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Thursday, April 18, 2019

New PhD program in Quantitative Life Sciences approved | Newsroom - McGill University

An innovative interdisciplinary PhD program will bridge the gap between the quantitative and biological domains to improve life sciences research, continues News releases.
 

Photo: McGill University
Quantitative Life Sciences (QLS), a joint venture initiated by the Faculties of Medicine and Science at McGill University and now involving many other faculties, has been given the green light by the Ministère de l’Éducation et l’Enseignement supérieur (MEES). The new program is one of three offered through McGill’s Interfaculty Studies (Biological and Biomedical Engineering and the Integrated Program in Neuroscience are the others) and is currently accepting applicants for September 2019.

“We need researchers who can develop and apply powerful mathematical and computational methods to life sciences research, and thereby help to solve pressing biological and medical challenges,” says inaugural Graduate Program Director for the PhD program, Dr. Celia Greenwood, Professor in the departments of Oncology, Human Genetics and Epidemiology, Biostatistics & Occupational Health, in the Faculty of Medicine. “The current timelines for translational bioscience research can be slow and costly. Often this is because we lack quantitative tools and approaches to work with the enormous datasets currently being generated.”

The new program will equip students to create, improve and apply quantitative methods originating in the fields of mathematics, physics, statistics and computer science to the broad study of biological systems, from single molecules to entire ecosystems.
Read more...

Source: McGill University


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How to be a PhD supervisor | Features - Times Higher Education (THE)

The relationship between PhD students and their supervisors is often said to be the most intense in the academy, with huge implications for student success. Yet most supervisors receive little if any training, argues Philip Moriarty et al.

Photo: Times Higher Education (THE)

The anomaly of academics receiving years of training in research but none in teaching is often remarked upon. But, equally notoriously, what that research training amounts to very much depends on the individual supervisor. After all, academics are not trained in research supervision either, and both supervisors and supervisees have their own set of expectations, needs and aptitudes.

How much and what variety of direction is appropriate? And to what end? Is the PhD still best conceived exclusively as an apprenticeship for would-be academics, even though many doctoral graduates end up – willingly or otherwise – in other walks of life? Indeed, is it realistic to expect all PhD students to be proficient in independent research at the end of the process? And what to do with those who are not? Is it the supervisor’s task to make sure they drop out early? Must supervisors always be optimistic and encouraging, offering whatever level of micromanagement is necessary to get the student through?

Here, six academics give their own takes on where the lines should be drawn in the doctoral quicksand.
Read more... 

Source: Times Higher Education (THE)


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Riverside-area students show off their skills with robots | Press-Enterprise

Ryan Hagen, reporter observes, April 17, to display the abilities they learned in robotics engineering classes.

Candice, a robotic dog programmed in part by the Art Club and Robotics Club from Riverside’s Wells Middle School students takes part Wednesday, April 17, in the second annual After-School Robotics Showcase in the Alvord Unified School District.
Photo: Milka Soko, contributing photographer
It was part of a robotics and STEM celebration at Riverside’s Arizona Middle School in the Alvord Unified School District...

Students worked with LEGO-compatible programmable robotic kits that were developed by Blue Brain Bot in Riverside, a division of Creative Brain Learning.
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Source: Press-Enterprise


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Plini, BTBAM, Tesseract Discuss: Should You Take Guitar Lessons & Learn Music Theory? | Ultimate-Guitar.Com

During a conversation with Total Guitar, Between the Buried and Me guitarists Paul Waggoner and Dustie Waring, Plini, Jake Howsam, and Tesseract guitarists Acle Kahney and James Monteith talked about guitar lessons and the importance of mastering music theory.

Photo: © Olly Curtis / Future
You can check out a part of the interview below. 

You're all a mix of being self-taught and having had formal lessons when you were starting out, are there advantages to being self-taught when it comes to finding your own way?

Plini: "I think it might have been bad if I'd had a bad teacher who had told me I'd never be anything and that C is the only scale. But I think if you have a good teacher it's probably inspiring."

Acle Kahney, Tesseract: "Yes, inspiring more than stifling."

Paul Waggoner, BTBAM: "I think it depends on what trajectory you're looking for as a musician. If you want to be a classical guitar player, obviously, you're going to want to learn how to sight-read.

"But in the world that we're in, it's probably good to have a healthy balance. For me, learning music theory was more of a communication tool, a way to communicate to other band members. But I could see how it could maybe stifle creativity a little bit; if you adhere to that kind of thing too much it becomes very regimented and can maybe build a wall around your creativity."
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Source: Ultimate-Guitar.Com


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Foundation names Dracut one of best school systems for music | Lowell Sun

The sounds of Dracut High School's string orchestra filled every corner of the room on a recent Tuesday morning with Robin Mallory at the helm, notes Amaris Castillo, reporter for The Lowell Sun.

Orchestra Director Robin Mallory conducts Dracut High School's string orchestra on April 2. Dracut Public Schools was recently named one of the Best Communities for Music Education from the NAMM Foundation. NAMM stands for National Association of Music Merchants.
Photo: SUN/Amaris Castillo
"Here we go, ba-dam!" the orchestra director said as the student musicians performed a medley of songs featured in the Academy Award-winning film "La La Land."

