Computational Art to introduce computing for CS0 and Outreach

After Attending an AI session at the Grace Hopper Conference I participated in a GFX session/workshop.

The first task for the participants of the workshop was to be creative! Draw yourself as the master of code in 30 seconds. This helps to “stretch”- to be creative. – (See my drawing below)

IMG_4638 (1)

Processing is an open source programming language and environment for people who want to learn code.

The CS0 class teaches how to learn computer science via games, music, mobile robotics ,securtiy and computational art.

Why should we care? In a study it was concluded that introducing this learning style can increase the number of people who see themselves in computer science in the future. This context based style teaching computer science has improved grades and graduation rates.

Human vision system is the largest system in our brain. Its good to put that part of the brain to use!

Why creativity?

Its something we can help people explore and learn. We can help people to problem solve by pushing people to expand their creativity.

The participants were asked to download processing.org

First, we  coded an ellipse together. With a couple of lines of code we created a small animation.

One method of teaching is asking student to look at code and then ask them to predict what the code will do.

Click here for a quick tutorial that goes over material similar to the work we did in this workshop.

Fun art styles to look into-

  • Art nouveau
  • impressions- implicit equations
  • Popart- arrays and data structures
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Using Artificial Intelligence to Solve Complex Problems

image1Managing fraud, recognizing speech, and creating more autonomous robots are just three areas that use artificial intelligence to come to grips with complexity. In this panel, industry and academic experts Tara Sainath,  Lydia Kavraki, and Jin Zhang discussed how they use cutting-edge techniques such as deep neural networks and path-finding algorithms to solve real-world problems.

Today I attended the Artificial Intelligence to Solve Complex Problems session. The speakers in this panel were Tara Sainath,  Lydia Kavraki, and Jin Zhang.

I found all of the topics covered in this session very interesting.

Below are the responses of the panelist for each question.

How did you get into your field of study? 

Lydia

Lydia shared her very relatable experience in grad school that helped her to get into Robotics. Much like my experience, she kind of stumbled into the field and found that she loved robotics! She wen on to briefly speak about the advancements of robotics.

Tara Sainath:  Tara started in AI because a professor asked her if she would be interested in it. She gave it a try and fell in love. She went on to get her masters and PHD. Again, I can really relate. I too stumbled into research after working with a professor for my senior project.

Jin Zhang: Jin started in Graduate school working as an RA. She first associated data with building applications but realized that the world was ran on large databases. She expressed how  cool it is that we now have the  ability to collect data and serve it right back to customers. AI has given us a lot of capabilities in data management and analysis.

How is AI affecting your field?:

Lydia: Senses have really helped with collecting data in AI. Computing the data has driven research for so many years. Robotics learning to work with humans is continually developing as a result of research.

Tara:   Tara works with acoustics modeling. This involves feature recognition and translation modeling and signaling modeling. Single biggest advancement is speech recognition is decreased error rates. Error rates have gone down because of the large amounts of data collected over time.

Gin: Gin stated that AI has drastically helped with problem solving. There are all common data points such as pass codes and security questions. She explained that there is a delicate balance where we need to know how much info is enough to know who is who.  She was able to deploy  a risk factor score that boiled down to – how can we quickly identify thumbs up or down with out inconveniencing the user. AI has allowed us to detect this information with out bugging the user. AI has opened up an angling approach to problem solving. She went onto explain how once you have data you have to process it. Its important to consider where and how is it processed. Now we ask questions like -What are we looking for? AI is powerful because it can show us what the data means with out us even knowing what to look for.

How are Deep neural networks used in acoustic modeling?

Tara: Tara uses deep neural networks in acoustic modeling. The benefit is that they had GPUs to train faster allowing for more layers. Training models involved, 1- reduce speaker variations and  2- discriminate training packets. Lower layers of the network capture speaker variances. Neural networks are great at feature recognition. More recently she has been looking into computation neural networks.

How are deep neural networks used in robotics?

Lydia: Lydia explained how neural networks are used differently. In other fields you know what the answer is and know what you are looking for but in robotics that is not always the case. She imagined that it will become more prevalent in robotics in the future.

What enables neural networks to be successful in your apps?

Gin: She explained that at one point there was a lot of complicated data but we weren’t processing it fast enough. The cloud has drastically help us to speed up the process. Genome sequencing used to be costly but now it is a lot less costly because of cloud computing. She expressed how she relies heavily on computing power.

What kind of data allows you to do your research?

Lydia: In robotics you produce a massive amount of data. Its used in many ways. Data is sent to the cloud , sensing data etc. The big questions are, what kind of data is needed, when to use it, where to store it , and how is it applicable to robotics?

Speech recognition- how do you leverage all the data?

Tara: Neural networks. If she trained her data using GPUs it would take a long time. Amazon uses GPUs but they quantize the machine to speed it up. IBM specializes software architecture that speeds up processing.

Its important when solving complex problems to look at cross platform efforts in different fields.

What suggestions do you have for researchers to make connections?

Lydia:

Lydia feels that we all have the responsibility to be open minded. She highly suggested that researchers look into fields that they aren’t working on for inspiration. She went to talks, and did research on complex algorithms. She was facinated about what she found on how people viewed emotion. People were willing to listen to her but she also had to listen to others. She went to talks and learned the language, terminology of the field and became engulfed with what she was learning.

Business advice:

Dont talk about features to customers that are not in the same field because you will confuse the heck out of them. If you are talking to a data scientist or then feel free to talk about your data science features but other wise zip it.

This was a great session! I am so glad that I was able to attend and capture such great information. I am currently working on an AI project and am starting to learn more and more about models such as Neural networks. Hopefully I’ll be able to connect with one of the speakers before the conference is over!

