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Predicting Operator Needs using Machine Learning

Cornell 2019-20

Siemens Healthineers Atellica® Solution is an immunoassay and clinical chemistry analyzer which performs sample management and statistical prioritization for medical diagnostic laboratories.The technology improves lab management by providing independent control with automatic scheduling, inherent quality control and workflow enhancement. This project aims to build an inherent 'Online Tutor' within the Analyzer which would guide the operator based on system events. It aims to enhance the ease of operation by determining the pattern of usage of the analyzers and recommending steps in the operation cycle.
Project Advisor: Professor Fengqi You

CFC: Cornell for Cornell

Cornell Spring'20

Cornell for Cornell is a social network website for Cornell students and Alumni for Industry references. Cornell alumni can post job openings in their companies on which they are willing to refer candidates to. Candidates can request references from these users. It is full stack python Project executed using FLASK framework. It consist of various functionalites such as user login, signup, Relational databases ,databse querying etc. It employs libraries such as jinja, werkezeug, SQLAlchemy. It is currently on the road to being deployed using Heroku. Github

Project Sirohi: Installation of Solar Panels in 300 Households

GGSIPU Spring'14

In the summer of 2014, my team and I finished the installation of stand-alone solar panels in three hundred households in the remote village of Sirohi, Haryana (India). We conducted Energy Audits and after assessment of the daily requirement sized solar panels & battery which were then installed over a span of six month. Project Sirohi helped reduce the community’s dependency on the unreliable distribution networks and become more self-sufficient. The project, done in partnership with Skilled Samaritan Foundation, Engineers Without Borders & BechTel, had a significant impact on me as it showed me the virtues of my education and allowed me to apply my theoretically learned knowledge for practical purposes. It also roused my interest in the energy sector as it gave me a glimpse of the future with renewables at the forefront and made me delve deeper in this area. Video

Information Diffusion in Social Networks

Cornell Spring'20

Information diffusion is an area of study of social networks with applications in predicting elections, identifying trends, forecasting market sentiment and understanding the reach of epidemics. With widespread social networks this project, through known information diffusion models, aims to study the spread of information and its impact in various world scenarios.
Project Advisor: Professor Vikram Krishnamurthy