U-M fosters thriving artificial intelligence and machine learning research

By | General Interest, HPC, News, Research

Research using machine learning and artificial intelligence — tools that allow computers to learn about and predict outcomes from massive datasets — has been booming at the University of Michigan. The potential societal benefits being explored on campus are numerous, from on-demand transportation systems to self-driving vehicles to individualized medical treatments to improved battery capabilities.

The ability of computers and machines generally to learn from their environments is having transformative effects on a host of industries — including finance, healthcare, manufacturing, and transportation — and could have an economic impact of $15 trillion globally according to one estimate.

But as these methods become more accurate and refined, and as the datasets needed become bigger and bigger, keeping up with the latest developments and identifying and securing the necessary resources — whether that means computing power, data storage services, or software development — can be complicated and time-consuming. And that’s not to mention complying with privacy regulations when medical data is involved.

“Machine learning tools have gotten a lot better in the last 10 years,” said Matthew Johnson-Roberson, Assistant Professor of Engineering in the Department of Naval Architecture & Marine Engineering and the Department of Electrical Engineering and Computer Science. “The field is changing now at such a rapid pace compared to what it used to be. It takes a lot of time and energy to stay current.”

Diagram representing the knowledge graph of an artificial intelligence system, courtesy of Jason Mars, assistant professor, Electrical Engineering and Computer Science, U-M

Johnson-Roberson’s research is focused on getting computers and robots to better recognize and adapt to the world, whether in driverless cars or deep-sea mapping robots.

“The goal in general is to enable robots to operate in more challenging environments with high levels of reliability,” he said.

Johnson-Roberson said that U-M has many of the crucial ingredients for success in this area — a deep pool of talented researchers across many disciplines ready to collaborate, flexible and personalized support, and the availability of computing resources that can handle storing the large datasets and heavy computing load necessary for machine learning.

“The people is one of the reasons I came here,” he said. “There’s a broad and diverse set of talented researchers across the university, and I can interface with lots of other domains, whether it’s the environment, health care, transportation or energy.”

“Access to high powered computing is critical for the computing-intensive tasks, and being able to leverage that is important,” he continued. “One of the challenges is the data. A major driver in machine learning is data, and as the datasets get more and more voluminous, so does the storage needs.”

Yuekai Sun, an assistant professor in the Statistics Department, develops algorithms and other computational tools to help researchers analyze large datasets, for example, in natural language processing. He agreed that being able to work with scientists from many different disciplines is crucial to his research.

“I certainly find the size of Michigan and the inherent diversity that comes with it very stimulating,” he said. “Having people around who are actually working in these application areas helps guide the direction and the questions that you ask.”

Sun is also working on analyzing the potential discriminatory effects of algorithms used in decisions like whether to give someone a loan or to grant prisoners parole.

“If you use machine learning, how do you hold an algorithm or the people who apply it accountable? What does it mean for an algorithm to be fair?” he said. “Can you check whether this notion of non-discrimination is satisfied?”

Jason Mars, an assistant professor in the Electrical Engineering and Computer Science department and co-founder of a successful spinoff called Clinc, is applying artificial intelligence to driverless car technology and a mobile banking app that has been adopted by several large financial institutions. The app, called Finie, provides a much more conversational interface between users and their financial information than other apps in the field.

“There is going to be an expansion of the number of problems solved and number of contributions that are AI-based,” Mars said. He predicted that more researchers at U-M will begin exploring AI and ML as they understand the potential.

“It’s going to require having the right partner, the right experts, the right infrastructure, and the best practices of how to use them,” he said.

He added that U-M does a “phenomenal job” in supporting researchers conducting AI and ML research.

“The level of support and service is awesome here,” he said. “Not to mention that the infrastructure is state of the art. We stay relevant to the best techniques and practices out there.”

Advanced Research Computing at U-M, in part through resources from the university-wide Data Science Initiative, provides computing infrastructure, consulting expertise, and support for interdisciplinary research projects to help scientists conducting artificial intelligence and machine learning research.

For example, Consulting for Statistics, Computing and Analytics Research, an ARC unit, has several consultants on staff with expertise in machine learning and predictive analysis with large, complex, and heterogeneous data. CSCAR recently expanded capacity to support very large-scale machine learning using tools such as Google’s TensorFlow.

CSCAR consultants are available by appointment or on a drop-in basis, free of charge. See cscar.research.umich.edu or email cscar@umich.edu for more information.

