MIT Big Data Challenge

Over the course of the last two months myself and some of my lab mates participated in the first annual MIT Big Data Challenge put on by the BigData@CSAIL.  This year’s data consisted of geolocated taxi cab pickups and dropoffs

/ Comments Off on MIT Big Data Challenge

MIT Big Data Challenge

Over the course of the last two months myself and some of my lab mates participated in the first annual MIT Big Data Challenge put on by the BigData@CSAIL.  This year’s data consisted of geolocated taxi cab pickups and dropoffs

/ Comments Off on MIT Big Data Challenge

Boston Taxi Pickups in D3

  As part of a homework assignment for a class on data mining, I got to explore a dataset of taxicab pickups in Boston.  With 6 months of data and the geocoded locations of roughly 4.2 million cabs, our task

/ No comments

Boston Taxi Pickups in D3

  As part of a homework assignment for a class on data mining, I got to explore a dataset of taxicab pickups in Boston.  With 6 months of data and the geocoded locations of roughly 4.2 million cabs, our task

/ No comments

Making sense of Big Data

It’s weird to see your face floating on MIT homepage, but I’m honored that it was. “Every time you use your cellphone, there is a little breadcrumb that’s stored that can be used in a lot of different ways to

/ No comments

Making sense of Big Data

It’s weird to see your face floating on MIT homepage, but I’m honored that it was. “Every time you use your cellphone, there is a little breadcrumb that’s stored that can be used in a lot of different ways to

/ No comments

Good Morning 2012, Stockholm, Sweden

A huge “Thanks!” and “Congratulations!” to the Stockholm School of Entrepreneurship for putting on such an inspiring event!  I was honored to be a part of it.  I’d like to personally thank their support staff Marie Sundström, Anna Jakus, and

/ No comments

Good Morning 2012, Stockholm, Sweden

A huge “Thanks!” and “Congratulations!” to the Stockholm School of Entrepreneurship for putting on such an inspiring event!  I was honored to be a part of it.  I’d like to personally thank their support staff Marie Sundström, Anna Jakus, and

/ No comments

Visualizing Taxi Fares.

Note: This content of this post is also posted on the website of the Human Mobility and Networks Lab A couple of weeks ago I participated in an MIT Transportation Hack-a-thon. The idea of a hackathon is pretty simple. Put

/ No comments

Visualizing Taxi Fares.

Note: This content of this post is also posted on the website of the Human Mobility and Networks Lab A couple of weeks ago I participated in an MIT Transportation Hack-a-thon. The idea of a hackathon is pretty simple. Put

/ No comments

Inferring Land Use from Mobile Phone Activity

Abstract: Understanding the spatiotemporal distribution of people within a city is crucial to many planning applications. Obtaining data to create required knowledge, currently involves costly survey methods. At the same time ubiquitous mobile sensors from personal GPS devices to mobile phones

/ No comments

Inferring Land Use from Mobile Phone Activity

Abstract: Understanding the spatiotemporal distribution of people within a city is crucial to many planning applications. Obtaining data to create required knowledge, currently involves costly survey methods. At the same time ubiquitous mobile sensors from personal GPS devices to mobile phones

/ No comments

Predicting Cellular Automata

Abstract: We explore the ability of a locally informed individual agent to predict the future state of a cell in systems of varying degrees of complexity using Wolfram’s one-dimensional binary cellular automata. We then compare the agent’s performance to that of two small

/ No comments

Predicting Cellular Automata

Abstract: We explore the ability of a locally informed individual agent to predict the future state of a cell in systems of varying degrees of complexity using Wolfram’s one-dimensional binary cellular automata. We then compare the agent’s performance to that of two small

/ No comments

Modeling the Adoption of Innovations in the Presence of Geographic and Media Influences.

Abstract: While there is a large body of work examining the effects of social network structure on innovation adoption, models to date have lacked considerations of real geography or mass media. In this article, we show these features are crucial

/ No comments

Modeling the Adoption of Innovations in the Presence of Geographic and Media Influences.

Abstract: While there is a large body of work examining the effects of social network structure on innovation adoption, models to date have lacked considerations of real geography or mass media. In this article, we show these features are crucial

/ No comments

TEDxUofM

Well, the weekend finally came and passed. TEDxUofM 2011 went off as a smashing success in my book. Below are some of my random thoughts and experiences from what was a fantastic and inspiring weekend. First and foremost, let’s just

/ 3 Comments

TEDxUofM

Well, the weekend finally came and passed. TEDxUofM 2011 went off as a smashing success in my book. Below are some of my random thoughts and experiences from what was a fantastic and inspiring weekend. First and foremost, let’s just

/ 3 Comments

Spatiotemporal correlations in criminal offense records.

Abstract: With the increased availability of rich behavioral datasets, we present a novel application of tools to analyze this information. Using criminal offense records as an example, we employ cross-correlation measures, eigenvalue spectrum analysis, and results from random matrix theory to

/ No comments

Spatiotemporal correlations in criminal offense records.

Abstract: With the increased availability of rich behavioral datasets, we present a novel application of tools to analyze this information. Using criminal offense records as an example, we employ cross-correlation measures, eigenvalue spectrum analysis, and results from random matrix theory to

/ No comments