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CSE Research News

Taking on the limits of computing power

Founded by Prof. Scott Mahlke and his former students Mehrzad Samadi (PhD CSE 2014) and Ankit Sethia (MSE PhD CSE 2011, 2015), Ann Arbor-based Parabricks Inc. employs proprietary high-performance computing techniques to dramatically accelerate whole genome sequencing, shortening tasks that took multiple days to a single hour while generating fully equivalent output. [Full Story]

Related Topics:  Alumni  Computer Architecture  Entrepreneurship and Tech Transfer  Health and Safety  Lab-Computer Engineering (CE Lab)  Mahlke, Scott  

Helping drivers use smart cars smarter

Profs. Jason Mars, Lingja Tang, CSE students Shih-Chieh Lin, Chang-Hong Hsu, and Yunqi Zhang, and Ford Motor Company have developed a conversational in-vehicle digital assistant that can respond to drivers questions and commands in natural language, helping them get to know the autonomous tools their cars have to offer. Their paper earned Honorable Mention Award in the Best Paper competition at this years ACM User Interface Software and Technology Symposium (UIST). [Full Story]

Related Topics:  Automotive industry  Autonomous Vehicles  Graduate Students  Lab-Artificial Intelligence  Mars, Jason  Tang, Lingjia  

Using drones, a new software tool can bring LTE networks anywhere

Prof. Z. Morley Mao and alumnus Mehrdad Moradi (PhD CSE 2018) earned a best paper award at this year's ACM MobiCom for their work on SkyCore, a reliable new way to deploy LTE networks using unmanned aerial vehicles (UAVs). The paper, SkyCore: Moving Core to the Edge for Untethered and Reliable UAV-based LTE networks, demonstrated a way to connect hotspots on drones with commercial networks and smartphones. [Full Story]

Related Topics:  Autonomous Vehicles  Lab-Systems  Mao, Zhuoqing Morley  Mobile Computing  

403 Forbidden Study reveals new data on region-specific website blocking practices

New work led by Prof. Roya Ensafi and PhD student Allison McDonald undertook the first wide-scale measurement study of server-side geographic restrictions, or geoblocking, a phenomenon in which websites block access for users in particular countries or regions, a phenomenon on the rise causing Internet balkanization. [Full Story]

Related Topics:  Ensafi, Roya  Graduate Students  Information Technology  Lab-Systems  

Two papers announced among 10 most influential in healthcare and infection control

Prof. Jenna Wiens group had two papers highlighted in a session on the top 10 most influential papers in healthcare epidemiology and infection control at Infectious Disease Week (IDWeek 2018). The papers were selected for their impact, the number of times they were cited in the preceding two years, and their potential effect on future research and technology. [Full Story]

Related Topics:  Health and Safety  Lab-Artificial Intelligence  Machine Learning  Wiens, Jenna  

The logic of feeling: Teaching computers to identify emotions

Using machine learning to decode the unpredictable world of human emotion might seem like an unusual choice. But in the ambiguity of human expression, U-M computer science and engineering associate professor Emily Mower Provost has discovered a rich trove of data waiting to be analyzed. [Full Story]

Related Topics:  Artificial Intelligence  Health and Safety  Lab-Artificial Intelligence  Machine Learning  Mower Provost, Emily  

Making software failures a little less catastrophic

Prof. Baris Kasikci presented a new technique called REPT REverse debugging with Processor Trace. In the paper REPT: Reverse Debugging of Failures in Deployed Software, Kasikci and collaborators propose a method to recreate the failing program execution to better diagnose the problem at hand. This technique is now deployed on Windows systems and the Windows Debugger platform. [Full Story]

