π Graduate Research Assistant @ WVU
π± Lifelong learner | π¨βπ» Code + Research + Real-world Impact
π Interests: Machine Learning β’ AI Agents β’ Sustainability β’ Computer Vision β’ Energy Systems
I'm a curious engineer-turned-data-scientist currently exploring the intersection of machine learning, environmental analytics, and human-centric AI. My journey spans from industrial process optimization to predictive modeling for sustainability and behavioral energy efficiency.
Iβm a big believer in:
- ποΈ Explainability > Black box magic
- βοΈ Systems thinking > One-off scripts
- π Evidence > Hype
Languages:
Python
, C++
, SQL
, JavaScript
, Bash
Data & ML:
scikit-learn
, PyTorch
, XGBoost
, SHAP
, LIME
, Optuna
, Imbalanced-learn
, tslearn
Visualization:
Matplotlib
, Plotly
, Seaborn
, D3.js
Cloud & DevOps:
AWS (EC2, S3, Lambda)
, Docker
, Git
, Kubernetes
, Airflow
Others:
Pandas
, NumPy
, FastAPI
, PostgreSQL
, Streamlit
Project | Description | Tech |
---|---|---|
πΏ BRFSS x P2 Cancer Model | Multilevel ML modeling combining CDC health survey (BRFSS) and state-level pollution data to predict cancer incidence | scikit-learn , SMOTE , SHAP |
I write about data science, sustainable systems, and tech philosophy.
Coming soon at akshayxcode.dev π§
Sample articles:
- LinkedIn: linkedin.com/in/aksh-ay06
- Email: [email protected]
- Portfolio: akshayxcode.dev
βYou don't need to be a genius to change the world. Just be consistently curious.β π
β Feel free to explore, fork, or collaborate. Pull requests and discussions welcome!