Rishabh Agrahari
Founder at Sanchai Analytics
Pune, Maharashtra, India
Summary
👤
Senior🎓
Top SchoolRishabh Agrahari is a founder and AI leader with 10 years of experience building production-ready deep learning and ML solutions across manufacturing, renewable energy, and healthcare. He led AI product development at TVARIT—taking a core product from zero to recurring savings on shopfloors by combining on-prem data pipelines, AWS integrations, and actionable Grafana UIs—and now builds agentic AI for renewable plants at Sanchai Analytics. Deep learning practitioner background includes deploying 3D adaptations of RetinaNet for medical imaging and time-series forecasting work (ARIMA, LSTM/GRU) showcased in his open-source load-forecasting projects. Comfortable across Python ecosystems, data infrastructure, and end-to-end delivery, he blends hands-on research with customer-centric productization. A serial founder who also built an early deepfake-detection platform, he pairs entrepreneurial risk-taking with practical engineering execution.
9 years of coding experience
3 years of employment as a software developer
High School, High School at St. Xavier's High SchoolEngineer’s Degree (B.Tech & M.Tech), Electrical Engineering, Engineer’s Degree (B.Tech & M.Tech), Electrical Engineering at Indian Institute of Technology (Banaras Hindu University), VaranasiIntermediate, Intermediate at Puranchandra Vidyaniketan
Stackoverflow
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jupyter-notebook
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Github Skills (32)
gru10
python10
arima10
pandas10
machine-learning10
time-series10
rnn-model10
exploratory-data-analysis10
n10
eda10
data-preprocessing10
keras10
lstm10
tensorflow10
data-analysis10
Programming languages (15)
Github contributions (5)
pyaf/load_forecasting
Jan 2018 - Jul 2019
Forecasting electric power load of Delhi using ARIMA, RNN, LSTM, and GRU models
Role in this project:
Data Scientist
Data ScientistContributions:43 commits, 4 PRs, 37 pushes in 1 year 6 months
Contributions summary:Rishabh's commits primarily focus on exploratory data analysis and implementing machine learning models for load forecasting. They added an EDA notebook to explore the data, including the extraction of date and time features. They also implemented and trained models like FFNN, ARIMA, LSTM, and GRU, indicating a focus on building predictive models for time series data. The user also removed csv data and updated webserver code.
forecastingpythonelectric-load-forecastingwmatime-series
pyaf/tpobot
Jul 2017 - Nov 2017
A messenger bot for giving updates of TPO portal to the students of IIT (BHU).
Contributions:52 commits, 28 pushes, 1 branch in 4 months
telegram-botredismessenger-botfacebook-messenger-platformdjango
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