CSCAR also provides workshops on topics in machine learning and other areas of data science, including sessions on Machine Learning in Python, and an upcoming workshop in March titled “Machine Learning, Concepts and Applications.”

The computing resources available to machine learning and artificial intelligence researchers are significant and diverse. Along with the campus-wide high performance computing cluster known as Flux, the recently announced Big Data cluster Cavium ThunderX will give researchers a powerful new platform for hosting artificial intelligence and machine learning work. Both clusters are provided by Advanced Research Computing – Technology Services (ARC-TS).

All allocations on ARC-TS clusters include access to software packages that support AI/ML research, including TensorFlow, Torch, and Spark ML, among others.

ARC-TS also operates the Yottabyte Research Cloud (YBRC), a customizable computing platform that recently gained the capacity to host and analyze data governed by the HIPAA federal privacy law.

Also, the Michigan Institute for Data Science (MIDAS) (also a unit of ARC) has supported several AI/ML projects through its Challenge Initiative program, which has awarded more than $10 million in research support since 2015.

For example, the Analytics for Learners as People project is using sensor-based machine learning tools to translate data on academic performance, social media, and survey data into attributes that will form student profiles. Those profiles will help link academic performance and mental health with the personal attributes of students, including values, beliefs, interests, behaviors, background, and emotional state.

Another example is the Reinventing Public Urban Transportation and Mobility project, which is using predictive models based on machine learning to develop on-demand, multi-modal transportation systems for urban areas.

In addition, MIDAS supports student groups involved in this type of research such as the Michigan Student Artificial Intelligence Lab (MSAIL) and the Michigan Data Science Team (MDST).

(A version of this piece appeared in the University Record.)

[SC2 Jobs] Postdoctoral and senior fellowships at the NASA Postdoctoral Program

By | SC2 jobs

The NASA Posdoctoral Program provides fellowships to conduct cutting-edge research at NASA Centers and NASA-affiliated research institutes, and is offering Postdoctoral and Senior Fellowship positions.

Research areas include aeronautics and engineering, astrobiology, astrophysics, biological sciences, cosmochemistry, earth science, heliophysics science, planetary science, technology development, and science management.

Appointments up to three years, and stipends begin at $53,500 increasing depending on locality and seniority. $8,000 is granted for support of professional travel per year. Health insurance and relocation assistance available.

Applications are due by March 1, July 1, November 1, 2018. Please see npp.usra.edu for more information. Women, minorities, and members of underrepresented communities are encouraged to apply.

Job category

Postdoctoral Fellow, Senior Fellowship

Location

N/A

Application deadline

March 1, July 1, November 1, 2018

[SC2 Jobs] Assistant Professor at the University of Nebraska, Lincoln

By | SC2 jobs

The Department of Mechanical & Materials Engineering at the University of Nebraska-Lincoln (http://mme.unl.edu) invites applications for two tenure-track faculty positions at the Assistant Professor level in the areas of (1) dynamics, systems, and design, or (2) thermal/fluids sciences and energy  conversion. Successful candidates are expected to develop an externally funded research program in emerging areas which may include: robotics and automation, micro/nanoscale thermal/fluids, optimal design, additive manufacturing, and micro/nanotechnology device development. The successful candidates will contribute to the undergraduate and graduate academic programs within the department and demonstrate a commitment to excellence in both teaching and research.

Applicants are expected to have a Ph.D. or equivalent in mechanical engineering or a closely related field. Applicants should have a record of strong scholarly achievement and a demonstrated commitment to excellence in undergraduate and graduate education with the potential to establish a strong externally-funded research program.

 

 

Please see https://employment.unl.edu/postings/56098 for more information on how to apply.

Job category

Assistant Professor

Location

Lincoln, Nebraska

 

[SC2 Jobs] Assistant Professor in Coastal Resiliency at Rice University

By | SC2 jobs

The Rice University Department of Civil and Environmental Engineering invites applications for a tenure track assistant professor position in the area of Coastal Resiliency. We seek candidates with expertise and interest in interdisciplinary research that contributes to enhancing the resilience of urban communities and infrastructure systems to the impacts of coastal natural hazards and climate change. Areas of interest include, but are not limited to: (1) urban hydrology, water resources, urban flood analysis, and coastal hydrodynamics; (2) modeling of natural hazards, infrastructure systems, and risk assessment in coastal settings; (3) and state-of-the-art remote sensing techniques. The successful candidate is expected to establish a rigorous, externally funded research program, to teach core courses and develop undergraduate and graduate courses within their area of expertise, advise graduate students, collaborate with other faculty, and be involved in service to the university and the broader scientific community.

