Data Science newsletter – February 18, 2020

Newsletter features journalism, research papers, events, tools/software, and jobs for February 18, 2020


Data Science News

University of Chicago to build instrumentation for upgrades to the LHC

University of Chicago, UChicago News


In 2012, scientists and the public around the world rejoiced at the news that CERN’s Large Hadron Collider had discovered the long-sought Higgs boson—a particle regarded as a linchpin in the Standard Model of particle physics, the theory that describes the fundamental forces and classifies all known elementary particles.

Despite the breakthrough, subsequent collisions in the machine have yet to produce evidence of what physicists call “new physics”: science that could address the areas where the Standard Model seems to break down—like dark matter, dark energy and why there is more matter than antimatter. So now, the particle accelerator and its detectors are getting an upgrade.

On Feb. 5, the National Science Foundation and the National Science Board gave the green light for $75 million in funding for upgrades to the ATLAS experiment, one of the collider’s two 7-story high and half a football-field long detectors—opening the doors for the discovery of new particles and rare processes. Approximately $5.5 million will go to the University of Chicago, a founding member of the ATLAS experiment, to design and build several components for the upgraded detector.

University introduces new CS plus animal sciences major

The Daily Illini, Michael Caruso


The University is introducing a new computer science plus animal sciences major for the fall 2020 semester. This will be the eleventh CS+X major available at the University and the second degree program for CS+X in the College of ACES.

However, this is the first program that will combine animal sciences with computer science in the entire country, said Rodney Johnson, head of the Department of Animal Sciences.

Program to introduce undergrad researchers to machine learning in cybersecurity

Penn State University, Penn State News


Undergraduate students interested in machine learning in cybersecurity research activities are invited to apply to a new Research Experiences for Undergraduates (REU) Site program, to be hosted this summer at Penn State’s College of Information Sciences and Technology.

Funded by the National Science Foundation, the intensive 10-week program will engage research-oriented undergraduate students in research projects focusing on topics such as fake news mitigation, smart contract fraud, and privacy in conversational agents. Nine applicants from institutions across the country will be selected for the 2020 program, and each will be paired with a College of IST faculty mentor.

The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence

arXiv, Computer Science > Artificial Intelligence, Gary Marcus


Recent research in artificial intelligence and machine learning has largely emphasized general-purpose learning and ever-larger training sets and more and more compute. In contrast, I propose a hybrid, knowledge-driven, reasoning-based approach, centered around cognitive models, that could provide the substrate for a richer, more robust AI than is currently possible.

Low-cost “smart” diaper can notify caregiver when it’s wet

MIT News


MIT researchers have developed a “smart” diaper embedded with a moisture sensor that can alert a caregiver when a diaper is wet. When the sensor detects dampness in the diaper, it sends a signal to a nearby receiver, which in turn can send a notification to a smartphone or computer.

The sensor consists of a passive radio frequency identification (RFID) tag, that is placed below a layer of super absorbent polymer, a type of hydrogel that is typically used in diapers to soak up moisture. When the hydrogel is wet, the material expands and becomes slightly conductive — enough to trigger the RFID tag to send a radio signal to an RFID reader up to 1 meter away.

U.S. mulls cutting Huawei off from global chip suppliers, with TSMC in crosshairs

Reuters, Alexandra Alper and Karen Freifeld


The Trump administration is considering changing U.S. regulations to allow it to block shipments of chips to Huawei Technologies from companies such as Taiwan’s TSMC (2330.TW), the world’s largest contract chipmaker, two sources familiar with the matter said.

Artificial Intelligence Gets Its Own System of Numbers

EE Times, Sally Ward-Foxton


BF16, the new number format optimized for deep learning, promises power and compute savings with a minimal reduction in prediction accuracy

BF16, sometimes called BFloat16 or Brain Float 16, is a new number format optimised for AI/deep learning applications. Invented at Google Brain, it has gained wide adoption in AI accelerators from Google, Intel, Arm and many others.

The messy, secretive reality behind OpenAI’s bid to save the world

MIT Technology Review, Karen Hao and Jonathan Stray


The AI moonshot was founded in the spirit of transparency. This is the inside story of how competitive pressure eroded that idealism.

Apple lobbies EU lawmakers on artificial intelligence policy

Cult of Mac, Ed Hardy


Apple apparently wants to make sure the European Union doesn’t put too many restrictions on artificial intelligence. John Giannandrea, Apple’s AI chief, is reportedly in Brussels while lawmakers debate new rules on machine intelligence.

Realizing the Potential of AI Localism by Stefaan G. Verhulst & Mona Sloane

Project Syndicate, Stefaan G. Verhulst and Mona Sloane


Until recently, AI governance has been discussed primarily at the national level. But most national AI strategies – particularly China’s – are focused on gaining or maintaining a competitive advantage globally. They are essentially business plans designed to attract investment and boost corporate competitiveness, usually with an added emphasis on enhancing national security.

