Skills

Technical Skills

• AI & ML: NumPy, Pandas, Matplotlib, Seaborn, SciPy, Scikit-learn, PyTorch, TensorFlow, Hugging Face Transformers, spaCy, OpenCV, PySpark, Keras, NLP, DASK, XAI
• Programming: C, C++, Java, Kotlin, Python, Swift, Dart, R, SQL, SAS
• Research Tools: Jupyter Notebook, Google Colab, LaTeX, MATLAB, R, Excel, SPSS, Minitab, TORA, NetworkX, ggplot2, plotly, Zotero, Mendeley
• Databases: MySQL, PostgreSQL, MongoDB, Hadoop, Spark
• App Development: Android (Java, Kotlin, Flutter), iOS (Swift, Objective-C, Flutter)
• REST API: Spring Boot (Java, Kotlin), Ktor (Kotlin), Django, FastAPI (Python)
• Additional: Statistical Analysis, Data Processing, Feature Engineering, Technical Writing, Academic Presentations

Specialized Expertise

AI in Healthcare

Clinical Prediction & Risk Modeling · Healthcare Utilization & Cost Forecasting · Explainable Medical AI · Public-Health Data Analysis

Mobile App Development

Expert in both Android and iOS development — cross-platform with Flutter, native Android (Java/Kotlin), native iOS (Swift/Objective-C). Team leadership experience with the Walton mobile app development team and enterprise-level application architecture and deployment.

Graph Neural Networks

Dynamic Graph Neural Networks (DGNNs) · Contrastive Attentive Graph Networks · Graph Attention Networks for Intrusion Detection · GraphSAGE for Relational Modeling

Explainable AI (XAI)

LIME and SHAP for feature-level insights · Grad-CAM, Grad-CAM++, and Eigen-CAM visualizations · ShapTime and Permutation Feature Importance · Model interpretability and transparency

Operations Research & Supply Chain

Supply Chain Demand Forecasting · Multi-Channel Data Fusion Networks · Cellular Manufacturing Systems · Big Data Analytics in Supply Chain Management

Computational Biology

Evolutionary Dynamics of Strongly Conserved Sequences · Comparative Genomics · Perfectly Conserved Sequences Analysis · Vertebrate and Insect Genomic Studies

Open Source Contributions

• Maintain 9+ open-source machine learning and deep learning project repositories on GitHub, each paired with a live, interactive Streamlit web app.
• Publish reproducible, end-to-end ML pipelines and notebooks spanning NLP, computer vision, recommendation systems, and time-series forecasting.
• Deploy publicly accessible data-science web apps for real-time inference and visualization.
• Active GitHub contributor with multiple research and applied codebases.