The KDD 2017 Workshop on Advancing Education with Data will be held in conjunction with the Knowledge Discovery and Data Mining conference on the morning of 14 August 2017 in beautiful Halifax, Nova Scotia, Canada. The workshop will bring together data scientists and educators together to stimulate research in the interdisciplinary field of data science for education. At this year’s workshop, we are highlighting the following areas of interest: (1) Lifelong learning, (2) Assessments, (3) Learning Analytics and Personalization, and (4) Infrastructure.
KDD is a premier interdisciplinary conference bringing together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data.
- Paper submission deadline: May 26, 2017
- Author notification: June 16, 2017
- Final version of accepted submissions: June 30, 2017
- Final workshop schedule: June 30, 2017
- Workshop: August 14, 2017
More details can be found on the workshop website.
Rice University DSP faculty member Richard Baraniuk has been elected to the American Academy of Arts and Sciences. He is one of 228 new members announced today by the academy, which honors some of the world’s most accomplished scholars, scientists, writers, artists and civic, business and philanthropic leaders. The academy is one of the country’s oldest learned societies and independent policy research centers. It convenes leaders from the academic, business and government sectors to respond to the challenges facing - and opportunities available to - the nation and the world.
Rice press release
DSP PhD student AmirAli Aghazadeh, DSP PhD alum Mona Sheikh, Bioengineering professor Rebekah Drezek, Bioengineering alums Allen Chen and Adam Yuh Lin, and DSP professor Richard Baraniuk have been awarded the 2017 Hershel M. Rich Invention Award for their development of Universal Microbial Diagnostics (UMD). UMD is a radically new way to detect and classify bacteria and other microbials that is fast (minutes rather than days) and efficient. (Double congratulations to Dr. Aghazadeh, who defended his PhD thesis today!)
Rice and Baylor College of Medicine Assistant Professor Xaq Pitkow has received an NSF CAREER award for his project "Distributed Nonlinear Neural Computation." The project will develop new quantitative theories that explain brain function as distributed nonlinear neural computations that implement principles of statistical reasoning. To test these theories, he is collaborating with experimentalists to design and interpret neuroscience experiments that quantify both what information about naturalistic tasks is encoded in neural populations and what aspects of that information are actually decoded.
DSP faculty member Richard Baraniuk is one of 13 Vannevar Bush Faculty Fellows announced today by the U.S. Defense Department. The fellows program provides extensive, long-term financial support for distinguished university scientists and engineers to pursue “blue sky” basic research that could produce revolutionary new technologies. The program was launched in 2008 as the National Security Science and Engineering Faculty Fellowship (NSSEFF) program and renamed this year in honor of Vannevar Bush, the famed American engineer and inventor who headed U.S. scientific research during World War II and later helped found the National Science Foundation. Baraniuk, Rice's Victor E. Cameron Professor of Electrical and Computer Engineering, is a leading expert on compressive sensing, a branch of signal processing that enables engineers to glean useful information from far fewer data samples than would typically be required.
DOD press release
Rice University press release
Rice Assistant Professor Anshumali Shrivastava has received an NSF CAREER award for his project "Hashing and Sketching Algorithms for Resource-Frugal Machine Learning." The project will develop new probabilistic hashing techniques to advance state-of-the-art machine learning algorithms. Apart from being exponentially cheaper, the new algorithms will also be massively parallelizable. The project capitalizes on several recent ideas, including asymmetric hashing, hash-based kernels, densified hashing schemes, sub-linear adaptive sampling, and adaptive sketching, to push learning algorithms to the extreme-scale.
Richard Baraniuk, Rice University's Victor E. Cameron Professor of Electrical and Computer Engineering, has been elected a Fellow of the National Academy of Inventors. He is one of 175 academic inventors named this year, and is now among 757 fellows representing 229 research universities and governmental and nonprofit research institutes. NAI Fellows have demonstrated a prolific spirit of innovation to create or facilitate inventions that have made a tangible impact on quality of life, economic development and the welfare of society. Combined, they are named inventors on more than 26,000 U.S. patents.
Thanks for making the Rice Machine Learning Workshop on January 24, 2017 a great success! Over 400 attendees participated in a range of sessions on not just new machine learning theory and algorithms but their applications in the energy, medical, financial, and legal industries.
Rice University faculty speakers: Genevera Allen on sparse learning, Richard Baraniuk on advanced data analytics, Paul Hand on machine vision, Ankit Patel on deep learning, and Anshumali Shrivastava on large-scale learning.
Industry speakers: Thomas Halsey (ExxonMobil) on machine learning in the energy industry, Satyam Priyadarshy (Halliburton) on machine learning in the upstream oil and gas industry, Craig Rusin (Medical Informatics Corp.) on patient informatics; Hardeep Singh (VA Hospital Houston) on reducing medical misdiagnosis through machine learning, and Alan Lockett (CS Disco) on machine learning in the legal domain.
Keynote speaker: Alfred Spector (Two Sigma)
See you next year at ML@RICE 2018!
How thin can a camera be? Very, say Rice University researchers who have developed patented prototypes of their technological breakthrough.
FlatCam, invented by the labs of Rice DSP faculty members Richard Baraniuk and Ashok Veeraraghavan, is little more than a thin sensor chip with a mask that replaces the lenses in a traditional camera.
Making it practical are the sophisticated computer algorithms that process what the sensor detects and converts the sensor measurements into images and videos. More info.