Rishabh Malhotra

Taught MIT's and UT Austin's online DS-ML program to working professionals, covering concepts from linear algebra and statistics to deep neural networks and recommendation systems.

Taught MIT’s and UT Austin’s online DS-ML program. Mentored working professionals on various topics.

Recorded deep learning lectures and conducted live sessions for the Data Science Masters program.

Recorded deep learning lectures and conducted live sessions for the Data Science Masters program.

Created and implemented a No Code Non-Linear Constrained End to End Cascaded Optimisation framework using Artificial Neural Networks for real-time optimisation and enhanced process control for manufacturing equipment across the whole Oil and Gas industry. Utilized document extraction techniques and developed RUL prediction and sensor value detection models.

Created and implemented a No Code Non-Linear Constrained End to End Cascaded Optimisation framework using Artificial Neural Networks for real-time optimisation and enhanced process control for manufacturing equipment across the whole Oil and Gas industry. Utilized document extraction techniques and developed predictive models for exchangers and field device sensor value detection.

Taught MIT's and UT Austin's online DS-ML program, mentored working professionals, and conducted marketing webinars.

Provided data science consulting services.

Provided data science consulting services.

Worked on real-time anomaly detection and signal processing project using DB-Scan clustering, LOF, and Markov Chain. Delivered synthetic control API for hypothesis testing.

Led a classification project, built a fraud detection model, implemented text cleaning techniques, and created a Time Series predictive model for deferred business due to the Covid19 pandemic.

Developed a financial lending investment portal, designed a rule engine and deep learning medical claims detection model, established a new data pipeline, and curated an embedded analytics product for clients.

Provided data science consulting services.

Led a classification project using spatial clustering, built a fraud detection model, implemented text cleaning techniques, and created a Time Series predictive model for Covid-19 impact.

Developed a financial lending investment portal, designed a complex rule engine and deep learning medical claims detection model, established a new data pipeline, and curated an embedded analytics product for clients.

Worked on real-time anomaly detection and signal processing project using DB-Scan clustering and Markov Chain, and delivered a synthetic control API for hypothesis testing.