I’m currently interested in a few things:
- Integrating Vision as additional context for language models, so we can eventually generate, understand and edit images better.
- Using agent workflows to automate a bunch of tedious and repetitive tasks.
Reach out if you want to chat.
Email me at: a7anand@ucsd.edu
Tesla - Machine Learning Engineer Intern
- ML pipeline for anomaly detection for Megapacks.
Halıcıo˘glu Data Science Institute — Machine Learning Researcher
- vLMs, Diffusion, Perception — Zhuowen Tu.
- World Models, Agents — Zhiting Hu.
Ivanti - Software Engineering Intern
- LLM Hallucination Reduction
Cognitive Science Department - Instructional Assistant
- COGS 18, Introduction to Python — Shannon Ellis.
- COGS 9, Introduction to Data Science — Bradley Voytek.
HCLTech — Software Engineering Bootcamp
- ML Pipeline for anomaly detection from KPI data.
AutoBots: RL-Based Autonomous Driving
- Trained self-driving agents using RL on CARLA and DonkeySim; designed reward functions for navigation performance.
Energy Telemetry Pipeline
- Built a Spark + Airflow telemetry lakehouse with data quality metrics and curated features for ML/BI.
Comparative Analysis of Modern Object Detection Algorithms
- Compared RCNN, YOLO-World, and GroundingDINO on a curated dataset with robustness evaluation.
sEMG Gesture-Controlled Toy Car
- Built a wearable sEMG system and classified gestures with KNN at ~98% accuracy.
Comparative ML Model Analysis
- Compared ANN, XGBoost, SVM, and Random Forest with SMOTE, encoding, and tuning.
Loan Default Risk Prediction using Machine Learning
- Analyzed 2.2M+ LendingClub loans (2007–2018), compared SVM/KNN/RF, and addressed fairness concerns.