Related Topics:  Kasikci, Baris  Lab-Systems  Software Systems  

Gaining a deeper understanding of how personal values are expressed in text

Content analysis of large collections of text is often a useful first step in understanding what people are talking or writing about. PhD student Steve Wilson, Prof. Rada Mihalcea, and Master student Yiting Shen have proposed a new method of performing these analyses in their paper, Building and Validating Hierarchical Lexicons with a Case Study on Personal Values. The researchers earned a Best Paper Award at the 2018 International Conference on Social Informatics (SocInfo) for their work. [Full Story]

Related Topics:  Graduate Students  Lab-Artificial Intelligence  Language and Text Processing  Mihalcea, Rada  Women in Computing  

Tyche: A new permission model to defend against smart home hacks

Prof. Atul Prakash, CSE PhD student Kevin Eykholt, and CSE alumni Amir Rahmati and Earlence Fernandes have proposed Tyche, a safer app permissions system for smart homes and the Internet of Things. Their paper on this project, Tyche: A Risk-Based Permission Model for Smart Homes, received a Best Paper Award at the IEEE Cybersecurity Development Conference. [Full Story]

Related Topics:  Alumni  Cybersecurity  Graduate Students  Internet of Things  Lab-Systems  Prakash, Atul  

Detecting Huntington's disease with an algorithm that analyzes speech

In an advance that could one day provide new insight into the progression of neurological diseases like Huntington's disease, Alzheimers and Parkinson's, researchers including Prof. Emily Mower Provost have demonstrated the first automated system that uses speech analysis to detect Huntington's disease. [Full Story]

Related Topics:  Big Data  Health and Safety  Lab-Artificial Intelligence  Machine Learning  Mower Provost, Emily  

Fake news detector algorithm works better than a human

An algorithm-based system that identifies telltale linguistic cues in fake news stories could provide news aggregator and social media sites like Google News with a new weapon in the fight against misinformation. Led by Prof. Rada Mihalcea, the researchers have demonstrated that its comparable to and sometimes better than humans at correctly identifying fake news stories. [Full Story]

Related Topics:  Artificial Intelligence  Big Data  Communications  Lab-Artificial Intelligence  Mihalcea, Rada  

Making online communication smarter with Trove Video

Trove is an Ann-Arbor based artificial intelligence startup built on the vision of improving communication using artificial intelligence. Profs. Danai Koutra and Walter Lasecki are collaborating with the company to develop novel methods and tools that will help make intelligent online communication smarter. [Full Story]

Related Topics:  Big Data  Communications  Koutra, Danai  Lab-Artificial Intelligence  Lasecki, Walter  

Intel processor vulnerability could put millions of PCs at risk

A newly discovered processor vulnerability could potentially put secure information at risk in any Intel-based PC manufactured since 2008. It could affect users who rely on a digital lockbox feature known as Intel Software Guard Extensions, or SGX, as well as those who utilize common cloud-based services. CSE researchers contributed to the discovery of the security hole, called Foreshadow. [Full Story]

Related Topics:  Cybersecurity  Genkin, Daniel  Graduate Students  Kasikci, Baris  Lab-Systems  Wenisch, Thomas  

Using software to beat Moore's Law: $9.5M to design the reconfigurable computer

In search of a new way to overcome the limitations of silicon, Prof. Ron Dreslinski is leading a project with a $9.5million DARPA grant to develop a hardware architecture and software ecosystem that together can approach the power of ASICs with the flexibility of a CPU. Called Transmuter, this software-defined hardware can change how programs use the hardware available to them in real time, effectively acting as a reconfigurable computer. [Full Story]

Related Topics:  Computer Architecture  Dreslinski, Ron  Integrated Circuits and VLSI  

Enabling anyone to design hardware with a new open-source tool

In a $6.5 million U-M-led project that could revolutionize and democratize designing hardware devices, Professors Wentzloff, Blaauw, Dreslinski, and Sylvester will work to create an open-source hardware compiler that aims to reduce the six month process of hand-designing analog circuits to a dramatically faster and automated 24-hour routine. [Full Story]

