LLMs), integrating theoretical insights with practical applications. It outlines the historical evolution of LLMs from traditional Natural Language Processing (NLP) models to their pivotal role in AI. A comparison of fine-tuning methodologies, including supervised, unsupervised, and ins...
Automated insulin delivery (AID) systems enhance glucose management by lowering mean glucose level, reducing hyperglycemia, and minimizing hypoglycemia. One feature of most AID systems is that they allow the user to view “insulin on board” (IOB) to help confirm a recent bolus and limit insulin stacking. This metric, along with viewing glucose conce...
Objective
To assess technical usability of the BigO app and clinical portal among diverse participants and explore the overall user experiences of both.
Methods
Methods included technical usability testing by measuring the relative user efficiency score (RUS) for the app and measuring Relative User Efficiency (RUE) using the ‘think aloud’ method w...
Conversational AI systems have emerged as key enablers of human-like interactions across diverse sectors. Nevertheless, the balance between linguistic nuance and factual accuracy has proven elusive. In this paper, we first introduce LLMXplorer, a comprehensive tool that provides an in-depth review of over 205 large language models (LLMs), elucidati...
Background: This study investigates glucose conditions preceding and following various hypoglycemia levels in individuals with type 1 diabetes using open-source automated insulin delivery (AID) systems. It also seeks to evaluate relationships between hypoglycemia and subsequent glycemic variability. Methods: Analysis of continuous glucose monitor (...
Background
Open-source automated insulin delivery (OS-AID) systems combine commercially available insulin pumps and continuous glucose monitors with open-source algorithms to automate insulin dosing for people with insulin-requiring diabetes. Two data sets (OPEN and the OpenAPS Data Commons) contain anonymized OS-AID user data.
Methods
We assessed...
p>Conversational AI systems have emerged as key enablers of human-like interactions across diverse sectors. Nevertheless, the balance between linguistic nuance and factual accuracy has proven elusive. In this paper, we first introduce LLMXplorer, a comprehensive tool that provides an in-depth review of over 150 Large Language Models (LLMs), elucida...
p>Conversational AI systems have emerged as key enablers of human-like interactions across diverse sectors. Nevertheless, the balance between linguistic nuance and factual accuracy has proven elusive. In this paper, we first introduce LLMXplorer, a comprehensive tool that provides an in-depth review of over 150 Large Language Models (LLMs), elucida...
Objectives:
Pancreatic enzyme replacement therapy (PERT) is essential for treating exocrine pancreatic insufficiency (EPI), a condition where the pancreas does not produce adequate enzymes for digestion. This study delves into the real-world experiences of individuals with EPI regarding their PERT usage.
Methods:
A study was executed using a tai...
AIVision360 is the pioneering domain-specific dataset tailor-made for media and journalism, designed expressly for the instruction fine-tuning of Large Language Models (LLMs).
The AIVision360-8k dataset is a curated collection sourced from "ainewshub.ie", a platform dedicated to Artificial Intelligence news from quality-controlled publishers. It i...
Conversational AI systems have emerged as key enablers of human-like interactions across diverse sectors. Nevertheless, the balance between linguistic nuance and factual accuracy has proven elusive. In this paper, we first introduce LLMXplorer, a comprehensive tool that provides an in-depth review of over 150 Large Language Models (LLMs), elucidati...
Large Language Model Explorer (LLMXplorer) is a comprehensive resource designed for researchers and businesses seeking to explore the landscape of LLMs, both open source and closed source.
This tool aims to capture the state of developments in the field of language models and provide insights into the evolution of LLM technologies.
It offers a...
Glucose forecasting serves as a backbone for several healthcare applications, including real-time insulin dosing in people with diabetes and physical activity optimization. This paper presents a study on the use of machine learning (ML) and deep learning (DL) methods for predicting glucose variability (GV) in individuals with open-source automated...
The use of Artificial Intelligence (AI) systems in the health domain requires developers of these systems to consider a wider view of requirements beyond traditional data security requirements. Data controllers of these systems should also include requirements that consider legal, privacy, fundamental rights, social, and ethical values. However, ha...
The relationship among the various causal factors of obesity is not well understood, and there remains a lack of viable data to advance integrated, systems models of its etiology. The collection of big data has begun to allow the exploration of causal associations between behavior, built environment, and obesity-relevant health outcomes. Here, we c...
BACKGROUND:
Thirty-nine percent of people with type 1 diabetes may have lowered pancreatic elastase levels, correlated with exocrine pancreatic insufficiency (EPI or PEI). EPI is treated with oral supplementation of pancreatic enzymes. Little is known about the glycemic impact of pancreatic enzyme replacement therapy (PERT) in people with diabetes....
