Aditya Khowal

Machine Learning Data foundations I work on Shepherd, Stripe’s next-generation ML feature platform, adapting the open-source Chronon platform, which enables ML teams to rapidly build consistent ML features across training and serving environments at scale. A fast and easy DSL that allows point in time correct features to be served online or computed in batch. https://stripe.com/blog/shepherd-how-stripe-adapted-chronon-to-scale-ml-feature-development https://chronon.ai/

Working in the Language Accessibility Research (LARCH) Lab, with Dr. Lucy Lu Wang, helping equitably and safely apply machine learning and AI models to improve clinical care.

Search & Recommendation systems TA Covered topics like collaborative based filters, content based filtering, deep learning recommender systems, vector based search, TF-IDF and more

Observability diagnostics team Worked on the mantis, an opensource control plane to handle real time streaming applications for logs. My project focused on redacting PII, personally identifiable information, from logs in our system before they hit splunk, without degrading performance or increasing backpressure.

Student-Athlete Academic Services CSE tutor. Tutored Intro to Comp Sci 1, 2, 3, CSE 414 database systems and CSE 373 data structures & Algorithms to student athletes for over 4 school quarters.

Worked on Alexa Active Playback Presentation (A2P2) team to deliver seamless music track transitions on Alexa multimodal devices, like the echo show series of products. Used Java, AWS, and Alexa Presentation Language to complete intern project within 12 weeks

- 1 of 5 scholars selected as part of the UW cohort - Engaged with junior and senior-level consultants at Deloitte to develop career-oriented skillsets A professional development program designed to connect diverse college sophomores to junior- and senior-level mentors at Deloitte based on industry and functional interests.

Teachers assistant for INFO 340 - client side development summer 23 Helped teach web development using HTML, CSS, JavaScript, and React to build interactive webapps. Led weekly team meetings and office hours to help students with assignments and projects.

AI optimization - Blood wastage Project • Used a data-driven stochastic time series model to predict and derive novel insights regarding blood usage and optimize ordering policy in Python. • Reduced simulated blood waste by 15% through the development and testing of a machine learning model using tensorflow and gurobipy for blood ordering policy. • Wrote and published for review a paper on optimizing blood ordering policy, contributing the literature review and methodologies sections. AI encoding - DNA encoding, Nanopore decoding project • Used Machine learning models like Guppy and Chiron to decode nanopore signals with 80% confidence. Evaluated basic data storage techniques by attempting to reverse engineer nanopore signal. • Presented my collaboration with this research group at the university research symposium.

Section leader for Stanford’s code in place teaching CS 106A! Led weekly discussion section to 7-10 students for Stanford's introductory CS 106A python course. Provided debugging & conceptual help at weekly office hours and campfire sessions. Taught concepts including programming fundamentals object-orientation , data structures , and recursion .

Graduated early