Gagandeep Singh

Leading Invoice extraction product, we work towards pushing the limits of state of the art research in information extraction from unstructured documents. alongside with this, we have created the self servicing user friendly platform, a no code service for training data extraction models. Our current In house developed model has surpassed the standards of Microsoft's LayoutLM and also being able to generalise well on unseen layouts with current 95.5% mef1 (mean entity f1 score). Provided solutions for Loss run, utility bills (real page) documents data extraction. Worked On Successful Magic Aadhaar product, which is able to mask security no. from aadhaar type documents in kyc processing. was the key automation in kyc processing of insurance documents for the client.

Collaborate with management, technical crew members team of 15, to organise efficient site operations and achieve demanding schedule targets simultaneously meeting quality standards meeting Industry norms based on research and domain knowledge. KPIs are thoroughly observed and Parameters are forecasted in manner that Unit achieve desired throughput and production with proper human resources management in regular basis. Part of Analytics Team, Have worked on Various ML models Implementations based On Regression, Time Series Forecasting etc.

Internship in Brewing Industry poised towards optimization (5% increase in yield by heat optimization) of processing system (Malt Evaporation). Identified areas of weakness and recommended implementable process improvements.

Project was aimed at production of Energy by anaerobic bacteria in wastewater and simultaneous waste management. Large sets of data were collected by varying input parameters and Multi Parameter Model was established with use of regression methods, for newer better design, with increased current density by 25%.

Successfully completed 5 course specialisation by DeepLearning.AI in field of machine learning.

Online course in direction of Decision making leveraging the Data.

Graduated with 8.72 GPA.

Passed with 88.80% and Securing a Merit on district level.