Category: Interview Series

Trash Data Science: Garbology, Anthropology, and Spatial Data Science – Conversation with Gideon Singer (Part Four)

Here is the fourth and final part of my interview with Gideon Singer, Director of Spacial Data Science at Litterati, for my Interview Series. He describes the strategies he uses to collect data as a garbologist and data scientist.

Here is Part 1, Part 2, and Part 3 of our interview.

Gideon Singer is an applied anthropologist in the business of exploring societies through the waste, litter, rubbish, and other detritus they leave behind. As a self-proclaimed digital garbologist, his work juxtaposes digital ethnography with archaeology and spatial data science.

Resources:

User-Centric Thinking in Data Science: Conversation with Anna Wu at Google Cloud (Part 3 of 3)

I interviewed Anna Wu, a UX researcher and data scientist overseeing Google Cloud’s Compute Engine. In this final part of the conversation, we discuss how design thinking may useful within data science and machine learning.

Here is the first interview if you would like to start from scratch, and here is more information about Interview Series that this is a part of.

Here is Part 1 and Part 2 of our interview.

Anna Wu, established leader in building and leading high-performing data teams to drive changes impacting hundreds of millions of users. Currently as a research manager at Google, she leads a team of quantitative UX researchers applying UX methods and large scale analytics to inform Cloud product development. 

Before this recent chapter, Anna had 10+ years practicing UX and data science at top IT companies and research labs as a UX researcher, data scientist, research scientist at Microsoft, IBM Research and Palo Alto Research Center. She got her PhD in HCI from Penn State and master/bachelor degrees from Tsinghua University.

Resources:

User-Centric Thinking in Data Science: Conversation with Anna Wu at Google Cloud (Part 1 of 3)

I interviewed Anna Wu, a UX researcher and data scientist overseeing Google Cloud’s Compute Engine, as the next installment of my Interview Series,. In this first part of our conversatoin, she discusses her journey from mechanical engineering into UX research and data science and the importance of effective storytelling within these two fields.

Here is Part 2 and Part 3 of our interview.

Anna Wu, established leader in building and leading high-performing data teams to drive changes impacting hundreds of millions of users. Currently as a research manager at Google, she leads a team of quantitative UX researchers applying UX methods and large scale analytics to inform Cloud product development. 

Before this recent chapter, Anna had 10+ years practicing UX and data science at top IT companies and research labs as a UX researcher, data scientist, research scientist at Microsoft, IBM Research and Palo Alto Research Center. She got her PhD in HCI from Penn State and master/bachelor degrees from Tsinghua University.

Resources mentioned:

User-Centric Thinking in Data Science: Conversation with Anna Wu at Google Cloud (Part 2 of 3)

In this second part of my interview with Anna Wu, she describes the interconnections between data science and qualitative UX research.

Here is the first interview if you would like to start from scratch, and here is more information about Interview Series that this is a part of.

Here is Part 1 and Part 3 of our interview.

Anna Wu, established leader in building and leading high-performing data teams to drive changes impacting hundreds of millions of users. Currently as a research manager at Google, she leads a team of quantitative UX researchers applying UX methods and large scale analytics to inform Cloud product development. 

Before this recent chapter, Anna had 10+ years practicing UX and data science at top IT companies and research labs as a UX researcher, data scientist, research scientist at Microsoft, IBM Research and Palo Alto Research Center. She got her PhD in HCI from Penn State and master/bachelor degrees from Tsinghua University.

Resources mentioned:

Data Science and Game Design: Conversation with Clayton Sisson (Part 1 of 3)

Clayton Sisson is a game designer and aspiring data scientist, passionate about how data science can shed light on human behavior. For the next installment of my Interview Series, we discuss ways to use game design and UX design to develop usable and useful machine learning products and their experiences transitioning from design into data science. In this first part, we discuss the connections between data science and game design.

Here is Part 2 and Part 3 of our interview.

Resources:

Trash Data Science: Garbology, Anthropology, and Spatial Data Science – Conversation with Gideon Singer (Part Three)

Here is the third part of my interview with Gideon Singer, Director of Spacial Data Science at Litterati, for my Interview Series. He discusses how the interconnections he has found between data science and garbology.

Here is Part 1, Part 2, and Part 4 of our interview.

Gideon Singer is an applied anthropologist in the business of exploring societies through the waste, litter, rubbish, and other detritus they leave behind. As a self-proclaimed digital garbologist, his work juxtaposes digital ethnography with archaeology and spatial data science.

Resources:

Trash Data Science: Garbology, Anthropology, and Spatial Data Science – Conversation with Gideon Singer (Part Two)

Here is the second part of my interview with Gideon Singer, Director of Spacial Data Science at Litterati, for my Interview Series. He describes garbology is and what kind of work he does as a data scientist garbologist.

Here is Part 1, Part 3, and Part 4 of our interview.

Gideon Singer is an applied anthropologist in the business of exploring societies through the waste, litter, rubbish, and other detritus they leave behind. As a self-proclaimed digital garbologist, his work juxtaposes digital ethnography with archaeology and spatial data science.

Resources:

Trash Data Science: Garbology, Anthropology, and Spatial Data Science – Conversation with Gideon Singer (Part One)

I interviewed Gideon Singer, Director of Spacial Data Science at Litterati, for my Interview Series. He discusses his mission to combine garbology, anthropology, and data science to better understand humanity and the trash we leave behind. In this first part, he describes the connections he has found between these various fields.

Here is Part 2, Part 3, and Part 4 of our interview.

Gideon Singer is an applied anthropologist in the business of exploring societies through the waste, litter, rubbish, and other detritus they leave behind. As a self-proclaimed digital garbologist, his work juxtaposes digital ethnography with archaeology and spatial data science.

Resources:

Applying Computational Ethnography and Statistics to Vapor Wave: Interview with Tanner Greene (Part 2 of 2)

Here is the second part of three in my conversation with Tanner Greene. He discusses his strategies for transitioning from graduate school to UX research and his recommendations for any fellow student seeking to do the same.

Here is Part 1 of our interview.

Tanner Greene is a UX Researcher and Ph.D. Candidate at the University of Virginia, where he’s finishing a dissertation on the history of vaporwave, a music genre created on social media platforms. Tanner’s interests straddle math and the humanities, spanning digital cultures, user metadata, and a long-dormant statistics ability he wants to revive. In his spare time, Tanner enjoys writing about music, playing video games, and dreaming about learning SQL.

Resources We Referenced:

For more context on my interview series in general, click here.

Applying Computational Ethnography and Statistics to Vapor Wave: Interview with Tanner Greene (Part 1 of 2)

For my next installment in my Interview Series, I interviewed Tanner Greene. He recently received his doctorate from the University of Virginia for his research on the digital music genre, vapor wave. He primarily used qualitative means but has also taught himself Python to be able to employ quantitative textual analysis into his project. It is a good example of how to integrate qualitative digital ethnographic techniques with quantitative natural language processing.

In this first part, he discusses why he decided to study the vapor wave community and his experiences learning Python to conduct statistical analysis with.

Here is Part 2 of our interview.

Tanner’s interests straddle math and the humanities, spanning digital cultures, user metadata, and a long-dormant statistics ability he wants to revive. In his spare time, Tanner enjoys writing about music, playing video games, and dreaming about learning SQL.

Resources We Referenced:

For more context on my interview series in general, click here.