added a non-exhaustive list of contributors

README.md

@@ -17,6 +17,7 @@ We are in an early-release Beta. Expect some adventures and rough edges.
 - [Getting Started](#getting-started)
 - [Communication](#communication)
 - [Releases and Contributing](#releases-and-contributing)
+- [The Team](#the-team)
 
 | Python |  **`Linux CPU`**   |  **`Linux GPU`** |
 |--------|--------------------|------------------|
@@ -180,8 +181,16 @@ Sending a PR without discussion might end up resulting in a rejected PR, because
 
 **For the next release cycle, these are the 3 big features were are planning to add:**
 
-1. [Distributed PyTorch](https://github.com/pytorch/pytorch/issues/241) (a draft implementation is present in this [branch](https://github.com/apaszke/pytorch-dist)
+1. [Distributed PyTorch](https://github.com/pytorch/pytorch/issues/241) (a draft implementation is present in this [branch](https://github.com/apaszke/pytorch-dist) )
 2. Backward of Backward - Backpropagating through the optimization process itself. Some past and recent papers such as
    [Double Backprop](http://yann.lecun.com/exdb/publis/pdf/drucker-lecun-91.pdf) and [Unrolled GANs](https://arxiv.org/abs/1611.02163) need this.
 3. Lazy Execution Engine for autograd - This will enable us to optionally introduce caching and JIT compilers to optimize autograd code.
 
+
+## The Team
+
+PyTorch is a community driven project with several skillful engineers and researchers contributing to it.
+
+PyTorch is currently maintained by [Adam Paszke](https://apaszke.github.io/), [Sam Gross](https://github.com/colesbury) and [Soumith Chintala](http://soumith.ch) with major contributions coming from 10s of talented individuals in various forms and means. A non-exhaustive but growing list needs to mention: Sergey Zagoruyko, Adam Lerer, Francisco Massa, Andreas Kopf, James Bradbury, Zeming Lin, Yuandong Tian, Guillaume Lample, Marat Dukhan, Natalia Gimelshein
+
+Note: this project is unrelated to [hughperkins/pytorch](https://github.com/hughperkins/pytorch) with the same name. Hugh is a valuable contributor in the Torch community and has helped with many things Torch and PyTorch.