Research Paper On Latest Computer Technology
The Allen School is committed to expanding our global leadership and impact in computer science and computer engineering research. We offer a supportive environment in which our faculty and students are empowered to pursue the next great advances—whether at the core of the field, or in emerging areas that address humankind’s greatest challenges through the transformative power of computing. Our faculty members have been nationally and internationally recognized for excellence, and our students are successful in the preeminent research competitions sponsored by industry and government. In the past five years alone, more than 40 students have received Graduate Research Fellowships or Honorable Mentions from the National Science Foundation, and over a dozen have earned accolades as part of the Computing Research Association's Outstanding Undergraduate Researcher Awards competition.
Allen School faculty and students are among the most prolific contributors of award papers to major conferences in our field. Our graduate program alumni go on to be leaders in industry and academia, and our undergraduates — most of whom participate in faculty-supervised research — power industry-leading companies and populate the nation’s most prestigious graduate programs.
Areas of Expertise
Conference Award Papers
In the News
- The Phone Charger of the Future Will Go Pew Pew, Wired, 2/23/18 More stories
- DNA Data Storage Gets Random Access, IEEE Spectrum, 2/20/18 More stories
- How DNA could store all the world's data in a semi-trailer, Financial Times, 2/4/18
- DARPA Wants to Build an Image Search Engine Out of DNA, Wired, 1/24/18
- UW researchers "MERGE" machine learning and medicine to enable targeted treatment of cancer, Allen School News, 1/5/18
- UW students teach Alexa to have a little chat with us, Seattle Times, 11/28/17
- Siddhartha Srinivasa and Tao Xie named Fellows of the IEEE, Allen School News, 11/22/17
- University of Washington's computer science clout on full display at annual student showcase, GeekWire, 11/16/17
- Robotics expert moves entire team to University of Washington, including famous Oreo-cracking robot, GeekWire, 11/16/17
- Your Next Password May Be Stored in Your Shirt Cuff, MIT Technology Review, 10/31/17 More stories
- Who Is Thinking About Security and Privacy for Augmented Reality?, MIT Technology Review, 10/19/17
- Professor Jennifer Mankoff Recognized with GVU Impact Award, Allen School News, 10/18/17
- It Takes Just $1,000 to Track Someone's Location with Mobile Ads, Wired, 10/18/17 More stories
- Smartphones Are Changing Medical Care in Some Surprising Ways, NBC MACH, 10/13/17
- How the 'Internet of Things' Will Change Everything, NBC MACH, 10/6/17
- Allen School and AWS team up on new NNVM compiler for deep learning frameworks, Allen School News, 10/6/17
- In 1,000 Years, This Recording Of Miles David Preserved In DNA Will Still Be Perfect, Fast Company, 10/5/17
- Nvidia to open robotics lab near University of Washington, expanding Seattle-area footprint, GeekWire, 10/5/17
- A clever way to transmit data on the cheap, The Economist, 9/13/17 More stories
- Jeffrey Heer wins IEEE Visualization Technical Achievement Award, Allen School News, 9/12/17
- Securing the Fourth Estate: What the Panama Papers and Confidante reveal about journalists' needs and practices, Allen School News, 9/11/17
- UW's Sounding Board names a finalist for $2.5 million Amazon Alexa Prize, Allen School News, 9/1/17
- Allen School's open-source TVM framework bridges the gap between deep learning and hardware innovation, Allen School News, 8/17/17
- 35 Innovators Under 35: Franziska Roesner, University of Washington, MIT Technology Review, 8/16/17
- Malware Stored in Synthetic DNA Can Take Over a PC, Researchers Find, The Wall Street Journal, 8/10/17 More stories
- Biohackers Encoded Malware in a Strand of DNA, Wired, 8/10/17
- Storing Data in DNA Brings Nature into the Digital Universe, Scientific American, 7/29/17
- Domino effect: UW and Microsoft researchers use spatial organization to build DNA computers, Allen School News, 7/26/17
- The Technology That Will Make It Impossible for You to Believe What You See, The Atlantic, 7/11/17 More stories
- This cell phone can make calls even without a battery, Wired, 6/28/17
- Allen School set to amplify UW's leadership in human-computer interaction with new hires Jennifer Mankoff and Jon Froehlich, Allen School News, 6/28/17
- Researchers use ridesharing cars to sniff out a secret spying tool, Wired, 6/2/17 More stories
- Allen School's Jeffrey Heer wins ACM Grace Murray Hopper Award, Allen School News, 5/3/17
- Video Games Help Model Brain's Neurons, New York Times, 4/24/17
- Six Allen School faculty members win NSF CAREER Awards, Allen School News, 4/18/17
- Allen School's Tom Anderson elected to the American Academy of Arts & Sciences, Allen School News, 4/13/17
- Apple's Turi acquisition funds new $1M UW professorship in AI and machine learning, GeekWire, 2/23/17
- Learning to love our robot co-workers, New York Times Magazine, 2/23/17
- UW 'genius' Shwetak Patel works on health monitoring apps for Senosis startup, GeekWire, 2/17/17