Related Topics:  Blaauw, David  Computer-Aided Design & VLSI  Dreslinski, Ron  Integrated Circuits and VLSI  Lab-Michigan Integrated Circuits (MICL)  Sylvester, Dennis  Wentzloff, David  

Michigan chips will be first to test next-generation hardware design tools

Professors Sylvester, Blaauw, and Dreslinski will test tools and provide feedback in a national program that aims to build free, open-source electronic design automation tools. [Full Story]

Related Topics:  Blaauw, David  Computer-Aided Design & VLSI  Dreslinski, Ron  Integrated Circuits and VLSI  Lab-Michigan Integrated Circuits (MICL)  Sylvester, Dennis  

Tool for structuring data creates efficiency for data scientists

Transforming messy data into a usable state turns out to be labor-intensive and tedious. Traditionally, domain experts handwrite task-specific scripts to transform unstructured data. Enter Foofah, a project developed by CSE graduate students Zhongjun Jin and Michael Anderson, Prof. Michael Cafarella, and Bernard A. Galler Collegiate Professor of Electrical Engineering and Computer Science H.V. Jagadish that can help to minimize the effort and required background knowledge needed to clean up data. [Full Story]

Related Topics:  Big Data  Cafarella, Michael  Data and Computing  Graduate Students  Jagadish, HV  

Undocumented immigrants' privacy at risk online, on phones

Every day, undocumented immigrants in the U.S. face discrimination, surveillance, deportation, and other dangers. When it comes to their smartphones, immigrants struggle to apply instinctive caution, according to a study by a team of University of Michigan researchers that included CSE PhD student Allison McDonald. [Full Story]

Related Topics:  Cybersecurity  Graduate Students  Halderman, J. Alex  

Cafarella Receives VLDB Test of Time Award for Structured Web Data Search

This award is given to the VLDB paper published ten years earlier that has had the most influence since its publication. In this paper, Cafarella and co-authors Alon Halevy, Zhe Daisy Wang, Eugene Wu, and Yang Zhang set out to determine how to provide search-engine-style access to huge volumes of structured web data. [Full Story]

Related Topics:  Big Data  Cafarella, Michael  Data and Computing  

Designing a flexible future for massive data centers

The days of bulky, expensive servers filling up data centers may be numbered: a new approach recreates the power of a large server by linking up and pooling the resources of smaller computers with fast networking technology. [Full Story]

Related Topics:  Big Data  Chowdhury, Mosharaf  Lab-Systems  Mozafari, Barzan  Networking, Operating Systems, and Distributed Systems  

Study maps careers of CS PhDs using decades of data

Of the many burning questions in the world of computing research, the one most dear to a student's heart has typically been the least investigated: what happens after a PhD in computer science? Prof. Danai Koutra and CSE PhD student Tara Safavi set out to provide the world's first data-driven answer, analyzing several decades of post-PhD computing careers using a large new dataset rich with professional information. [Full Story]

Related Topics:  Big Data  Data and Computing  Koutra, Danai  

"Stitching" together a web user from scattered, messy data

Modern internet users submit a massive trove of personal details to the web - but they scatter their data across dozens of websites, accounts, and devices with very little continuity. Prof. Danai Koutra will work to "stitch" these personal details together into a cohesive, useful whole, making a user's time online a more pleasant, continuous experience across devices with better product and service recommendations. [Full Story]

Related Topics:  Big Data  Data and Computing  Koutra, Danai  

Building a security standard for a post-quantum future

Chris Peikert, with a team of eleven other researchers, has submitted a cryptographic scheme as a proposed standard to the NIST Post-Quantum Cryptography project. Called FrodoKEM, this family of encryption algorithms is designed to be a conservative and practical implementation of one of the most-studied approaches in the post-quantum cryptography field. [Full Story]

Related Topics:  Cybersecurity  Peikert, Chris  Quantum Science and Technology  

$6.25M project will decode worlds most complex networks

A new $6.25 million project built on game theory and led by Professors Mingyan Liu and Michael Wellman will develop tools to understand and shape online and on-the-ground networks that drive human decision making. [Full Story]