Over the next hour, Mallory would periodically pause the ninth- to 12th-grade students to give them instruction and perfect their collective sound.

Mallory's leadership at Dracut High is just one facet of music education within Dracut Public Schools, which was recently named one of the Best Communities for Music Education from the NAMM Foundation. NAMM stands for National Association of Music Merchants. The signature program recognizes and celebrates school districts and schools for their support and commitment to music education and efforts to assure access to music for all students as part of a well-rounded education, according to the NAMM Foundation's website...

In an email Zolezzi said the survey administered by The Music Research Institute at the University of Kansas evaluates schools and districts "based on funding, staffing of highly qualified teachers, commitment to standards, and access to music instruction."
Coordinator of Performing Arts Carolyn Cardella submitted the survey on Dracut Public Schools' behalf with the support of Superintendent of Schools Steven Stone. It is one of 14 communities in Massachusetts to be recognized.

"I'm extremely proud of the staff and the students," Cardella said recently. "I don't feel that I can claim any credit for it because it's the programs that they've had in place that they've been doing for many years now. I just helped them get recognized for it."
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Source: Lowell Sun


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Wednesday, April 17, 2019

Peeking into the Black Box of Artificial Intelligence | Technology - BBN Times

While artificial intelligence (AI) applications are becoming increasingly capable of solving even the most complex of our problems requiring human-like cognition, the black box of artificial intelligence makes it difficult for us to understand how these systems actually go about solving these problems, as BBN Times reports.  

Photo: BBN Times
Although humans had always known about the existence of fire, it was only when we learned to control or “tame” fire that we really kickstarted the journey of rapid technological progress and evolution we currently find ourselves in. Now, over a million years later, we find ourselves at a similar juncture—albeit faced with an entity that we created instead of a natural phenomenon. The creation of artificial intelligence, undoubtedly, is a step into an era of unprecedented growth unlike any we’ve seen before. But, a true leap can only be achieved once we “tame” the technology, as it were, by first illuminating the black box of artificial intelligence that will enable us to better control the outcomes affected by the technology. 

Our brain, the apotheosis of human evolution and the most vital of our organs, also happens to be the most complex and enigmatic things known to us. Similarly, artificial intelligence, which represents the pinnacle of human technological development, is equally perplexing—despite the fact that it has been created by us. To be fair to ourselves, there is a lot we do know about our brain and can predict with some certainty how it reacts to different stimuli...

Deep Neural Networks: The Working of the Black Box of Artificial Intelligence 
Deep neural networks use multiple layers of algorithms that analyze data and classify or cluster items. Since these neural networks are designed to function in ways similar to our brains, they also gain the ability to classify objects like we do—through experience. A human baby learns to differentiate between objects as it grows by observing them and learning to label them based on what it is taught by its parents. Similarly, a deep learning algorithm learns through training data that gets fed to it so that the algorithm gains “experience”. But this isn’t where the similarity between the human brain and a deep learning algorithm ends. Have you ever noticed that we gain the ability to identify different breeds of cats and dogs as “cats” and “dogs” even when we’ve never seen some breeds before? We don’t need to see every breed of dogs there is to be able to identify one when we see it for the first time. This phenomenon is called ‘generalization’, where we identify and memorize certain distinctive features of dogs (or any other entity) and use those features to generally identify a dog as one, even when we see a totally new breed with radically different features. The similar ability to generalize is also seen in AI agents who can use what they learn from one dataset to generalize across new sets of similar input.
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Source: BBN Times


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Lithium–ion battery book written by machine learning algorithm | Books - Chemistry World

A book written entirely by machine-learning algorithms has been published by Springer Nature, inform Frances Addison, Digital Content Assistant at Chemistry World.

Photo: Getty Images
It discusses current research in lithium–ion batteries and is pulled from more than 150 research articles published between 2016 and 2018. The team responsible wanted the book to demonstrate the current abilities of machine learning algorithms, and to identify problem areas that need to be improved.

Lithium–ion batteries is an area of fast moving research, with many articles published each year. To help researchers keep up with recent advances without needing to sift through vast quantities of literature, Springer Nature wanted to produce a manuscript that summarised all of the research automatically...

To give an accurate representation of the abilities of current machine learning technology, the book has not been copy-edited. This both highlights the tremendous accomplishment of the algorithm – large passages of the book read well without any obvious mistakes – as well as some of the flaws. Sentences and paragraphs have crept in where the algorithm has generated sentences that falter or are grammatically incoherent.  
Read more...

References
Beta Writer, Lithium-Ion Batteries:
A Machine-Generated Summary of Current Research. Springer Nature, 2019. 


Recommended Reading


10 Algorithms Every Machine Learning Enthusiast Should Know by Ambika Choudhury, budding Technical Journalist. 

Source: Chemistry World


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The artificial intelligence field is too white and too male, researchers say | Tech - The Verge

A new report explores AI’s ‘diversity crisis’, insist Colin Lecher, Senior Reporter at The Verge. 
 