Open-source automated insulin delivery (AID) technologies use the latest continuous glucose monitors (CGM), insulin pumps, and algorithms to automate insulin delivery for effective diabetes management. Early community-wide adoption of open-source AID, such as OpenAPS, has motivated clinical and research communities to understand and evaluate glucos...
Open-source automated insulin delivery (AID) technologies use the latest continuous glucose monitors (CGM), insulin pumps, and algorithms to automate insulin delivery for effective diabetes management. Early community-wide adoption of open-source AID, such as OpenAPS, has motivated clinical and research communities to understand and evaluate glucos...
Identification and re-identification are two major security and privacy threats to medical imaging data. De-identification in DICOM medical data is essential to preserve the privacy of patients’ Personally Identifiable Information (PII) and requires a systematic approach. However, there is a lack of sufficient detail regarding the de-identification...
Technology companies have become increasingly data-driven, collecting and monitoring a growing list of metrics, such as response time, throughput, page views, and user engagement. With hundreds of metrics in a production environment, an automated approach is needed to detect anomalies and alert potential incidents in real-time. In this paper, we de...
The energy efficiency in ICT is becoming a grand technological challenge and is now a first-class design constraint in all computing settings. Energy predictive modelling based on performance monitoring counters (PMCs) is the leading method for application-level energy optimization. However, a sound theoretical framework to understand the fundament...
Obesity is a major public health problem worldwide, and the prevalence of childhood
obesity is of particular concern. Effective interventions for preventing and treating childhood obesity aim to change behaviour and exposure at the individual, community, and societal levels. However, monitoring and evaluating such changes is very challenging. The E...
Performance and energy are the two most important objectives for optimization on modern parallel platforms. In this article, we show that moving from single-objective optimization for performance or energy to their bi-objective optimization on heterogeneous processors results in a tremendous increase in the number of optimal solutions (workload dis...
Energy predictive modelling is the leading method for determining the energy consumption of an application. Performance monitoring counters (PMCs) and resource utilizations have been the principal source of model variables primarily due to their high positive correlation with energy consumption. Performance events, however, have come to dominate th...
Obesity is a major public health problem worldwide and the prevalence of childhood obesity is of particular concern. Effective interventions for preventing and treating childhood obesity aim to change behaviour and exposures at the individual, community, and societal levels. However, monitoring and evaluating such changes is challenging. Developmen...
Technology companies have become increasingly data-driven, collecting and monitoring a growing list of metrics, such as response time, throughput, page views, and user engagement. With hundreds of metrics in a production environment, an automated approach is needed to detect anomalies and alert potential incidents in real-time. In this paper, we de...
Accurate and reliable measurement of energy consumption is essential to energy optimization at an application level. Energy predictive modelling using performance monitoring counters (PMCs) emerged as a promising approach, one of the main drivers being its capacity to provide fine-grained component-level breakdown of energy consumption. In this wor...
Accurate energy profiles are essential to the optimization of parallel applications for energy through workload distribution. Since there are many model-based methods available for efficient construction of energy profiles, we need an approach to measure the goodness of the profiles compared with the ground-truth profile, which is usually built by...
Information and Communication Technologies (ICT) systems and devices are forecast to consume up to 50% of global electricity in 2030. Considering the unsustainable future predicted, energy efficiency in ICT is becoming a grand technological challenge and is now a first-class design constraint in all computing settings. Energy efficiency in ICT can...
Modern high-performance computing platforms, cloud computing systems, and data centers are highly heterogeneous containing nodes where a multicore CPU is tightly integrated with accelerators. An important challenge for energy optimization of hybrid parallel applications on such platforms is how to accurately estimate the energy consumption of appli...
General trends in computer architecture are shifting more towards parallelism. Multicore architectures have proven to be a major step in processor evolution. With the advancement in multicore architecture, researchers are focusing on finding different solutions to fully utilize the power of multiple cores. With an ever-increasing number of cores on...
Energy predictive modelling using performance monitoring counters (PMCs) has emerged as the leading mainstream approach for modelling the energy consumption of an application. Modern computing platforms such as multicore CPUs provide a large set of PMCs. The programmers , however, can obtain only a small number of PMCs (typically 3-4) during an app...
Performance and energy are the two most important objectives for optimisation on modern parallel platforms. Latest research demonstrated the importance of workload distribution as a decision variable in the bi-objective optimisation for performance and energy on homogeneous multicore clusters. We show in this work that bi-objective optimisation for...