Related Topics:  Liu, Mingyan  Networking, Operating Systems, and Distributed Systems  Wellman, Michael  

CSE researchers win Best of SELSE award

have won the the best paper award at the 14th Workshop on Silicon Errors in Logic - System Effects (SELSE) for their paper entitled "Low Cost Transient Fault Protection Using Loop Output Prediction." [Full Story]

Related Topics:  Alumni  Computer Architecture  Graduate Students  Lab-Computer Engineering (CE Lab)  Mahlke, Scott  

Preventing deadly hospital infections with machine learning

New machine learning models tailored to individual hospitals could give them a much earlier prediction of which patients are most likely to develop C. difficile, potentially helping them stave off infection before it starts. The models are detailed in a paper published today in Infection Control and Hospital Epidemiology. [Full Story]

Related Topics:  Lab-Artificial Intelligence  Wiens, Jenna  

Michigan researchers discover vulnerabilities in next-generation connected vehicle technology

The US Department of Transportation has started implementing I-SIG, a vehicle-to-infrastructure technology that uses real-time vehicle trajectory data to intelligently control the duration and sequence of traffic signals. With the use of this system, comes vulnerabilities, and Michigan researchers have demonstrated that even one single cyberattack can greatly manipulate the intelligent traffic control algorithm in the current I-SIG system and cause severe traffic jams. [Full Story]

Related Topics:  Lab-Systems  Mao, Zhuoqing Morley  

Cuba "sonic attacks" - a covert accident?

The purported "sonic attacks" that sickened U.S. and Canadian government workers in Cuba last year could have been an accidental side effect of attempted eavesdropping, says Prof. Kevin Fu, who with his colleagues reverse-engineered the attacks in a lab. [Full Story]

Related Topics:  Cybersecurity  Embedded Systems  Fu, Kevin  Lab-Computer Engineering (CE Lab)  

New computing system to enable deep space missions

A new radiation-hardened, multi-processor, Arm-based spacecraft processor is being developed at Michigan in a project led by Boeing and funded by NASA. Prof. Ron Dreslinski is leading the research at Michigan. [Full Story]

Related Topics:  Computer Architecture  Dreslinski, Ron  Lab-Computer Engineering (CE Lab)  Mudge, Trevor  

Chat tool simplifies tricky online privacy policies

Kang G. Shin, the Kevin and Nancy O'Connor Professor of Computer Science, and his collaborators have created an automated chatbot that uses artificial intelligence to weed through the fine print of privacy policies so that you will know what you're agreeing to. [Full Story]

Related Topics:  Artificial Intelligence  Lab-Artificial Intelligence  Shin, Kang G.  

Michigan researchers predict emotions by examining the correlation between tweets and environmental factors

Research fellow Carmen Banea, alumna Vicki Liu, and Prof. Rada Mihalcea explored the concept of grounded emotions, focusing on how external factors, ranging from weather, news exposure, social network emotion charge, timing, and mood predisposition may have a bearing on ones emotion level throughout the day. [Full Story]

Related Topics:  Lab-Artificial Intelligence  Language and Text Processing  Mihalcea, Rada  

Internet-scanning U-M startup pioneers new approach to cybersecurity

Ann Arbor-based Censys has launched based on work done over the past 5 years in Prof. J. Alex Halderman's lab. Censys is the first commercially available internet-wide scanning tool. It helps IT experts working to secure large networks, which are composed of a constantly changing array of devices ranging from servers to smartphones and internet-of-things devices. [Full Story]

Related Topics:  Cybersecurity  Halderman, J. Alex  Lab-Systems  

Reimagining how computers are designed: University of Michigan leads new $32M center

The Center for Applications Driving Architectures, or ADA, at the University of Michigan will develop a transformative, "plug-and-play" ecosystem to encourage a flood of fresh ideas in computing frontiers such as autonomous control, robotics and machine-learning. [Full Story]

