2024 — Present
Fundamental research & applied data science
Data Scientist
CEA Paris-Saclay · Paris, France
Technical lead on building street-scale emission intelligence for India.
ForecastingCausal MLSHAPDistributed Computing
Rohith Teja — Data Scientist
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Rohith Teja — Data Scientist
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DATA SCIENCE•MACHINE LEARNING•FORECASTING•ENERGY INTELLIGENCE•TIME SERIES•GRAPH NEURAL NETWORKS•CAUSAL INFERENCE•SHAP•PYTHON•CLIMATE SCIENCE•URBAN MOBILITY•RAG•LLMs•MLOps•PYTORCH•DASK•DEEP LEARNING•INTERACTIVE VISUALIZATION•DATA SCIENCE•MACHINE LEARNING•FORECASTING•ENERGY INTELLIGENCE•TIME SERIES•GRAPH NEURAL NETWORKS•CAUSAL INFERENCE•SHAP•PYTHON•CLIMATE SCIENCE•URBAN MOBILITY•RAG•LLMs•MLOps•PYTORCH•DASK•DEEP LEARNING•INTERACTIVE VISUALIZATION•
i am rohith
I’m a data scientist and researcher working at the intersection of forecasting, energy intelligence, urban mobility, and AI.
At CEA Paris-Saclay, I built and oversee the modeling for India's traffic component of a €1M project, where I developed a street-scale emission intelligence framework that transforms terabytes of floating car data from 100 Indian cities into daily 500m-resolution CO₂ and pollutant estimates.
I specialise in large-scale time-series forecasting, interpretable ML, and causal inference. My work spans natural gas demand forecasting across 1,000 U.S. counties to urban emissions modelling, using SHAP and causal ML to turn complex data into decisions people can trust.
My research has been published in Science Advances and Nature Scientific Data, with collaborations across UC Irvine, Tsinghua University, and IIT Bombay.
Domains
- Urban Mobility
- Climate & Energy
- Forecasting
- Causal Inference
- Knowledge Graphs
- LLMs & RAG
Specialties
- Forecasting & Time Series
- Graph ML
- Interpretable ML (SHAP)
- Causal ML & DAGs
- MLOps & Big Data
- Interactive Data Viz
Currently
Data Scientist @ CEA Paris-Saclay in complex systems & energy intelligence
Education
PhD Complex Systems & Machine Learning, Université Paris-Saclay
Location
Paris, France
numbers that tell a story
scale · resolution · accuracy : what a my journey of data science looks like
0TB+
Floating car data processed
0
Indian cities with street-scale emission maps
0
U.S. counties under natural gas forecast
0%
Short-term forecast accuracy
0
Publications & preprints
0K+
Views on science communication
0m
Emission grid resolution
0+
Medium subscribers
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experience
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0104
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Data Scientist · CEA Paris-Saclay · 2024 — Present
education
PhD · Complex Systems & Machine Learning
Université Paris-Saclay, France
Research on urban mobility, energy intelligence and causal ML.
Master · Machine Learning & Data Mining
Université Jean Monnet, France
Specialised in graph neural networks and deep learning.
Bachelor of Technology
NIT Raipur, India
Distributed computing and systems.
i write
on all things data science!
(06)
AI & Technology
01
7 min read
ChatGPT, Random Numbers and the Lottery
An interesting exploration of how ChatGPT handles random number generation and what this reveals about AI systems when applied to lottery scenarios.
Read on Medium
Machine Learning
02
12 min read
How to Generate and Evaluate Knowledge Graph Embeddings
A comprehensive guide on generating and evaluating the performance of knowledge graph embeddings, covering practical implementation and evaluation metrics.
Read on Medium
Climate Science
03
8 min read
What Does an Eerie Song on Global Warming Tell Us?
An intriguing analysis connecting music, data, and climate change messaging. Exploring how artistic expression can communicate environmental data and climate science.
Read on Medium
Tutorial
04
15 min read
Let's Talk About Graph Neural Network Python Libraries
A comprehensive comparison and guide to the most popular Graph Neural Network libraries in Python, helping developers choose the right tools for their projects.
Read on Medium
Data Visualization
05
10 min read
I Created Music from Data Using Python
A creative exploration of data sonification - transforming datasets into musical compositions using Python. Discover how data can become art through sound.
Read on Medium
Bioinformatics
06
14 min read
Graph Machine Learning in Biomedical Networks
An in-depth discussion on applying graph machine learning techniques to biomedical networks, exploring applications in drug discovery and biological analysis.
Read on Medium
Read on Medium
Visit My Medium BlogWant to read more?
Check out my Medium blog for more articles on data science and AI.
research
published papers & contributions
Open to opportunitieslet's build something
let's build something
data can't solve alone
I'm open to senior data scientist, AI research and energy / mobility intelligence roles. Let's connect!
find me here
© 2026 Rohith Teja