ANIK SHIKARPURI

• Providing consulting services to the Department of Health in the realm of Data Science
• Developed and maintained technical documentation for customer solutions
• Analyzed customer requirements to create custom software solutions
• Optimized existing software to improve scalability, reliability, and efficiency
• Deployed applications on cloud platforms such as Amazon Web Services, Snowflake, Microsoft Azure, or Google Cloud Platform
• Implemented robust code in multiple programming languages including Java, C++, and Python.
• Helping find future talent for the firm
• Designed and executed comprehensive test plans to identify software vulnerabilities and bugs
• Collaborated with UI/UX designers to improve software usability and user experience

• Developed Artificial Intelligence for the company using Azure Form Recognizer
• Wrote Python scripts to increase efficiency with AI model and other tasks
• Developed Data Visualization for FEMA and other government agencies
• Used platforms such as Excel, Power BI, and H20.ai to create data visualization/analysis
• Presented to the company (250+ employees) to discuss the benefits of the AI model we created
• Used Agile methodology and SCRUM framework
• Helped company win more contracts and technical work with the US government

Machine Learning (AI) Research position: Working on Multi-Task Learning for improving learning on sparse datasets. We use materials property data that is acquired by destructive testing, we rarely obtain all the properties of interest for a given sample. We are interested in MTL network architectures to improve inference using these sparse datasets. This will allow us to predict missing values for the Material Science department at Penn State which would decrease school spending on unnecessary use of school furnaces to conduct experiments. The final goal is to help other organizations decrease their spending on material testing.