Our Research Projects
Delhi Pollution Forecast & History
We have engineered AirCast Delhi and AirCast-SR, a diffusion-based foundation model utilizing Latent Consistency Diffusion to downscale coarse global weather predictions (~28 km) into kilometer-scale, high-resolution local forecasts. By fine-tuning atmospheric super-resolution models on sparse weather station observations across India, the platform bridges the critical gap in fine-scale weather data, enabling actionable decision-making for urban infrastructure, local heatwaves, and extreme rainfall events across Delhi and surrounding regions.
S2S Research · Experimental Subseasonal Forecast
We have created a website that shows sub-seasonal to seasonal forecast looking ahead six weeks. This is based on global weather models that are fine tuned and optimized to give better predictions.
Financial Factor Data Library
The website provides Fama-French factors for Indian equity markets along with an interactive tool visualization, analysis, and backtesting portfolio strategies. We currently cover the six core Fama-French factors: size, value, profitability, investment, and momentum starting in October 2003. We start with all stocks in the CMIE Prowess database and apply filters to screen out thinly traded stocks, penny stocks, and microcaps. This is the final SCDLDS universe that we use to compute monthly portfolio and factor returns. We will augment the return time series on a monthly basis and add other factors from time to time.
Agentic AI & ML Applications in Indian Equity Markets and Corporate Governance
Factor investing has been a prominent investment strategy for fund managers across the globe and has gained popularity in India as well. However, applying global factor construction methodology directly to India can be misleading due to the microstructure of the Indian equity market. They are characterised by a vast majority of small and illiquid firms which are often harder to trade. To address this, we propose a rigorous and empirically grounded approach for factor construction for India. The methodology incorporates liquidity, penny stocks, microcaps, accounting lags, and negative book equity filters to arrive at the tradable universe.
Generative AI using diffusion modelling
The diffusion group at SCDLDS seeks to explore various theoretical questions in the subfield of diffusion, which is the state-of-the-art theory employed in the best generative models around the world such as image/video generators, and recently in LLMs.
AI for weather and climate modelling
This group focuses on improving weather forecasts for India with data-driven methods to help mitigate the impacts of climate change and help various downstream applications like energy, agriculture and disaster management. We work with various agencies like the Indian Met Department to get access to relevant weather data and develop models on them.