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Thinking
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Thinking

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@autonlab @Center-for-Applied-AI @WecoAI

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DhruvSrikanth/README.md

I'm a researcher at Weco AI, building LLM and VLM agents for code generation and problem solving. Previously I spent time at the Auton Lab at the Robotics Institute at CMU, where I worked on deep learning algorithms for vision, robotics and time-series. I also spend my free time working on AI safety, specifically alignment and fairness in computer vision. Prior to this, I worked on efficient deep learning for 2D-3D single-view reconstruction. In the past, I've spent some time doing applied machine learning and deep learning research at a few startups and large companies.

Apart from AI research, I enjoy high-performance computing and all the kernel/thread/cluster programming (debugging lol) that comes with it. I've made a few games, simulations, and systems.

I like to apply my research to healthcare, climate, industrial, and scientific problems. I am interested in AI and research at companies that take a practical engineering approach to innovation and impact.

Outside of research I enjoy being spending time outdoors by hiking, surfing and playing golf.

   Website    GoogleScholar    Twitter URL   

Open Source Contributions

Deep Learning
AutonFeat: A high-performance Python package for automatic and distributed time series feature extraction and selection
tsfresh: A time series feature extraction package
Denoising Diffusion Probabalistic Models (DDPMs)
2D-3D Single View Reconstruction
pynn (Deep Learning Framework with pure NumPy Computation)
VanillaGAN (Vanilla GAN experimentation library)
ConditionalGAN (Conditional GAN experimentation library)
DCGAN (DC GAN experimentation library)
PSNRGAN (Contrastive PSNR GAN experimentation library)
Monocular Depth Estimation
Neural Artistic Recreation (A CLI for Neural Style Transfer)
High-Performance Computing
CUDANN (Distributed Deep Learning Framework accelerated on NVIDIA GPUs)
FastConv (Multithreaded GPU CUDA kernels for Convolution)
Ray Tracing (using Monte-Carlo Algorithm on GPU Accelerators)
Advection Diffusion Simulation (Multithreaded, Shared Memory Parallelism, Distributed Memory Parallelism)
N Body Particle Simulation (Multithreaded, Shared Memory Parallelism, Distributed Memory Parallelism)
Distributed Poisson Solver (using Conjugate Gradient Optimization)
Image Editor via Convolutions (using Work Stealing and Work Balancing parallel schemes)
Sparse Linear Solver (using the Map Reduce parallelism scheme with Conjugate Gradient Optimization)
Image Editor via Convolutions (using Pipeline and BSP parallel schemes)
Twitter Application (using Producer-Consumer parallelism model)
Machine Learning
Boosting and Boostability (An understanding through Computational Learning Theory)
Financial Forecasting of TSLA (using sentiment analysis, feature engineering, and RNNs)
Computer Systems
GoLLUM - A GoLang Compiler
Unix Shell
Games
Climbing Mount Everest (A text-based adventure game)
Other
Useful Algorithms
Superconductor Regression (Kaggle Challenge)
Canvas Web Application
Blood Donations Database

Pinned Loading

  1. pytorch/pytorch pytorch/pytorch Public

    Tensors and Dynamic neural networks in Python with strong GPU acceleration

    Python 85.3k 23k

  2. pytorch/torchtune pytorch/torchtune Public

    PyTorch native post-training library

    Python 4.5k 468

  3. huggingface/text-generation-inference huggingface/text-generation-inference Public

    Large Language Model Text Generation Inference

    Python 9.5k 1.1k

  4. blue-yonder/tsfresh blue-yonder/tsfresh Public

    Automatic extraction of relevant features from time series:

    Jupyter Notebook 8.5k 1.2k

  5. WecoAI/aifn-python WecoAI/aifn-python Public

    Client side API for building and deploying AI functions

    Python 4

  6. autonlab/AutonFeat autonlab/AutonFeat Public

    A High Performance Library for Time-Series Featurization.

    Python 24 1