Merge branch 'master' of https://github.com/uhm-descartes/uhm-descart…

…es.github.io

README.md

@@ -1,16 +1,16 @@
-# UHM Descartes Project page
+# UHM Descartes Project Site
 
-If you are changing the structure of this site, you will want to consult the documentation for the [Minimal Mistakes](https://mmistakes.github.io/minimal-mistakes/) Jekyll theme.  If you are simply adding content, you shouldn't need to know much more than what is presented below. 
+If you are changing the structure of this site, you will want to consult the documentation for the [Minimal Mistakes](https://mmistakes.github.io/minimal-mistakes/) Jekyll theme.  If you are simply adding content, you shouldn't need to know much more than what is presented below.
 
-## How to edit this site
+Here's how to do it.
 
-### 1. Obtain write permission to the repo
+## 1. Obtain write permission to the repo
 
 First, you must have write access to <https://github.com/uhm-descartes/uhm-descartes.github.io>. 
 
 A quick way to see whether you have write access is to check whether or not there is a "pencil icon" in the upper right corner of the [README.md](https://github.com/uhm-descartes/uhm-descartes.github.io/blob/master/README.md) file. If you don't see a pencil, contact Prasad or Philip with your github username and one of them will provide you with permissions.
 
-### 2. Set up your gitpod.io workspace
+## 2. Set up your gitpod.io workspace
 
 The simplest way to edit this site is by using <https://gitpod.io>:
 
@@ -50,7 +50,7 @@ Click it, and the site will appear in a new browser tab:
 
 Installation is now complete. You can now edit and (when ready) publish the site. 
 
-### 3. Edit the site
+## 3. Edit the site
 
 Editing the site is an iterative process of:
 
@@ -67,11 +67,11 @@ In that case, simply switching to the browser tab containing the built site and
 
 In other cases (such as when you edit config files), you may need to restart the Jekyll server to see the changes.  In this case, select the Terminal window, then press `control-c` (to terminate), followed by `control-p` (to retrieve the previous command, which is `bundle exec jekyll serve`), then `return` (to restart Jekyll).
 
-### 4. Publish the site
+## 4. Publish the site
 
 When you are done editing, you should commit and publish your changes. This means sending your edited source files from gitpod.io to github.com.  The github.com repo is configured to automatically build and publish the site whenever commits are made to the repo. 
 
-#### 4.1 Give GitPod permission to write to the repo
+### 4.1 Give GitPod permission to write to the repo
 
 If you are a first time user of GitPod, you need to give GitPod permission to commit changes to GitHub. Here's how to do it:
 
@@ -103,7 +103,7 @@ Make sure all of the permissions are selected, then click “Update Permissions
 
 Now GitPod has all of the permissions necessary to commit your changes, which we'll do in the next section.
 
-#### 4.2 Commit your changes to master
+### 4.2 Commit your changes to master
 
 To publish the site, first notice that after editing a file, a blue dot will appear over the "Source Control" icon on the left side of the VS Code browser tab:
 
@@ -121,15 +121,17 @@ Please select "Commit and Sync". (This will both push your changes to GitHub, an
 
 If you now go to the "Actions" tab of the GitHub repository page, you'll see that GitHub is now building the site:
 
-<img src="README-screenshots/gitpod-10.png"/>
+<img src="README-screenshots/gitpod-11.png"/>
 
 Once there is a green arrow to the left of the "pages build and deployment" action, you should now be able to see your changes reflected in the published site at <https://uhm-descartes.github.io/>.
 
-### How to help build and manage this site
+## 5. Beyond basic markdown
+
+If you want to go beyond basic markdown, you will need to consult the [Minimal Mistakes](https://mmistakes.github.io/minimal-mistakes/docs/quick-start-guide/) documentation. Philip has done some basic customization of the defaults; you can contact him for guidance. 
 
-### NRT Project Sites
+## 6. NRT Project Sites
 
-First, I recommend that you review some of the existing NSF NRT project sites for ideas. Here are a few:
+You can find helpful examples of the content and structure of our site by looking at other NRT sites.  Here's links:
 
 * https://futurerivers.uw.edu/
 * https://aim-nrt.pratt.duke.edu/

_pages/apply/overview.md

@@ -3,31 +3,4 @@ permalink: /apply/overview/
 title: "Apply: Overview"
 ---
 
-## Why NRT?
-
-UHM Descartes is a multi-disciplinary National Science Foundation Research Traineeship (NRT) program at the University of Hawaii (UH) at Manoa. The NRT trainees will have great opportunities to participate an unique graduate program and conduct cross-disciplinary research. At the end of the program, the trainees will master the essential skills in **data science and artificial intelligence (AI)**, and work on **cutting-edge research projects** from a variety of disciplines (engineering, computer science, social science, business, and medicine). 
-
-If eligible, the traineess may also receive a **generous stipend (~$34K per year) and tuition waiver for up to two years**.
-
-For more details of our program, please visit [the About page](../about.md).
-
-## Eligibility
-
-Our NRT program hosts both funded and non-funded trainees. To be a trainee, you need to
-- be in good academic standings;
-- more importantly, be passionate about data science and AI!
-
-To be a **funded** trainee, you need to be a **U.S. citizen or permanent resident**, which is required by the NSF.
-
-If you are **not eligible** for funding, you are also encouraged to **contact [the NRT faculty](../people/leadership-team.md) about potential fundings from other sources**.
-
-
-## How to apply?
-
-- **Step 1.** Please fill out [the Application Form](https://forms.gle/D37NfAoUqhFayUse7). In the application form, you will be asked to
-    - update your CV;
-    - identify research areas of your interests (please see [the Research page](../research/overview.md) for more details);
-    - indicate whether you are eligible for the stipend;
-    - update your undergraduate and graduate (if any) transcripts.
-- **Step 2.** Please have at least two referees to send the reference letter to [email protected].
-- **Step 3.** You need to enroll in a graduate program at UH Manoa to participate in our NRT program. If you are not a graduate student yet, please go to the [Graduate Division Application website](https://manoa.hawaii.edu/graduate/how-to-apply/) for instructions on how to apply.
+Content goes here.

