What are the frontiers of computer science research?

Answer by Ian Cosgrove:

AI:
Convolutional Neural Networks. Instead of training a neural network to recognise what an object is, CNN uses multiple neural networks. Each one trained to recognise individual features that add up to one overall identification.
Pointy ears+whiskers+sits on keyboard while you're working = Cat
CNNs are what enable Google Now and recent improvements in speech and character recognition

Cognitive Systems, like IBMs Watson. Provides some of the features you would traditionally look at expert systems for but rules don't need to be hard coded. Cognitive systems excel at big data and pattern recognition to provide analysis decision support systems, Watson assists in diagnosis and selection of cancer treatment.

Big Data:

Blended Datasets, combination of multiple indirectly related datasets. Looking at an upcoming predicted heatwave and realtime power usage you can predict how all of those air conditioners kicking on will affect the grid. Blend in travel data like booked airplane tickets coming in (coastal region) or going out (cities) and you have a better idea again.

Platforms, Hadoop and NoSql DBs are changing things and there's still a far way to go. Install Ubuntu server 13 and MongoDB now.

Security, how do you keep all that sensitive real world, real people safe and secure. Then how do you monetize it?

Internet of Things:

Sensors, IoT is not just an internet enabled refridgerator. Realworld sensors will allow autonomic systems to be aware of what is happening in the real world in real time, understand it and take action in real time. From Nest thermostats to smart meters to the whole SmartGrid the IoT can enable massive power/money/carbon savings.

Jobs for makers, the IT industry has been moving away from embedded and low level/hardware developers for years leaving that area up to hobbyists, hackerspaces and the maker community. That expertise is needed more than ever so find your local hackerspace and see when they are holding their next open day/workshops and see what this sensor/arduino/raspberry pi business is all about.

Human Sensors, anyone with a smart phone can be considered a node in the IoT, people contribute real world data as it happens about weather and traffic events, traffic routes etc and social contribution apps will only get bigger thanks to successes like Waze

Cloud and Web Services:
What? Aren't they the buzzwords of 2-14 years ago? Yes but what do you think enables all of these IoT, BD, AI things to communicate. Services will continue to become more modular and composable until AI can identify your needs and weave a custom solution out of the cloud. When things go wrong you're going to need an increasingly self diagnosing/healing interweb and that's going to need some new types of magic.

Languages:
Object Oriented languages were a great step up, the problem is that they're too good. They don't speak concurrently and they lack the correct verbage for building big big systems of the future but they allow us to build things that work so we put up with them to solve problems they were never intended for. I'm thinking something based on Set theory..

Wearables and blended reality:
Yea confidence in the market took a knock after the Nike Fuelband situation but how many times did tablets fail before the iPad launched?
I'm not a huge fan of augmented reality but come on, Word Lens did it right. Just a pity Glass didn't go far enough.  Then on the other end of the spectrum you have Oculus Rift.

Add in some big data from the IoT categorized by CNNs and analyzed by cognitive system and you have just elevated the capabilities of the human mind.

So aspects of all of these things exist on the fringes, you may have heard of some or all of them already but they are still cutting into new frontiers and exposing new challenges. It's where these trends will be combining that real fringe opportunities are emerging.

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Research Papers: Where to find them?

For any researcher, scientist, and student a research paper is a piece of information needed for some research of their own or for study of newest technology, their flaws and corrections. They also provide information on history of concerned topic, or the course they followed before being in current form. Here I provide some really nice sites to fetch such great knowledge:

1. Microsoft Academic Search

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Microsoft Academic Search is a free public search engine for academic papers and literature, developed by Microsoft Research for the purpose of algorithms research in object-level vertical search, data mining, entity linking, and data visualization. Although largely functional, the service is not intended to be a production web site and may be taken offline in the future when the research goals of the project have been met.

2. CiteSeerX

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CiteSeer was a public search engine and digital library for scientific and academic papers, primarily in the fields of computer and information science that has been replaced by CiteSeerX. Many consider it to be the first academic paper search engine. It became public in 1998 and had many new features unavailable in academic search engines at that time.

3. arXiv

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The arXiv (pronounced “archive”) is repository of electronic preprints of scientific papers in the fields of mathematics, physics, astronomy, computer science, quantitative biology, statistics, and quantitative finance, which can be accessed online. In many fields of mathematics and physics, almost all scientific papers are self-archived on the arXiv. Begun on August 14, 1991, arXiv.org passed the half-million article milestone on October 3, 2008.By 2012 the submission rate has grown to more than 7000 per month.

4. Google Scholar

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Google Scholar is a freely accessible web search engine that indexes the full text of scholarly literature across an array of publishing formats and disciplines. Released in beta in November 2004, the Google Scholar index includes most peer-reviewed online journals of Europe and America’s largest scholarly publishers, plus scholarly books and other non-peer reviewed journals.

5. Journal Ranking

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Journal ranking is widely used in academic circles in the evaluation of an academic journal’s impact and quality. Journal rankings are intended to reflect the place of a journal within its field, the relative difficulty of being published in that journal, and the prestige associated with it.

6. ResearchGate

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ResearchGate is a social networking site for scientists and researchers to share papers, ask and answer questions, and find collaborators. Members are encouraged to share raw data and failed experiment results as well as successes, in order to avoid repeating their peers’ scientific research mistakes. Microsoft co-founder Bill Gates is among the company’s investors. ResearchGate announced in 2013 that the site had two million members.

Well, I would also mention Academia.edu which is a tough competitor of ResearchGate.

With so many sites to play with, I hope we will never be devoid of updated information and research papers. If you liked it, plz share and make others aware too…