Energy is now a first-class design constraint along with performance in all computing settings. Energy predictive modelling based on performance monitoring counts (PMCs) is the leading method used for prediction of energy consumption during an application execution. We use a model-theoretic approach to formulate the assumed properties of existing m...
Energy of computing is a serious environmental concern and mitigating it is an important technological challenge. Accurate measurement of energy consumption during an application execution is key to application-level energy minimization techniques. There are three popular approaches to providing it: (a) System-level physical measurements using exte...
Many classical methods and algorithms developed when single-core CPUs dominated the parallel computing landscape, are still widely used in the changed multicore world. Two prominent examples are load balancing, which has been one of the main techniques for minimization of the computation time of parallel applications since the beginning of parallel...
AdditivityChecker is a tool that checks PMCs of applications for their Additivity, i.e., a must criteria for selecting a PMC to be used as a predictor variable in energy consumption modelling. More information on Additivity @ http://superfri.org/superfri/article/view/153.
AdditivityChecker takes STAT files generated by SLOPE-PMC-LIKWID (Beta) as i...
SLOPE-PMC-LIKWID (Beta Version) is an automated tool for collecting Performance Monitoring Counters (PMCs) on any Linux based platform supported by LIKWID.
How to Use SLOPE-PMC-LIKWID (Beta Version)?
1) Go to "SLOPE-PMC-LIKWID(Beta)" directory
2) Open main.c and give executable application where specified
3) Run startup.sh (source startup.sh)
4)...
Performance events or performance monitoring counters (PMCs) have been originally conceived, and widely used to aid low-level performance analysis and tuning. Nevertheless, they were opportunistically adopted for energy predictive modeling owing to lack of a precise energy measurement mechanism in processors, and to address the need of determining...
This paper concerns the design space exploration of Reconfigurable Multi Processor System on Chip (MPSoC) architectures. Reconfiguration allows users to allocate optimum system resources for a specific application in such a way as to improve the energy and throughput balance. To achieve the best balance between power consumption and throughput perf...
Driven by the advances in hardware and software technologies, the term Internet of things has emerged as a worldwide framework of ‘smart’ internet-based interconnected electronic devices through web having a significant impact in the betterment of our traditional living style. The use of these web connected embedded devices, as Information and comm...
Performance events or performance monitoring counters (PMCs) are now the dominant predictor variables for modeling energy consumption. Modern hardware processors provide a large set of PMCs. Determination of the best subset of PMCs for energy predictive modeling is a non-trivial task given the fact that all the PMCs can not be determined using a si...
SLOPE-PMC is a project for automating the process of collecting Performance
Monitoring Counters (PMCs) on Intel-based multicore systems.
SLOPE-PMC-LIKWID is an automated tool for collecting Performance
Monitoring Counters (PMCs) on the Intel-based multicore server by using LIKWID.
SLOPE-PMC-PAPI is an automated tool for collecting Performance...
Being an era of fast internet-based application environment, large volumes of relational data are being outsourced for business purposes. Therefore, ownership and digital rights protection has become one of the greatest challenges and among the most critical issues. This paper presents a novel fingerprinting technique to protect ownership rights of...
Standard benchmark tools play an integral part in the design process for performance evaluation of a computer system. A previously proposed tool, JetBench, is an Open Source multiprocessor benchmark that can be used to analyze the performance of a specific target platform. JetBench uses reaction-propulsion engine parameters and thermodynamical equa...
Multi-Processor System on Chip (MPSoC) architectures have become a mainstream technology for obtaining performance improvements in computing platforms. With the increase in the number of cores, the role of cache memory has become pivotal. An ideal memory configuration is always desired to be fast and large; but, in fact, striking to balance between...
The initiation to have a concept of shared memory in processors has built an opportunity for thread level parallelism. In various applications, synchronization or ordering tools are utilized to have an access to shared data. Traditionally, multithreaded programming models usually suggest a set of low-level primitives, such as locks, to guarantee mu...
The scaling of CMOS technology has continued due to ever increasing demand of greater performance
with low power consumption. This demand has grown further by the portable and battery operated
devices market. To meet the challenge of greater energy efficiency and performance, a number of power
optimization techniques at processor and system compone...
General trends in computer architecture are shifting more towards parallelism. Multicore architectures have proven to be a major step in processor evolution. With the ever-increasing number of cores on a chip, the role of cache memory has become pivotal. An ideal memory configuration should be both large and fast, however, in fact, system architect...