Anirudh Pai Email & Phone Number

San Ramon, CA, US

Berkeley, California, United States

- Developing a full-stack application for course articulation optimization using a React/Redux/Flask/MongoDB stack- Building a natural language processing pipeline implementing sentenceBERT. Converting textual course information into semantic, euclidean-space, vector embeddings for course-to-course comparison using cosine similarity.- Researching effects.

- Designed comprehensive problem and solution sets to facilitate remote learning via OATutor platform- Responded to feedback from classroom teachers regarding platform user interface as a team- Formulated action plans and met content curation deadlines in timely manner

Menlo Park, California, United States

- Implemented RQ models with Variational Auto-Encoders and Implicit Neural Codebooks to improve cold-start media recommendation- Built distributed SQL pipelines to conduct quantization analysis, creating useful metrics for codebook usage and semantic meaning- Integrated quantizers into larger recommendation model, leading to 3% increase in hit rate using.

- Led team of six developers in development of efficient, fast, gRPC-based alternative to previous image upload system- Spearheaded the design of robust unit and integration tests to ensure compatibility with all existing backend services- Utilized Go and PHP to create six new image writer services with 79% faster runtime, optimizing transaction rate by 32%

Berkeley, California, United States

- Utilized AWS utilities such as S3 Buckets, Lambda, and DynamoDB to develop secure data storage pipeline to scrape and store status of upcoming eSport games- Implemented precise feature extraction and imputing techniques to build regression and classification pipelines to predict outcomes and statlines for upcoming eSport games- Analyzed current models’.

Berkeley, California, United States

- Migrating eSprinter Health Application from Android to iOS using the ReactNative application framework- Utilizing XCode and knowledge of Swift to build objective-C header to allow for bluetooth printer integration- Ensuring parity in app’s integrations within iOS environment through rigorous testing procedures

San Francisco, California, United States

- Developed a fraud-detecting smart contract that identifies anomalous transactions and flags them, preventing wallet drainage on Solana Chain- Utilized Next.js/Redux/Firebase/Flask stack to develop a Chrome extension interface, REST API, and data storage system- Experimented with different algorithms such as K-means to identify anomalous groups of.

San Ramon, California, United States

- Taught basics of Python and Scratch to aspiring computer scientists of a young age- Formulated organized learning curriculum tailored to each student’s needs and curiosities; reviewed foundational knowledge of algorithms and data structures to do so- Fluidly conveyed students’ educational progression to parents, maintained precise communication with.

California, United States

- Developed online platform to spark greater financial literacy internationally, reached global audience of 3000+ users- Conducted interviews to expand company, helped onboard new employees by creating welcoming environment- Led team of software developers, created list of deadlines to facilitate timely development of platform

San Ramon, California, United States

- Created efficient machine learning curriculum for aspiring machine learning engineers and data scientists- Taught the intuition behind and implementation of several machine learning algorithms - Algorithms for regression, classification, computer vision, natural language processing, etc.- Developed understandable presentations to explain concepts to.

- Instilled academic confidence in like-minded peers by urging them to pursue interests in CS- Developed structured curriculum to introduce beginner computer science concepts and work toward more advanced ideas

- Designed a machine learning pipeline in Python using Scikit-Learn and TensorFlow to detect anomalous network states- Used K-means to group unlabeled data; fed output into Support Vector Classifier to identify anomalous data points- Used K-fold validation to select best hyper-parameters and clusterer-to-classifier pairing, learned about pipeline.

Bachelor'S, Electrical Engineering & Computer Science

GPA: 4.0/4.0

Pursuing High School Diploma, General Studies

Activities and Societies: Machine Learning Club Computers and Programming Club Educore Peer Tutor