- AccessMap finds routes that avoid common pitfalls for those with limited mobility, TechCrunch, 2/1/17
- Jeeva Wireless, founded by UW researchers, raises $1.2M to develop 'breakthrough' passive Wi-Fi system, GeekWire, 1/30/17
- Senior faculty hires Sidd Srinivasa and Michael Taylor set to advance UW's leadership in robotics and computer engineering research, CSE News, 1/17/17
- Geek of the Week: UW Ph.D. student Irene Zhang has big ideas to make life easier for programmers, GeekWire, 12/16/16
- Shwetak Patel named a Fellow of the Association for Computing Machinery, CSE News, 12/8/16
- Direct brain stimulation lets gamers play blind, New Atlas, 12/6/16
- Is DNA the Future of Data Storage?, Wall Street Journal, 10/25/16
- This Contact Lens Will Kick-Start the Internet of Disposable Things, MIT Technology Review, 10/19/16
- Can Passwords Be Sent Through the Human Body?, Wall Street Journal, 10/7/16
- From digital to biological: Why the future of storage is all about DNA, ZDNet, 9/23/16
- 10 Scientists to Watch: Shayan Oveis Gharan finds the shortest route to success, Science News, 9/21/16
- A Lesson of Tesla Crashes? Computer Vision Can't Do It All Yet, The New York Times, 9/19/16
- Have stencil, will lift, ASCR Discovery, September 2016
- How DNA could store all the world's data, Nature, 8/31/16
- Devices could recycle radio waves instead of transmitting them with new ‘interscatter’ technique, TechCrunch, 8/17/16 More stories
- They really are watching you: web tracking surges with online ads, USA Today, 8/16/16 More stories
- Shyam Gollakota in the Brilliant 10: The Man Who Powers Devices with Wi-Fi, Popular Science, 8/11/16
- The Robot You Want Most Is Far from Reality, MIT Technology Review, 8/10/16
- Apple acquires Turi in major exit for Seattle-based machine learning and AI startup, GeekWire, 8/5/16
- RFID tag maker Impinj prices IPO at $14, shares soar in rare public offering, GeekWire, 7/21/16 More stories
- This amazing search engine automatically face-swaps you into your image results, TechCrunch, 7/21/16 More stories
- Researchers stored an OK Go music video on strands of DNA, Mashable, 7/7/16 More stories
- The Ultimate Facial-Recognition Algorithm, The Atlantic, 6/28/16 More stories
- Students demonstrate their HoloLens apps after a quarter of VR and AR design, TechCrunch, 6/10/16
- Tech Turns to Biology as Data Storage Needs Explode, Scientific American, 5/31/16
- Intelligent water: New $40M Phyn joint venture taps UW tech expertise with Seattle R&D lab, GeekWire, 5/26/16
- In first, 3-D printed objects connect to WiFi without electronics
- UW students win Amazon's inaugural Alexa Prize for most engaging socialbot
- New tool quantifies power imbalance between female and male characters in Hollywood movie scripts
- How to store information in your clothes invisibly, without electronics
- For $1000, anyone can purchase online ads to track your location and app use
- UW team shatters long-range communication barrier for devices that consume almost no power
- PupilScreen aims to allow parents, coaches, medics to detect concussion, brain injuries with a smartphone
- New app could use smartphone selfies to screen for pancreatic cancer
- Computer scientists use music to covertly track body movements, activity
- DNA sequencing tool lack robust protections against cybersecurity risks
- Lip-syncing Obama: New tools turn audio clips into realistic video
- First battery-free cellphone makes calls by harvesting ambient power
- Catching the IMSI-catchers: SeaGlass brings transparency to cell phone surveillance
- Kids, parents alike worried about privacy with internet-connected toys
- Period tracking apps failing users in basic ways, study finds
- Food photos help Instagram users with healthy eating
- Scientific discovery game significantly speeds up neuroscience research process
- Two UW faculty named to American Academy of Arts and Sciences
- $50M endowment establishes the Paul G. Allen School of Computer Science & Engineering at the University of Washington
- Singing posters and talking shirts: UW engineers turn everyday objects into FM radio stations
- UW CSE announces the Guestrin Endowed Professorship in Artificial Intelligence and Machine Learning
- Three UW scientists awarded Sloan Fellowships for early-career research
- New route-finding map lets Seattle pedestrians avoid hills, construction, accessibility barriers
- Two UW professors win Presidential Early Career Awards for Scientists and Engineers
- No peeking: Humans play computer game using only direct brain stimulation
- What makes Bach sound like Bach? New dataset teaches algorithms classical music
- Secure passwords can be sent through your body, instead of air
- HemaApp screens for anemia, blood conditions without needle sticks
- Interscatter communication enables first-ever implanted devices, smart contact lenses, credit cards that ‘talk’ Wi-Fi
- Unearthing trackers of the past: UW computer scientists reveal the history of third-party web tracking
- Imaging software predicts how you look with different hair styles, colors, appearances
- UW, Microsoft researchers break record for DNA data storage
- How well do facial recognition algorithms cope with a million strangers?
