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Résumé

Aakash Madabhushi

The full version is below so you don't have to open a file. Available from December 2026, in the San Francisco Bay Area, and open to relocating.

aakash.vardhan15@gmail.comlinkedin.com/in/aakash-vardhangithub.com/aakashvardhan

Last updated August 2026

Education

M.S. Applied Data Science, San José State University
Expected Dec 2026
AI & Machine Learning Operations Graduate Certificate, Indian Institute of Science (IISc)
B.S. Artificial Intelligence, Illinois Institute of Technology
May 2023

Experience

Instructional Student Assistant, Machine Learning · SJSU Department of Applied Data Science

Aug 2026 to present

  • Support machine learning instruction alongside my research work.

Graduate Research Assistant · SJSU Department of Applied Data Science

Mar 2026 to present

  • Built an end-to-end LeRobot v3 data pipeline for SO-101 pick-and-place imitation learning, synchronizing 6-DoF joint state and action trajectories with dual 640x480 RGB streams at 30 FPS, and published 50 teleoperated episodes (49,633 frames) to Hugging Face.
  • Developed pre-training quality gates over Parquet metadata and H.264 video, validating episode and frame alignment, video decodability and resolution, and NaN-free action and proprioceptive tensors.
  • Engineered a reproducible PyTorch/CUDA training pipeline for 52M-parameter Action Chunking Transformer policies with configurable augmentation, Weights & Biases tracking, 5K-step checkpointing, and resume support, completing 30K- and 60K-step runs.
  • Built a resumable physical-robot evaluation pipeline for a 100-trial fixed and randomized cube-placement protocol with automatic return-to-start, stale-cache guards, placement-error measurement, and success/grasp/failure logging. Completed all 50 fixed-position rollouts at 92% success and 2.49 cm mean placement error.
  • Building physics-based manipulation simulations in Isaac Sim and MuJoCo for SO-ARM101 and Franka Emika Panda arms, validating control algorithms before deployment.

Software Engineer · Sapaad

Jun 2023 to Oct 2024

  • Built production data pipelines processing 5M+ daily rows across a multi-tenant SaaS platform using Databricks and PySpark for recommendation model feature extraction.
  • Optimized 10+ Spark jobs through SQL window function tuning and caching, reducing dashboard query latency by 20% across 75+ tenant instances.
  • Implemented a Delta Lake data quality framework with automated schema validation and anomaly detection for production ML.

Computer Vision Engineer Intern · Toothlens

Sep to Dec 2022

  • Developed computer vision pipelines for an orthodontic alignment assessment prototype, enabling automated detection of teeth positioning from smartphone images.
  • Optimized a PyTorch GAN pipeline by integrating OpenCV for geometric normalization, improving model recall by 9% and reducing image preprocessing failures.
  • Designed evaluation protocols to benchmark model performance across edge cases including partial occlusion and low resolution.

Research Assistant · Illinois Institute of Technology

Sep 2019 to Mar 2020

  • Automated tweet collection through the Tweepy API and generated FastText embeddings to identify water-related disaster events.
  • Trained an SVM classifier to 85% accuracy, adding GridSearchCV hyperparameter tuning for a further 7% gain.

Skills

Machine learning & robotics
PyTorch · CUDA · scikit-learn · pandas · LeRobot · ACT · SmolVLA · Imitation learning · Teleoperation · NVIDIA Isaac Sim · MuJoCo · ROS 2 · OpenCV · Weights & Biases · Hugging Face Hub
Data & pipelines
Python · SQL · PySpark · Databricks · Spark SQL · Delta Lake · Parquet · Airflow · dbt · Snowflake · Kafka
LLM applications & retrieval
LangGraph · LangChain · Llama 3.3 · Llama 3.2 Vision · Groq · Pinecone · ChromaDB · Sentence Transformers
Services & delivery
Docker · FastAPI · GitHub Actions · AWS EC2 · React · TypeScript
Also worked with
JavaScript · SwiftUI · Vite · Chrome MV3 · Gemini Nano · Cloud Firestore · MongoDB · Redis · MySQL · Streamlit · PyTorch Geometric · RoBERTa · Grad-CAM · Cross-attention fusion · Mel spectrograms · Fine-tuning · Retrieval-augmented generation · Gazebo · CycleGAN · Pix2Pix · Variational autoencoders · SSIM

Projects

The rest of the work is on the home page, with the code and data behind each one.