Venkat Ramaraju

experience

• swe iii @ tabapay jan'23 - present
• sde @ amazon lab126 jun'22 - jan'23
• swe @ redhat may'21 - jun'22
• researcher @ compact x-ray free electron lab jan'21 - may'21
• teaching assistant, cse 110 @ asu 3 semesters

education

• bachelors in computer science @ arizona state university aug'18 - dec'21

  graduated early with a 4.0 GPA

projects

• polydb: a vector database written from scratch in go

  trained an embedding model from scratch via sgns + pytorch. apiserver communicates with vector services via grpc. more training runs in progress.

  at some point, i may completely overhaul the model and train it to align semantically similar sentences from different languages into similar vector spaces. this would allow users to search various documents in whatever language they would like.

• polyglot: a multilingual tokenizer implemented from scratch in go via the byte-pair encoding algorithm.

  achieves uniform compression and fertility across across 10 diverse scripts. training to achieving 5.0 compression in progress.

• dataquest.ai: an authenticated ai natural language querying tool for documents, datasets, videos, emails, etc.
  this application implements rate limiting, request caching, and connection pooling from scratch.

  leverages pinecone, langchain with gpt3.5 turbo, gmail api, youtube transcription api, and stripe api integrations.

• interspersed bilingual decoder (ibd): a code-mixing decoder-only model fine tuned on top of LLama-3.1.

  generated hinglish code-mixed datasets using pos tagging with stanza/spacy, performed sft + dpo for alignment. working on additional tests right now.

• agora: stock recommender based on public sentiment

  uses VADER sentiment analysis models, daily web scrapers using selenium, yfinance api, xgboost and random forest ensemble models

  big shoutout to Dr. Ajay Bansal and his PhD student James Smith for their support in elevating this project.

papers

• Forecasting Stock Market Performance: An Ensemble Learning-Based Approach

  Journal paper - Nominated by AIKE 2023 chairs for the IJSC 2024 edition

• Forecasting Stock Market Performance: An Ensemble Learning-Based Approach

  Long paper - AIKE 2023, Published in IEEE Xplore

• A Sentiment Analysis Based Stock Recommendation System

  Long paper - AIKE 2022, Published in IEEE Xplore

• Agora: Introducing the Internet's Opinion to Traditional Stock Analysis and Prediction

  Short paper - ICSC 2022, Published in IEEE Xplore

interesting (recent) reads & listens