Deep Learning for Plant Disease Detection: A Practical Framework for Image-Based Crop Diagnosis
Research note on using deep learning for image-based plant disease detection, crop diagnosis, and practical AI-assisted agriculture workflows.
Deep Learning for Skin Cancer Detection: A Practical Framework for Automated Skin Lesion Classification
This research note presents a practical deep learning framework for automated skin lesion classification, showing how AI can support skin cancer detection workflows through image-based analysis.
An End-to-End Data Quality Management Framework for Banking Systems with Generative AI Integration
This research note presents an end-to-end data quality management framework for banking systems, showing how generative AI can support profiling, validation, anomaly detection, root-cause analysis, and governance.
AI-Assisted Protein Analysis: From Sequence Representation to Drug-Binding Hypothesis Generation
This research note explores how AI can support protein analysis, from sequence representation and structural interpretation to drug-binding hypothesis generation for early-stage drug discovery.
Building a Persona-Driven Survey Engine Using AI for Synthetic User Modeling and Decision Simulation
This research note explores how an AI-powered persona-driven survey engine can simulate user responses, model synthetic personas, and support structured decision-making through feedback analysis.
Evolving Reasoning in Large Language Models: From Linear Chain-of-Thought to Graph-Based Diagram-of-Thought Frameworks
This research note explores how reasoning in large language models is evolving from linear chain-of-thought prompting to graph-based Diagram-of-Thought frameworks that support more structured, multi-path reasoning.
From Simulation to Prediction: Data-Driven Modeling of Fluid Dynamics Using Artificial Intelligence
Can artificial intelligence learn the behaviour of fluid dynamics from simulation data? This research note explores how AI can support prediction of Rayleigh-Bénard convection using WALRUS and scientific machine learning.
From Simulation to Prediction: Learning Fluid Dynamics with AI
Can an AI predict how fluid moves?
In this piece, I explore how a physics foundation model—WALRUS—learns to forecast the evolution of a heated fluid system. Instead of solving equations, the model observes patterns and generates its own version of the future. The result is a striking simulation that reveals both the power and the limits of AI in modeling the physical world.
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AI-Assisted Protein Analysis: From Sequence to Drug-Binding Hypothesis
Can AI help us understand how medicines interact with the body?
In this edition, I explore a beginner-friendly experiment where I used AI tools like AlphaFold and AutoDock Vina to go from a protein sequence to a plausible drug-binding hypothesis—all on a laptop. A simple walkthrough, even if you’re new to biology.
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Building a Persona-Driven Survey Engine Using AI
What if you could test your product idea before having real users?
In this post, I show how to use AI personas to build a synthetic focus group—generate surveys, simulate responses, and uncover insights early.
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