Hey, I’m Pranav.
I build AI/ML systems and the software around them. RAG pipelines, forecasting models, production frontends. CS graduate and published IEEE researcher.
Experience
Built responsive, user facing frontends in HTML, CSS and JavaScript, and developed a stock price forecasting model in Python using time series methods to predict market movements.
Named author on three research papers across electricity price forecasting, Arctic mercury modeling, and pesticide resistance surveillance. Built a hybrid CNN/BiLSTM/Attention model (TensorFlow, Keras) reaching ~25% lower RMSE (12.40 vs 16.49) and higher R² (0.87 vs 0.63) than the strongest baselines.
Built a RAG based health chatbot end to end, answering symptom questions with LangChain, OpenAI APIs and a vector database. Contributed UI for a HIPAA compliant medical app.
Student athlete on the varsity roster, training and competing alongside a full course load and research work.
RosterOrganized and analyzed large datasets with data warehousing techniques, ran cleaning and EDA in Pandas, and automated processing with Dataiku for non technical stakeholders.
Projects
VALS ↗
2026Led a team of 4 to build a realtime VR label autocomplete system with a Trie based prefix search supporting full word and abbreviation matching, loading anatomy data dynamically from CSV.
Maargdarshak ↗
2024A guidance tool with a Streamlit interface tuned for usability and accessibility, wiring Python logic to the OpenAI API for realtime interactivity.
Arctic Mercury Modeling ↗
2025An ML assisted framework modeling mercury reduction, reemission, and diffusion across Arctic snow and ice, blending quantum chemistry and molecular dynamics with data driven models.
Restaurant Management ↗
2023A dynamic order management platform with a staff interface for categories, orders, and customer records, backed by MySQL for reliable storage and retrieval.
Research
UniElecPrice: A Unified Cross Regional Day Ahead Electricity Price Dataset
Introduced a globally unified dataset of day ahead electricity prices drawn from 40 markets across 5 continents, enabling standardized forecasting research. Developed and validated a hybrid CNN/BiLSTM/Attention model that outperformed LSTM and Transformer baselines.
Toolkit
Let’s build something.
The fastest way to reach me is email. Always happy to talk shop.
p.pranavbalachander@gmail.com