Related Topics:  Bertacco, Valeria  Computer Architecture  Lab-Computer Engineering (CE Lab)  

U-M startup May Mobility blazes toward autonomous fleet market

May Mobility, co-founded and led by Prof. Edwin Olson, has tested its autonomous vehicles on the streets of Downtown Detroit. The startup recently licensed five autonomous driving related technologies from U-M, and outside of the life sciences, is the most successful UM startup in raising first round of funding so quickly. [Full Story]

Related Topics:  Autonomous Vehicles  Lab-Artificial Intelligence  Olson, Edwin  Robotics and Autonomous Systems  

CSE Researchers Funded to Enhance Online Communication

Profs. Danai Koutra and Walter Lasecki have been awarded two grants from Trove.ai, an Ann-Arbor based artificial intelligence startup, to develop novel methods and tools that will unleash the power of online communication. [Full Story]

Related Topics:  Koutra, Danai  Lab-Artificial Intelligence  Lab-Systems  Lasecki, Walter  

Unhackable Computer Under Development with $3.6M DARPA Grant

By turning computer circuits into unsolvable puzzles, a University of Michigan team aims to create an unhackable computer with a new $3.6 million grant from the Defense Advanced Research Projects Agency. Todd Austin, a professor of computer science and engineering, leads the project, called MORPHEUS. [Full Story]

Related Topics:  Austin, Todd  Computer Architecture  Cybersecurity  Lab-Computer Engineering (CE Lab)  

2017 CSE Graduate Student Honors Competition Highlights Outstanding Research

CSE held its fourteenth annual CSE Graduate Student Honors Competition on November 8. The top presentation competition was "Analyzing and Enhancing the Security of Modern Memory Systems," given by Salessawi Ferede Yitbarek, who represented CSE's Hardware research area. [Full Story]

Related Topics:  Graduate Students  

Prof. Chris Peikert Receives TCC Test of Time Award for Work in Lattice Cryptography

Chris Peikert, the Patrick C. Fischer Development Professor in Theoretical Computer Science, and his co-author Alon Rosen have received the TCC Test of Time Award for their paper on efficient collision-resistant hashing on cyclic lattices. The award is a recognition of a long line of works by Prof. Peikert and others who laid the foundations for practically efficient lattice-based cryptography. [Full Story]

Related Topics:  Cybersecurity  Lab-Theory of Computation  Peikert, Chris  

Michigan Researchers Win Best Paper Award at DFT 2017

John P. Hayes, Claude E. Shannon Professor of Engineering Science, and CSE graduate student Paishun Ting have received the Best Paper Award at the 30th IEEE Symposium on Defect and Fault Tolerance for their work in eliminating a hidden source of error in stochastic circuits. [Full Story]

Related Topics:  Computer Architecture  Computer-Aided Design & VLSI  Graduate Students  Hayes, John  Lab-Computer Engineering (CE Lab)  

Wearables to boost security of voice-based log-in

Voice authentication is easy to spoof. New technology could help close this open channel. [Full Story]

Related Topics:  Cybersecurity  Lab-Systems  Networking, Operating Systems, and Distributed Systems  Shin, Kang G.  

Precision Health at Michigan

Learn more about Michigan's new initiative to lead in precision health: using advanced tools and technology to provide personalized solutions to improve an individual's health and wellness. Lead by co-director Eric Michielssen. [Full Story]

Related Topics:  Applied Electromagnetics and RF Circuits  Big Data  Health and Safety  Michielssen, Eric  Signal & Image Processing and Machine Learning  

Manos Kapritsos and Collaborators Win USENIX Security Paper Award

A team of researchers including Prof. Manos Kapritsos has won a Distinguished Paper Award at the 2017 USENIX Security Symposium for Vale, a new programming language and tool that supports flexible, automated verification of high-performance cryptographic assembly code. [Full Story]