Photo: Alex Castro / The Verge

The artificial intelligence industry is facing a “diversity crisis,” researchers from the AI Now Institute said in a report released today, raising key questions about the direction of the field.

Women and people of color are deeply underrepresented, the report found, noting studies finding that about 80 percent of AI professors are men, while just 15 percent of AI research staff at Facebook and 10 percent at Google are women. People of color are also sidelined, making up only a fraction of staff at major tech companies. The result is a workforce frequently driven by white and male perspectives, building tools that often affect other groups of people. “This is not the diversity of people that are being affected by these systems,” AI Now Institute co-director Meredith Whittaker says.

Worse, plans to improve the problem by fixing the “pipeline” of potential job candidates has largely failed. “Despite many decades of ‘pipeline studies’ that assess the flow of diverse job candidates from school to industry, there has been no substantial progress in diversity in the AI industry,” the researchers write...

Diversity, while a hurdle across the tech industry, presents specific dangers in AI, where potentially biased technology, like facial recognition, can disproportionately affect historically marginalized groups. Tools like a program that scans faces to determine sexuality, introduced in 2017, echo injustices of the past, the researchers write. Rigorous testing is needed. But more than that, the makers of AI tools have to be willing to not build the riskiest projects. “We need to know that these systems are safe as well as fair,” AI Now Institute co-director Kate Crawford says.  

Source: The Verge


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Meet Hypatia, the ancient mathematician who helped preserve seminal texts | Massive Science


The mathematician, astronomer, and philosopher Hypatia is considered the first known female mathematician and one of the “last great thinkers of Alexandria, the sophisticated Ancient Egyptian city.

Brianna Bibel, Biochemistry at Cold Spring Harbor  Laboratory reports, Her dramatic death often overshadows her epic life, but it shouldn’t.

Photo: Matteo Farinella

Why the last? Tension between religious and secular factions seeking control over the city boiled over in the early 400s, leading to her violent murder and turning her into a martyr for scientists, pagans, and atheists.

Hypatia’s death is much better recorded than her life - historians aren’t even sure when she was born (sometime around 350 CE). But there is plenty of evidence that Hypatia was a tremendous scholar.

If you wanted to learn math and astronomy in Alexandria, it helped if your dad was Theon, the last known member of Alexandria’s museum (not a museum in the sense we use the word now but more of a “university”). Theon taught Hypatia and sought her help with some of his commentaries - republications of someone else’s work with notes interpreting and explaining various parts. Commentaries such as these played an important role in preserving and advancing ancient Greek works at a time when such works were seen by many as “pagan” and opposed to Christian ideals. Many historians believe that at least one of the commentaries attributed to her father, the third book of Theon’s version of Ptolemy’s Almagest, an astronomical text used widely until the 16th century, was actually written by Hypatia...

Hypatia was a master networker - she had an “in” with many powerful figures in the ancient world, including the governor of Alexandria, Orestes. This popularity likely spawned jealousy in archbishop Cyril, already in a foul mood due to a feud with Orestes over control of the city. Orestes was a Christian, but he didn’t think the Christian Church should encroach on “civil government.” Cyril, on the other hand, wanted the church to have more control in secular affairs. The argument led to Cyril’s monks trying to assassinate Orestes, but they only succeeded at putting Orestes on high alert. But they didn’t have to look far for an easier target - Hypatia regularly traveled around, giving public lectures proudly espousing “pagan” views.
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Source: Massive Science


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The Sexist Trolls Doubting Black Hole Researcher Katie Bouman Need to Learn to Code | Black Hole - VICE

This article originally appeared on VICE US.


Last week, fans of cool astronomical phenomena (read: almost everyone) rejoiced as an international team of scientists released the first ever image of a black hole, continues VICE.

Photo: VICE
For the astrophysicists, software engineers, philosophers, and mathematicians who worked on the Event Horizon Telescope that captured the image, the announcement was an unprecedented milestone.

Their excitement was perhaps best embodied by a photo of one computer scientist on the Event Horizon Telescope team, Katie Bouman, who hid her beaming smile with her hands as she looked at the monumental rendering. Bouman had a lot to smile about—the image was created using petabytes of data that were stitched together using CHIRP, an algorithm that Bouman worked on. And Bouman had long served as a public face for the computer imaging aspect of the Event Horizon Telescope, delivering a TED Talk on the project in 2016.

But within a day of the announcement, online harassers created fake Instagram accounts for Bouman, started angry threads on Reddit and Hacker News asserting that she hadn’t done as much to help the project as she was getting credit for, and produced lengthy YouTube tirades, all with the aim of discrediting her contributions to the project...

In scientific fields that thrive on data, sexism can pass as legitimate when couched in the language of cold, unfeeling numbers and percentage points. But anyone with even a basic understanding of modern computer science should quickly realize how dangerous and plainly wrong these trolls are when they weaponize metadata from public Github repositories. 
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Source: VICE


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