- UW-led team awarded $1M bioelectronics innovation prize
- Paper gets ‘smart’ with drawn-on, stenciled sensor tags
- This five-fingered robot hand learns to get a grip on its own
- New health sensing tool measures lung function over a phone call, from anywhere in the world
- UW team stores digital images in DNA — and retrieves them perfectly
- Smartwatches can now track your finger in mid-air using sonar
- UW engineers achieve Wi-Fi at 10,000 times lower power
- Three UW professors win Presidential Early Career Award for Scientists and Engineers
- UW computer scientists to make financial products better and more available for the poor
Since we recently announced our $10001 Binary Battle to promote applications built on the Mendeley API (now including PLoS as well), I decided to take a look at the data to see what people have to work with. My analysis focused on our second largest discipline, Computer Science. Biological Sciences (my discipline) is the largest, but I started with this one so that I could look at the data with fresh eyes, and also because it’s got some really cool papers to talk about. Here’s what I found:
What I found was a fascinating list of topics, with many of the expected fundamental papers like Shannon’s Theory of Information and the Google paper, a strong showing from Mapreduce and machine learning, but also some interesting hints that augmented reality may be becoming more of an actual reality soon.
The top graph summarizes the overall results of the analysis. This graph shows the Top 10 papers among those who have listed computer science as their discipline and chosen a subdiscipline. The bars are colored according to subdiscipline and the number of readers is shown on the x-axis. The bar graphs for each paper show the distribution of readership levels among subdisciplines. 17 of the 21 CS subdisciplines are represented and the axis scales and color schemes remain constant throughout. Click on any graph to explore it in more detail or to grab the raw data.(NB: A minority of Computer Scientists have listed a subdiscipline. I would encourage everyone to do so.)
1. Latent Dirichlet Allocation (available full-text)
LDA is a means of classifying objects, such as documents, based on their underlying topics. I was surprised to see this paper as number one instead of Shannon’s information theory paper (#7) or the paper describing the concept that became Google (#3). It turns out that interest in this paper is very strong among those who list artificial intelligence as their subdiscipline. In fact, AI researchers contributed the majority of readership to 6 out of the top 10 papers. Presumably, those interested in popular topics such as machine learning list themselves under AI, which explains the strength of this subdiscipline, whereas papers like the Mapreduce one or the Google paper appeal to a broad range of subdisciplines, giving those papers a smaller numbers spread across more subdisciplines. Professor Blei is also a bit of a superstar, so that didn’t hurt. (the irony of a manually-categorized list with an LDA paper at the top has not escaped us)
2. MapReduce : Simplified Data Processing on Large Clusters (available full-text)
It’s no surprise to see this in the Top 10 either, given the huge appeal of this parallelization technique for breaking down huge computations into easily executable and recombinable chunks. The importance of the monolithic “Big Iron” supercomputer has been on the wane for decades. The interesting thing about this paper is that had some of the lowest readership scores of the top papers within a subdiscipline, but folks from across the entire spectrum of computer science are reading it. This is perhaps expected for such a general purpose technique, but given the above it’s strange that there are no AI readers of this paper at all.
3. The Anatomy of a large-scale hypertextual search engine (available full-text)
In this paper, Google founders Sergey Brin and Larry Page discuss how Google was created and how it initially worked. This is another paper that has high readership across a broad swath of disciplines, including AI, but wasn’t dominated by any one discipline. I would expect that the largest share of readers have it in their library mostly out of curiosity rather than direct relevance to their research. It’s a fascinating piece of history related to something that has now become part of our every day lives.
4. Distinctive Image Features from Scale-Invariant Keypoints
This paper was new to me, although I’m sure it’s not new to many of you. This paper describes how to identify objects in a video stream without regard to how near or far away they are or how they’re oriented with respect to the camera. AI again drove the popularity of this paper in large part and to understand why, think “Augmented Reality“. AR is the futuristic idea most familiar to the average sci-fi enthusiast as Terminator-vision. Given the strong interest in the topic, AR could be closer than we think, but we’ll probably use it to layer Groupon deals over shops we pass by instead of building unstoppable fighting machines.