This singular focus on competition has meant that framing rules and regulations for AI has been ignored. But cities are increasingly stepping into the void, with New York, Toronto, Dubai, Yokohama, and others serving as “laboratories” for governance innovation. Cities are experimenting with a range of policies, from bans on facial-recognition technology and certain other AI applications to the creation of data collaboratives. They are also making major investments in responsible AI research, localized high-potential tech ecosystems, and citizen-led initiatives.

This “AI localism” is in keeping with the broader trend in “New Localism,” as described by public-policy scholars Bruce Katz and the late Jeremy Nowak. Municipal and other local jurisdictions are increasingly taking it upon themselves to address a broad range of environmental, economic, and social challenges, and the domain of technology is no exception.

It’s time for cities to address “privacy fatigue” — they’ll need design help

Medium, Sidewalk Labs, Eric Jaffe


New research shows the challenge of designing alerts that we can assess quickly without missing key information. As privacy notices move into the physical world, cities need solutions.

‘Moving the Goalposts’: What You Need to Know About DeVos’s Closer Scrutiny of Foreign Gifts

The Chronicle of Higher Education, Lindsay Ellis and Dan Bauman


Calling for more reporting of foreign gifts than is widely practiced, the U.S. Department of Education’s letters to Harvard and Yale Universities this week signaled a ratcheting up of scrutiny of relations between American campuses and Chinese entities.

In the two letters, each dated Tuesday, the department said Harvard and Yale may not have fully detailed their gifts and contracts with foreign entities as required by federal law. The cited provision requires universities to tell the Education Department about gifts from and contracts with foreign sources greater than $250,000.

But in the letters, the department appeared to urge a thorough accounting of all programs, activities, and people funded with money from foreign entities — no matter how small. The letters raised alarms that such an onerous requirement could discourage collaboration between American campuses and those abroad, and the targeting of Harvard and Yale showed a focus on high-profile institutions that could catch other campuses’ eyes.

Responsible Data Science: Charting New Pedagogical Territory

Medium, NYU Center for Data Science


In response to the dearth of scholarship surrounding responsible data science (RDS), NYU CDS faculty are paving the way with a course dedicated to RDS and the publication of their pedagogical methodology.

The demand for data scientists is growing, and so is the need for an ethical approach to the handling of data. Many technical students still disregard the importance of data-related ethics courses, and the nascent area of study known as responsible data science (RDS) has yet to be codified as a course of study at most university campuses. The lack of pedagogical RDS methods and resources creates a unique challenge for data scientists and educators in the field.

Top 3 Data Challenges to Addressing the Social Determinants of Health

HealthIT Analytics, Jessica Kent


An individual’s race, ethnicity, income level, or geographic location often has more influence on her physical and mental health than clinical factors, and the industry has made a concentrated effort to better address these social determinants. … A recent report published in Health Affairs showed that many accountable care organizations (ACOs) lacked data on both their patients’ social needs and the capabilities of their potential community partners. ACOs also reported difficulties in determining how to best approach return on investment with social determinants initiatives.


Marathon Match – Predict how different shapes bend under pressure

“In this problem you will be given a 3D shape, a hollow rectangular box, with walls of some thickness and with some holes cut out of it. Your code should read a model file describing this shape, and then estimate how it will be affected when pressed by a moveable bar. In addition to the displacement, you will also be asked to estimate the maximum stress experienced at each node.” Deadline for registrations is February 23.

Short Paper Call for Participation – IEEE Vis 2020

“IEEE Vis 2020 solicits submissions in a short paper format. Short papers draw from the same paper types and topics as full papers of VAST, Infovis and Scivis, ranging from theoretical to applied research contributions.” Deadline for submissions is June 13.
Tools & Resources

How Wittgenstein can help you explain and use an mHealth schema

Open mHealth, David Haddad


In this post I’m going to break down what an Open mHealth data standard is through an mHealth schema and why need this to drive greater health data interoperability.

I’ll also show you can use the Open mHealth data schemas today to help you make your patient-generated data cleaner and simpler to use.

31 Ways to Make Your APIs More Secure

freeCodeCamp, Fatos Morina


“It is a list with some really helpful tips that you can immediately apply in your APIs.”

The GigaIO FabreX Network – New Frontiers in Networking For Big Data



GigaIO has developed a new whitepaper to describe GigaIO FabreX, a fundamentally new network architecture that integrates computing, storage, and other communication I/O into a single-system cluster network, using industry standard PCIe (peripheral component interconnect express) technology.

Have you ever felt someone you know was in #burnout risk? Helping starts with a serious assessment.

Twitter, Marcos Sponton



Full-time positions outside academia

Chief Innovation Officer

City Manager of Oklahoma City; Oklahoma City, OK

Postdoctoral fellowship (-s)

Aarhus University, DATALAB – Center for Digital Social Research; Aarhus, Denmark
Tenured and tenure track faculty positions

Two Open-Rank Faculty Positions in Cognitive Science

Central European University, Department of Cognitive Science; Vienna, Austria

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