_pages/research/fundamental.md

@@ -0,0 +1,6 @@
+---
+permalink: /research/fundamental/
+title: "Research: Fundamental Research"
+---
+
+Content goes here.

_pages/research/wireless.md

@@ -3,21 +3,4 @@ permalink: /research/wireless/
 title: "Research: Wireless Systems"
 ---
 
-The research training in communications, networks, and security areas focues on creating NextG wireless systems with enhanced communication performance, novel sensing functionalities, strong attack resiliency, and high energy efficiency, for uses in Augmented, Virtual or eXtended Reality (AR/VR/XR), autonomous driving, massive interactive real-time applications, advanced industrial, manufacturing, and telehealth. Specifically, we design wireless systems and algorithms to control or explore the wireless propagation characters, thus improving signal quality, achieving ubiquitous, low-power sensing, and preventing or reducing attack vectors, such as jamming and eavesdropping.
-
-**Wireless Sensing for Physiological Monitoring.** 
-The NextG wireless vision create precise representations of the physical world using wireless signal calls for new sensing solutions that extend beyond traditional radar functions of localization, tracking, and object recognition. Wireless sensing using the mobile communication network as a sensor (with the evolution of cellular systems to mmWave bands and sub-THz bands, deployed in small cell configuration) has the potential to become a key component of NextG wireless systems. However, the challenge is to achieve sub-wavelength sensing accuracy and multiple target separations through a communication setting, which is inherently bistatic and noncoherent, (e.g. the transmitter and receiver are positioned differently and not in sync.) To address this challenge, we develop algorithms and tools that leverage the spatial diversity of a multiple antenna system or the frequency diversity of a wideband single antenna system to detect and separate close-by targets accurately. The former utilizes multiple antennas at the receiver to observe different signal mixtures from the multiple targets and separate them via blind source separation technique. The latter exploits the phase differences among multiple paths at different frequencies to create different signal mixtures from the multiple targets, then separates them in the frequency domain by suppressing individual signals sequentially. Both methods allow us to detect and characterize tiny motions such as chest movements due to respiration, which we use to verify a patient’s identity during
-at-home sleep apnea test or establish a trusted link between two devices observing the same patient.
-
-**Wireless Physical Layer Security.**
-NextG wireless network systems will connect billions of heterogeneous Internet of Things (IoT) devices to billions of people and enable machine-to-machine communications. The proliferation of low-cost devices with wireless connectivity presents grave security challenges as massive and automatic key exchanges are impractical within a heterogeneous network. Therefore, great interest has been drawn to the physical layer of the communication stack, seeking to leverage the uniqueness of the wireless channel, location, motion, time, trajectory, velocity, and physiological/biokinetic signals to enhance security. However, physical properties often contain insufficient entropy (randomness) and are prone to prediction-based attacks once the adversary learns the physical property characteristics.
-
-To overcome the limitations, we design protocols that utilize reconfigurable devices, such as pattern-reconfigurable antennas, to randomize a slow-fading, quasi-stationary wireless channel and create an artificial fast-changing channel that is difficult to predict. We develop compressed sensing algorithms for the transmitter to calculate the randomizing effect of unused antenna patterns and pre-equalize the channel for the intended receiver. As a result, the main channel state appears stable in the eye of the intended receiver but randomly changes from the attacker's perspective, which we exploit for secure communication or physical layer key generation (Fig. 4, col 3).
-
-**Wireless Communication with Intelligent Reconfigurable Surfaces.** 
-With increasing numbers of mobile devices per user, the NextG wireless networks will serve more devices, operate with low latency and less power, and provide functionalities beyond communication. However, the spectral capacity of today’s sub-6GHz wireless networks is already operating close to Shannon capacity limits. To meet the rapidly growing needs of  modern devices, high-frequency bands are being considered to host the future wireless networks as they provide wider bandwidth, directional transmission, and servess more users (while considering limited signal coverage and reduced link reliability). 
-
-To address the coverage issue at the mmWave band, we develop cost-efficient coverage extension devices, known as intelligent reflecting surfaces (IRSs), which consist of large numbers of low-cost passive/active reflecting electronic elements with reconfigurable parameters. Once deployed, they can capture signal energy proportional to their areas and re-radiate in the shape of beams towards other directions determined by the  processors or base stations, allowing NLoS or obstacle-penetrating communication. We also increase the channel diversity between nearby users in outdoor and indoor settings, which reduces interference and increases the number of servable users per area (user capacity).
-
-**Federated Learning.**
-Recent advances in electronics with enhanced capabilities of data collection and processing, along with NextG wireless systems with enhanced connectivities, creates a new paradigm in learning, namely *federated learning*. In federated learning, machine learning models are trained on the edge devices, instead in central servers, for reduced delay and improved privacy. We will develop distributed training algorithms for federated learning with provable performance and reduced communication overhead.
+Content goes here.