5. Reinforcement Learning: An Introduction (available full-text)
This is another machine learning paper and its presence in the top 10 is primarily due to AI, with a small contribution from folks listing neural networks as their discipline, most likely due to the paper being published in IEEE Transactions on Neural Networks. Reinforcement learning is essentially a technique that borrows from biology, where the behavior of an intelligent agent is is controlled by the amount of positive stimuli, or reinforcement, it receives in an environment where there are many different interacting positive and negative stimuli. This is how we’ll teach the robots behaviors in a human fashion, before they rise up and destroy us.
6. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions (available full-text)
Popular among AI and information retrieval researchers, this paper discusses recommendation algorithms and classifies them into collaborative, content-based, or hybrid. While I wouldn’t call this paper a groundbreaking event of the caliber of the Shannon paper above, I can certainly understand why it makes such a strong showing here. If you’re using Mendeley, you’re using both collaborative and content-based discovery methods!
7. A Mathematical Theory of Communication (available full-text)
Now we’re back to more fundamental papers. I would really have expected this to be at least number 3 or 4, but the strong showing by the AI discipline for the machine learning papers in spots 1, 4, and 5 pushed it down. This paper discusses the theory of sending communications down a noisy channel and demonstrates a few key engineering parameters, such as entropy, which is the range of states of a given communication. It’s one of the more fundamental papers of computer science, founding the field of information theory and enabling the development of the very tubes through which you received this web page you’re reading now. It’s also the first place the word “bit”, short for binary digit, is found in the published literature.
8. The Semantic Web (available full-text)
In The Semantic Web, Tim Berners-Lee, Sir Tim, the inventor of the World Wide Web, describes his vision for the web of the future. Now, 10 years later, it’s fascinating to look back though it and see on which points the web has delivered on its promise and how far away we still remain in so many others. This is different from the other papers above in that it’s a descriptive piece, not primary research as above, but still deserves it’s place in the list and readership will only grow as we get ever closer to his vision.
9. Convex Optimization (available full-text)
This is a very popular book on a widely used optimization technique in signal processing. Convex optimization tries to find the provably optimal solution to an optimization problem, as opposed to a nearby maximum or minimum. While this seems like a highly specialized niche area, it’s of importance to machine learning and AI researchers, so it was able to pull in a nice readership on Mendeley. Professor Boyd has a very popular set of video classes at Stanford on the subject, which probably gave this a little boost, as well. The point here is that print publications aren’t the only way of communicating your ideas. Videos of techniques at SciVee or JoVE or recorded lectures (previously) can really help spread awareness of your research.
10. Object recognition from local scale-invariant features (available in full-text)
This is another paper on the same topic as paper #4, and it’s by the same author. Looking across subdisciplines as we did here, it’s not surprising to see two related papers, of interest to the main driving discipline, appear twice. Adding the readers from this paper to the #4 paper would be enough to put it in the #2 spot, just below the LDA paper.
So what’s the moral of the story? Well, there are a few things to note. First of all, it shows that Mendeley readership data is good enough to reveal both papers of long-standing importance as well as interesting upcoming trends. Fun stuff can be done with this! How about a Mendeley leaderboard? You could grab the number of readers for each paper published by members of your group, and have some friendly competition to see who can get the most readers, month-over-month. Comparing yourself against others in terms of readers per paper could put a big smile on your face, or it could be a gentle nudge to get out to more conferences or maybe record a video of your technique for JoVE or Khan Academy or just Youtube.
Another thing to note is that these results don’t necessarily mean that AI researchers are the most influential researchers or the most numerous, just the best at being accounted for. To make sure you’re counted properly, be sure you list your subdiscipline on your profile, or if you can’t find your exact one, pick the closest one, like the machine learning folks did with the AI subdiscipline. We recognize that almost everyone does interdisciplinary work these days. We’re working on a more flexible discipline assignment system, but for now, just pick your favorite one.
These stats were derived from the entire readership history, so they do reflect a founder effect to some degree. Limiting the analysis to the past 3 months would probably reveal different trends and comparing month-to-month changes could reveal rising stars.
To do this analysis I queried the Mendeley database, analyzed the data using R, and prepared the figures with Tableau Public. A similar analysis can be done dynamically using the Mendeley API. The API returns JSON, which can be imported into R using the fineRJSONIO package from Duncan Temple Lang and Carl Boettiger is implementing the Mendeley API in R. You could also interface with the Google Visualization API to make motion charts showing a dynamic representation of this multi-dimensional data. There’s all kinds of stuff you could do, so go have some fun with it. I know I did.