Robotics

Speach Recoginitions and

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“Write Once,Run Anywhere” The Mobile Developer Pipedream – Paola Castro -Notes

IMG_4616 (1)With the increased need to provide apps for numerous platforms namely, Android, iOS and the web, maintaining and scaling mobile applications is one of the greatest challenges for mobile developers.

In this session Paola spoke on the technologies that allow for maintaining a single code base, their pros and cons and SurveyMonkey’s strategy in this matter.

SURVEY MONKEY -UNIFYING CODEBASE

  • Best user interfaces for mobile devices are done natively
    Native app- is written in the language specific for that particular OS.
    Example- objective c, swift
  • Native OS/languages are optimized for user experience

It causes slower development to manage multiple platforms.

How to deal with these problems?

Establish requirements

  • navigation
  • gesture recognition
  • third party libraries,
  • html rendering

Decide on strategy

  • Frameworks approach
  • Hybrid approach

Implement- Native part of the Hybrid Approach

Choose Native features that work well on both platforms.(ie Swipe gesture)

 

 

 

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IOT and Emerging Tech: Gina Sprint Presentation

 

IOT and pres431s2-auth_pic_0EMERGING TECH -Gina Sprint

PHD STUDENT OF WASHINGTON STATE UNIVERSITY

Gina Sprint received a B.S. degree in computer science from Eastern Washington University, Cheney, WA, in 2012. Currently she is working toward the Ph.D. degree in computer science at Washington State University, Pullman, WA. She is a National Science Foundation Fellow in the IGERT Integrative Training Program in Health-Assistive Smart Environments at Washington State University. Her research interests include wearable computing, machine learning, technology applications for healthcare, and computer science education.

Today I attended the IOT and Emerging Tech session at the Grace Hopper Conference 2015. Gina Sprint spoke on wearable sensors for clinical outcome predictions. This is an extremely interesting topic. I also do research on mHealth so I am happy that I was able to attend her presentation.

Gina went over 3 aspects of wearable rehabilitation.

  • Why technology for rehabilitation:She explains there is objective data that can be used.
  • Why wear able sensors? : They are portable  and inexpensive
  • Why ecological environments : They are more representative of abilities and resembles discharge environments.

Her study is still on going. Most her participants are older.

I was most interested in how she computes her data. She explained that she collects measurements from the body . She spoke on time stamp alignment, orientation correction, band pass filtering- to prevent noise and clinical assessments of process.

 

Linear SVM,linear regression, random forest w/100 trees are some of the models she currently uses in her research.

Project Models

1)Patient is admitted – they have access to data. (M1)

2)Patient is recruited.(M2)

3)Combining data from session one and two. Sensor data and metrics improves the accuracy. (M3)

Model approaches

  • Cumulative model construction
  • Separate model construction

She states that their is obvious room for improvement of the accuracy of the models.

Gina expresses that her tool can be used in Industry. 7/7 people interviewed showed support for the project expressing that they would use it. She would like to create a mobile app for her system and advance the its technology. I think that Gina has a great project on her hands. Best of luck to Gina and her future  plans with this project. 🙂

If you would like to know more about her project contact her on  Linkedin .

 

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Grace Hopper Conference

blogpostI will be blogging, vlogging and note taking throughout the conference. I’ll keep you guys posted on the sessions I intend to cover. I’m soo excited!

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Calling all women techies (students and professionals) from Bangalore!

tech-for-goodAs a committee member of Grace Hopper for India I feel it is my duty to inform you all about the great opportunity to join Tech for Good 2015, the exclusive women-only Hackathon for students and industry professionals from computing and technology backgrounds in Bangalore.

This is a great opportunity to work and code with other technology oriented women on ideas and projects that will have a social impact. This is your chance to help change the world with your great ideas!

The Hackathon will be held as a contest over two rounds. The first round will be conducted in five different cities (Bangalore, Hyderabad, Madurai, New Delhi and Pune). The top finalists selected from the first round will present their applications at the grand finale to be held at the largest technical conference for women in India – the Grace Hopper Celebration of Women in Computing India (GHCI) 2015 in Bangalore during 2-4 December, 2015. The winning teams will be chosen by a panel of judges at GHCI 2015.

For more details and to register click here.

City Hackathon date
(first round)
Registrations open Registrations close
Hyderabad 1 August, 2015 6 July, 2015 28 July, 2015
Pune 8 August, 2015 8 July, 2015 4 August, 2015
Madurai 16 August, 2015 16 July, 2015 8 August, 2015
New Delhi 22 August, 2015 22 July, 2015 14 August, 2015
Bangalore 29 August, 2015 29 July, 2015 21 August, 2015

We look forward to your participation.

Don’t forget to share this opportunity among your networks and friends.

Thank you.

To enter the contest, select a city of your choice (for the first round) and apply.

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Conversation killer

I found this post interesting. Why does telling people about computer science cause a huge awkward silence or a quick jump to the next topic?

Technology education and me

One of the stereotypes of people working computing is that they aren’t great at socializing, and I have to say when I was young that was very true for me. As a shy child I had difficulty striking up conversations with strangers or even responding when people would try to talk to me, which is partially why I admired my mother so much. She could talk to anyone and everyone and seemed to be constantly engaging people in conversation. Happily, as I’ve grown older I’ve become more like my mother when it comes to socializing. It’s now comfortable and easy for me to engage strangers in conversation, and it’s a rare day when I don’t talk to someone when I’m out and about in the city.

I find, however, that some of the typical subjects of conversation don’t work well. For example, it’s very common for someone (a store clerk…

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