A5075112022- Ethics and Social Impacts of AI
- Artificial Intelligence in Healthcare and Education
- Explainable Artificial Intelligence (XAI)
- Bacterial biofilms and quorum sensing
- Bacterial Genetics and Biotechnology
- Adversarial Robustness in Machine Learning
- Antimicrobial Peptides and Activities
- Nanomaterials and Printing Technologies
- CRISPR and Genetic Engineering
- Biosimilars and Bioanalytical Methods
- Bioinformatics and Genomic Networks
- Enzyme-mediated dye degradation
- Microbial bioremediation and biosurfactants
- Microbial Metabolic Engineering and Bioproduction
- Advanced Biosensing Techniques and Applications
- Recycling and Waste Management Techniques
- Big Data and Business Intelligence
- Additive Manufacturing and 3D Printing Technologies
- Biomedical Ethics and Regulation
- Biosensors and Analytical Detection
- Statistical Methods in Clinical Trials
- Advanced biosensing and bioanalysis techniques
- Socioeconomic Development in MENA
- Environmental remediation with nanomaterials
Hong Kong University of Science and Technology
2017-2024
University of Hong Kong
2017-2024
Delft University of Technology
2015
Large Language Models (LLMs) have become a cornerstone of modern artificial intelligence (AI), finding applications across various domains such as healthcare, finance, entertainment, and customer service. To understand their ethical social implications, it is essential to first grasp what these models are, how they function, why carry significant impact. This introduction aims provide comprehensive beginner-friendly overview LLMs, introducing basic structure, training process, the types...
In this study, the capability of using aerobic granules to undergo simultaneous anaerobic decolorization and aromatic amines degradation was demonstrated for azo dye wastewater treatment. An integrated acclimation-granulation process devised, with Mordant Orange 1 as model pollutant. Performance tests were carried out in a batch column reactor evaluate effect various operating parameters. The optimal condition use 1.0-1.7 mm (1.51 ± 0.33 mm) granules, 5 g/L biomass, 4000 mg/L organics...
Artificial Intelligence (AI) has permeated numerous aspects of our daily lives, from predictive text on smartphones to complex decision-making systems in healthcare and finance. While AI shown remarkable accuracy efficiency, it is often criticized for being a 'black box,' particularly when comes models like deep learning large language (LLMs). This where Explainable (XAI) into play.Explainable aims make decisions transparent, understandable, interpretable. The lack interpretability raised...
Abstract Due to the complexity of screen‐printing operation and rheological behaviors screen‐printable paste, such a paste is usually formulated by trial‐and‐error. In this report, systematic procedure, based on heuristics mechanistic models, for design developed. The procedure demonstrated case study formulation conductive copper particles .
This article presents a numerical platform for predicting the performance of paper-based analytical devices.
Large Language Models (LLMs) have become a cornerstone of modern artificial intelligence (AI), finding applications across various domains such as healthcare, finance, entertainment, and customer service. To understand their ethical social implications, it is essential to first grasp what these models are, how they function, why carry significant impact. This introduction aims provide comprehensive beginner-friendly overview LLMs, introducing basic structure, training process, the types...
Large Language Models (LLMs) represent a significant advancement in artificial intelligence, capable of understanding and generating human-like text based on extensive training data. These models are trained vast datasets that encompass various topics, languages, styles, enabling them to perform wide range language-related tasks, such as translation, summarization, content creation, even complex question answering. Their versatility makes invaluable tools across different industries,...
The integration of bioinformatics predictions and experimental validation plays a pivotal role in advancing biological research, from understanding molecular mechanisms to developing therapeutic strategies. Bioinformatics tools methods offer powerful means for predicting gene functions, protein interactions, regulatory networks, but these must be validated through approaches ensure their relevance. This review explores the various technologies used validation, including expression analysis,...
Explainability in artificial intelligence (AI) has become crucial for ensuring transparency, trust, and usability across diverse application domains, such as healthcare, finance, autonomous systems. This comprehensive review analyzes the state of research on explainability techniques, categorizing approaches into model-agnostic, model-specific, hybrid methods. Key SHAP, LIME, rule-based explanations, are discussed alongside their respective strengths limitations. The also delves...
In recent years, the field of artificial intelligence (AI) and machine learning (ML) has undergone a transformative shift, with generative models emerging as one most significant impactful areas research. Generative models, in essence, are that can generate new data instances resemble given set training data. Unlike discriminative which focus on classification tasks, aim to understand replicate underlying structure data, making them capable generating images, text, audio, even 3D objects....
Large Language Models (LLMs) have become a cornerstone of modern artificial intelligence (AI), finding applications across various domains such as healthcare, finance, entertainment, and customer service. To understand their ethical social implications, it is essential to first grasp what these models are, how they function, why carry significant impact. This introduction aims provide comprehensive beginner-friendly overview LLMs, introducing basic structure, training process, the types...