Applicants must have earned a Ph.D. degree in Civil /Environmental Engineering or a related field, demonstrate excellence in research, display distinction (or potential for distinction) in teaching, and be able to collaborate across disciplines.

To apply, please submit materials in electronic form through the Rice Application Portal via this link:
http://jobs.rice.edu/postings/12464

Please see http://www.usacm.org/jobs/133 for more information.

Job category

Assistant Professor

Location

Houston, TX

 

[SC2 Jobs] Postdoc Researcher at the Virginia Polytechnic Institute and State University

By | SC2 jobs

The Computational Mechanics Laboratory in the Department of Biomedical Engineering and Mechanics is seeking applications from outstanding candidates for a Postdoctoral Researcher position. The duties involve using commercial either finite element based or meshless methods based software to numerically study deformations, failure and penetration during impact events. The candidate will prepare technical reports detailing the work done, analysis methods, and interpretation of results. Also, they will prepare journal articles suitable for publication in peer-reviewed journals, and present research findings at relevant conferences.

Applicants must have earned a Ph.D. in either Engineering Mechanics, Mechanical Engineering, Applied Mechanics or Computational Science and Engineering. Expertise in Computational Solid Mechanics. Experience in high performance computing, developing subroutines for commercial software. Good knowledge of FORTRAN and/or C++. Proven oral and written communication skills.

Interested persons should apply by clicking on the link: https://listings.jobs.vt.edu/postings/81623

Please see http://www.usacm.org/jobs/132 for more information.

Job category

Postdoc researcher

Location

Blacksburg, VA

 

[SC2 Jobs] Tenure-Track Faculty Position at Carnegie Mellon University

By | SC2 jobs

Carnegie Mellon University’s Department of Civil and Environmental Engineering (CEE) invites applications at the Assistant Professor level for a faculty member with expertise in mechanics and interest in any civil and environmental engineering application domain. We will also consider highly-qualified applicants at the untenured Associate Professor level.

Applicants must have earned a Ph.D. in civil and environmental engineering or a related field by the start date for the position. We invite applications from individuals with expertise in experimental, theoretical, and/or computational mechanics, and interests in civil and environmental engineering applications. Please discuss potential intersections with existing faculty research areas, and alignment with one or more research centers and institutes within the department or university.

 

Applications will be accepted until December 31, 2017.

Review of applications will begin on December 15, 2017 and will continue until the position is filled. The expected start date is August 1, 2018.

Please submit your application, including a cover letter, curriculum vitae, transcripts (official or unofficial), statement of research experience and interests, statement of teaching experience and interests, a diversity statement (outlining how you have contributed to, or plan to contribute to, diversity, inclusion, and equity), up to three publications or manuscripts, and a list of at least three references with contact information. We will notify you in advance of any requests for reference letters.

Please see http://www.usacm.org/jobs/131 for more information.

Job category

Assistant Professor

Location

Pittsburgh, Philadelphia

Application Deadline

December 31, 2017

 

[SC2 Jobs] Postdoc Research Associate at the Scientific Computation Research Center, Rensselaer Polytechnic Institute

By | SC2 jobs

The Scientific Computation Research Center  (www.scorec.rpi.edu) at Rensselaer is seeking highly qualified post-doctoral research associates to develop parallel adaptive unstructured mesh technologies that will be applied in multiple areas of application including fusion modeling, computational fluid dynamics and others.

Applicants are expected to have a PhD in Engineering, Applied Mathematics,  Computer/Computational Science, or related discipline. Applicants should have expertise in a subset of the areas listed and be interested in working closely with others that provide expertise in the other areas: Unstructured meshing generation/adaptation technologies, development and optimization of parallel Particle in Cell methods (PIC), development of parallel unstructured simulation technologies, experience in parallel programming and high performance computing, good knowledge of FORTRAN, C and/or C++ programming languages and GNU/Linux operating system is required, and knowledge of modern software engineering tools will be considered favorably.

Please see http://www.usacm.org/jobs/129 for more information on how to apply.

Job category

Postdoc Research Associate

Location

Troy, NY