diff --git a/README.md b/README.md
index 8d05857..2ed66df 100644
--- a/README.md
+++ b/README.md
@@ -1,22 +1,24 @@
 # Simulator for quantum networks and channels
 
-<img align="right" src="/docs/source/img/superdenseAEB.png" width=400>
+<!-- images are hard-linked so they will show up on pypi page -->
+
+<img align="right" src="https://github.com/att-innovate/squanch/blob/master/docs/source/img/superdenseAEB.png" width=400>
 
 SQUANCH (Simulator for QUAntum Networks and CHannels) is an open-source Python framework for creating performant and 
 parallelized simulations of distributed quantum information processing. Although it can be used as a general-purpose 
 quantum computing simulation library, SQUANCH is designed specifically for simulating quantum *networks*, acting as a 
-sort of "quantum playground" to test ideas in quantum transmission and networking protocols. The package includes 
-flexible modules that allow you to intuitively design and simulate a multi-party quantum network, extensible quantum 
-and classical error models which introduce realism and the need for error correction in your simulations, and a 
-multi-threaded framework for manipulating quantum information in a performant manner.
+sort of "quantum playground" to test ideas for quantum networking protocols. The package includes flexible modules that 
+allow you to easily design and simulate complex multi-party quantum networks, extensible classes for implementing quantum 
+and classical error models for testing error correction protocols, and a multi-threaded framework for manipulating quantum
+information in a performant manner.
 
 SQUANCH is developed as part of the Intelligent Quantum Networks and Technologies ([INQNET](http://inqnet.caltech.edu)) 
-program, a collaboration between AT&T and the California Institute of Technology. 
+program, a [collaboration](http://about.att.com/story/beyond_quantum_computing.html) between AT&T and the California Institute of Technology. 
 
 ## Documentation
 
 Documentation for this package is available at the [documentation website](https://att-innovate.github.io/squanch/) or 
-as a pdf manual [here](/docs/SQUANCH.pdf).
+as a [pdf manual](/docs/SQUANCH.pdf). You can also view the presentation given at the 2017 INQNET Symposium [here](https://indico.hep.caltech.edu/indico/getFile.py/access?sessionId=1&resId=1&materialId=0&confId=131).
 
 ## Installation 
 
@@ -30,7 +32,12 @@ If you don't have pip, you can get it using `easy_install pip`.
 
 ## Demonstrations
 
-Demonstrations of the framework's capabilities can be found in the [demos](/demos) folder and in the [documentation](https://att-innovate.github.io/squanch/demos.html).
+Demonstrations of various quantum protocols can be found in the [demos](/demos) folder and in the [documentation](https://att-innovate.github.io/squanch/demos.html):
+
+- [Quantum teleportation](https://att-innovate.github.io/squanch/demos/quantum-teleportation.html)
+- [Superdense coding](https://att-innovate.github.io/squanch/demos/superdense-coding.html)
+- [Man-in-the-middle attack](https://att-innovate.github.io/squanch/demos/man-in-the-middle.html)
+- [Quantum error correction](https://att-innovate.github.io/squanch/demos/quantum-error-correction.html)
 
 As a simple example to put in this readme, let's consider a simulation of
 a transmission of classical data via [quantum superdense coding](https://en.wikipedia.org/wiki/Superdense_coding). In this
@@ -38,7 +45,7 @@ scenario, we have three agents, Alice, Bob, and Charlie. Charlie will distribute
 send data to Bob by encoding two bits in the Pauli-X and -Z operations for each of her photons. Bob receives Alice's photons and 
 disentangles them to reconstruct her information, as shown in the following diagram.
 
-![](docs/source/img/superdenseABC.png)
+![](https://github.com/att-innovate/squanch/blob/master/docs/source/img/superdenseABC.png)
 
 Simulating complex scenarios with multiple agents like this one is what SQUANCH is designed to do. The quantum states of large
 numbers of particles can be efficiently dealt with using `QStream` objects, and the behavior of each agent can be defined by 
@@ -110,4 +117,4 @@ received_img = np.reshape(np.packbits(out["Bob"]), img.shape)
 plt.imshow(received_img)
 ``` 
 
-![Alice transmitting an image to Bob over 1km simulated fiber optic cable.](docs/source/img/transmissionDemo.png)
+![Alice transmitting an image to Bob over 1km simulated fiber optic cable.](https://github.com/att-innovate/squanch/blob/master/docs/source/img/transmissionDemo.png)