Asad Sheikh Email & Phone Number

New York, United States

- Researched predictive visualization recommendation systems with the Data Interaction Group.- Created fully functioning code editor and table visualizer using Svelte and duckdb-wasm.- Analyzed NYTimes articles on 20th century Latin American geopolitical conflicts using Natural Language Processing methods to determine efficacy of passive voice usage as a.

- Mentored 10 students each semester on intensive term projects showcasing mastery of Python.- Implemented weekly student wellness events to help alleviate student stress.- Oversaw weekly group of 7 TAs to tutor students.- Created tracker to monitor student performance and identify struggling students.

- Developed a Bidirectional LSTM deep learning model to identify disease progression events for non-small cell lung cancer patients.- Explored and evaluated potential applications of synthetic data generation to create deidentified datasets.- Assessed and presented on value of using cancer patient billing data to enhance and validate current research.

- Analyzed feelings of safety of BIPOC teenagers in the Pittsburgh area with the Alliance for Refugee Youth Support and Education.- Worked with the Family Independence Initiative to analyze and visualize income level changes in low-income households over two years.- Performed analysis to determine significant social and financial factors that impact a.

- Utilized Natural Language Processing to automate data mapping process for product data. - Implemented Google Maps API to automate geocoding and validation of 60,000 rows of address data. - Employed Python and BeautifulSoup to automatically scrape and capture all text and dropdown fields of internal search pages.

- Created persona for virtual assistant (chatbot) capturing best aspects of the ways customers interact with the brand including in-person, FAQs, and online customer help as well as digital appearance.- Researched, developed and delivered business engagement plan case study for Fortune 50 companies across various verticals.- Exercised the entire business.

- Analyzed student learning data through creating statistical models to represent learning curves.- Visualized models that best represented learning curves using number of opportunities to answer and concept being tested.- Analyzed accuracy of different learning curve models in LearnSphere and R.

- Performed psychological analysis of sounds and determined their similar acoustic features using statistical analysis and machine learning methods.- Designed and ran experiment to test how participants judge the physical causes of sound events.- Analyzed data in MATLAB, R, and SPSS Statistics.- Submitted abstract to APCAM 2019: Auditory Perception.