- Production-grade LLM Workflows: Successfully moved LLM workflows into production for various customers. Expected key metrics include reducing a mortgage company's case backlog from 45 days to 1 day and decreasing patient intake waitlist times by over 80% to less than 30 days, highlighting strong operational improvements.- AI Adoption: Lead customer adoption of Appian GenAI, working closely with clients across industries—financial services, healthcare, education, and logistics—to align solutions with their unique AI strategies. This includes understanding customer requirements and showcasing the time to value, high accuracy metrics, & end user business value.- Product Feedback: Provide direct, data-driven feedback to product and engineering teams, influencing critical feature development. For example, adding OCR technologies in the feature for unstructured scanned document processing and helping with the transition of a plugin into a core product feature, both driven by customer needs and insights from field experience.- Proof of Concepts: Develop comprehensive demos showcasing LLM capabilities and business value, including presenting to prospective clients. For instance, converted a "no-go" 16-week engagement into a streamlined 10-week project using Appian GenAI by showcasing rapid time to value, an extraction accuracy of ~98%, and a 5x reduction in manual extraction time.

- Process Mining: Identified time inefficiencies and work errors in the institutional client onboarding process at a major financial bank; Recommended four major actions that would potentially save ~25,000 days/year of cycle time and 150 days/year of handling time.- SQL based data transformation: Developed a SQL procedure-based data transformation pipeline as an alternative to Python data transformations for process mining in an effort to provide Appian native solutions for customers.

- Developed a python program using Beautiful Soup to retrieve information about where Heinz alumni are working currently and to analyze promotion rates, employee turnover, industry and region preferences, etc.

Statistics for IT Managers

- Data Engineering and Web Mining: Developed a multi-threaded asynchronous script using Python which fetched information using API requests from KCF’s SmartDiagnostics website reducing download time by 30x - Feature Engineering and Outlier Detection: Created an algorithm for ~400,000 data points to prevent misclassification of non-faulty assets by eliminating vibration noise from such assets before ingestion into the ML model

- Market Analysis and Strategy Research: Conducted market research and analysis for a novel carbon product that would increase the end-product strength by 70% and cut user costs by 50%; Secured funding of ~$207,000 from U.S. Dept. of Energy- Data Visualization, and Commercial Focus: Developed data visualizations using Tableau to determine how close the carbon black industry is to the US shale oil basins; This data was considered crucial for the commercialization plan- Innovation and Problem Solving: Led lab-scale experiments that resolved the issue of dispersing carbon in water used for concrete; The solution enhanced the properties of concrete used in pavements, bridges, and stadiums by 20%

- Project Management, Decision-making, and Execution: Conceptualized, designed, built, and evaluated a fluidized bed reactor which was implemented to work with the pilot system; Utilized Python’s matplotlib and Pandas libraries to generate meaningful plots which supported in securing an additional funding of ~ $382,000- Analytics, Statistics, and Client Interaction: Created an automated image analysis method to determine the carbon particle size using edge detection and statistical methods; Presented to management as a key performance indicator for business growth - Leadership and Presentation: Managed the operation of the pilot system and delivered test reports to management providing insights for efficient planning of experimental campaigns- Technical Writing and Communication: Compiled technical reports highlighting the premise, results, and analyses to unify project information, explain observations and results, and answer important questions when referred to in the future

- Assembled and supported operation of a 6-kW microwave plasma reactor for graphene generation from natural gas.- Utilized analytical equipment (gas chromatography, GC-MS) along with extraction equipment (Soxhlet extractor, Rotovapor) to separate by-products and evaluate product chemical composition.- Developed SOPs for the microwave plasma reactor, the analytical equipment and the extraction equipment.- Engineered an in-house calcination process that successfully improved product conductivity by 4 times.- Trained an intern about the niche techniques needed to assemble the reactor.

- Conducted experiments to evaluate solvent quality, chain dynamics and glass transition temperatures of neutral polymer (cellulose) in green solvents using rheology equipment (Ares-G2, Capillary viscometer & DHR-3).- Interpreted and analyze quantitative and qualitative results to devise future experiment parameters.- Publications: Rheology of dry native cellulose in solution with ionic liquids (presentation) for the Society of Rheology meeting in October 2018.

Oversaw all club functions, managed board members and all home events.

Oversaw and monitored all financial activities of the club.

- Assisted in the separation & post-processing of active pharmaceutical ingredients and interpreted the data for written reports enhancing research & analytical skills.- Formulated tablets using the double rotary tablet press machine and learned about patents & copyright issues from the intellectual property team.