Research is the biggest driving force behind innovation and success. It is also the main reason why many of us are drawn to higher education. It is the bread and butter of what we do and why we do it. It is the motivation behind all those underpaid hours we spend in front of our computers designing surveys, crunching numbers, reviewing the literature, making grant deadlines, tediously crafting and re-crafting study protocols, running experiments, going through zillions of revisions on our manuscripts…
The UC Berkeley D-Lab (Social Sciences Data Laboratory) is hiring up to five full-fee remission, 50% time appointment (20 hours/week), graduate student researcher (GSR) positions starting in January 2020 to teach workshops and provide consulting. These positions may be renewed.
In a previous blog I wrote about an exciting project on transportation in cities that, along with some colleagues, I’ve had the opportunity to work on.
Former D-Lab instructor and consultant Chris Hench, now a research scientist in Alexa AI’s Applied Modeling and Data Science group at Amazon, has been collaborating on a project that made it possible for Amazon’s Alexa to feature three new languages: Hindi, U.S. Spanish and Brazilian Portuguese.
Those who are new to data science are recommended by data science blogs and data scientists to pursue side projects. These side projects should showcase your skill set and help you create a foundation for your portfolio. The job industry places a large emphasis on ones “research portfolio” as an important piece of landing a job. Despite this sound logic, I pursue side projects for different reasons..
The advent of the Big data exploitation has led to an increased focus on data-driven decision making. These changes have created giant leaps in technology for different sectors including health care, supply chains, agriculture,online retailing among others.
Last year, some friends discovered that I didn’t use the digital assistant on my phone, very often. This seemed counterintuitive, given that I am a linguist interested specifically in speech, including speech recognition. So, as an exercise, I reactivated my “Hey Siri” feature and said “Hey Siri” a handful of times into my microphone when prompted. I have since embarked on my journey to talk to a rectangular piece of plastic and glass, with varying degrees of success.
Big data has been a buzz word for a few years and the trend of its expansion into other fields is by no means slowing down. As always, where there is a “gold rush” of a new concept lawyers do not fall very far behind, even if it is about numbers—something lawyers do not particularly claim a forte in.
In this short blogpost I will sketch out my perspective on the principles which I believe underpin the Computational Text Analysis Working Group (CTAWG) here at D-Lab. As the composition of CTAWG will inevitably change over time, I have come to the realization that a statement on the working group's objectives and guiding principles is necessary for the preservation of institutional memory.