Related Topics:  Cybersecurity  Kapritsos, Manos  Lab-Systems  

Michigan, Georgia Tech Researchers Funded to Deter Financial Market Manipulation

Researchers at the University of Michigan and the Georgia Institute of Technology will develop innovative approaches to detecting and deterring the computerized manipulation of financial markets under a $1M grant from the National Science Foundations's Big Data program. Michael Wellman, the Lynn A. Conway Collegiate Professor of Computer Science and Engineering, is project director and one of five PIs. [Full Story]

Related Topics:  Artificial Intelligence  Big Data  Lab-Artificial Intelligence  Wellman, Michael  

Improving Natural Language Processing with Demographic-Aware Models

Michigan researchers, including Prof. Rada Mihalcea, research fellow Carmen Banea, and graduate student Aparna Garimella have found that word associations vary across different demographics, and researchers can build better natural language processing models if they can account for demographics. [Full Story]

Related Topics:  Lab-Artificial Intelligence  Mihalcea, Rada  

BugMD: Automatic Mismatch Diagnosis for Bug Triaging

Today's incredibly dense microprocessors take more time to verify for correctness than they do to design, and bugs are extremely difficult to track down and correct. CSE researchers have introduced BugMD, an automatic bug triaging solution that collects multiple architectural-level mismatches and employs a classifier to pinpoint buggy design units. [Full Story]

Related Topics:  Bertacco, Valeria  Computer Architecture  Computer-Aided Design & VLSI  Lab-Computer Engineering (CE Lab)  Mahlke, Scott  

'Learning Database' Speeds Queries from Hours to Seconds

University of Michigan researchers developed software called Verdict that enables existing databases to learn from each query a user submits, finding accurate answers without trawling through the same data again and again. Verdict allows databases to deliver answers more than 200 times faster while maintaining 99 percent accuracy. In a research environment, that could mean getting answers in seconds instead of hours or days. [Full Story]

Related Topics:  Big Data  Lab-Systems  Mozafari, Barzan  

Codeon is the Intelligent Assistant for Software Developers

Researchers, including Profs. Walter S. Lasecki and Steve Oney, and graduate students Yan Chen and Yin Xie have created Codeon, a system that enables more effective task hand-off between end-user developers and remote helpers by allowing asynchronous responses to on-demand requests. With Codeon, developers can request help by speaking their requests aloud within the context of their Integrated Development Environment. [Full Story]

Related Topics:  Lab-Artificial Intelligence  Lab-Systems  Lasecki, Walter  

Accelerating the Mobile Web: Vroom Software Could Double its Speed

Vroom software, developed by computer scientists including Prof. Harsha Madhyastha and CSE graduate student Vaspol Ruamviboonsuk, can dramatically speed the loading of webpages on mobile devices. [Full Story]

Related Topics:  Lab-Systems  Madhyastha, Harsha  Mobile Computing  

Kurator Will Help You Curate Your Personal Digital Content

People capture photos, audio recordings, video, and more on a daily basis, but organizing all these digital artifacts quickly becomes a daunting task. Automated solutions struggle to help us manage this data because they cannot understand its meaning. Profs. Walter Lasecki and Mark Ackerman have helped create Kurator, a hybrid intelligence system leveraging mixed-expertise crowds to help families curate their personal digital content. [Full Story]

Related Topics:  Ackerman, Mark  Lab-Artificial Intelligence  Lab-Systems  Lasecki, Walter  

Movie Design for Specific Target Audiences

Creating products that satisfy the market is critical to companies as it determines their success and revenue. Currently, experts use their judgment to estimate solutions to designing a new product that will satisfy customers, but this does not scale or allow leveraging massive datasets. Prof. Danai Koutra and her colleagues sought to identify how they can design new movies with features tailored to a specific user population. [Full Story]

Related Topics:  Koutra, Danai  Lab-Artificial Intelligence  Lab-Systems  

All CSE News for 2018