Brief Biographies of the Twitter Course Instructors
8/23/2012 Marti Hearst/ Gilad Mishne Intro to course; Twitter basics
Marti Hearst is a Professor in the School of Information at UC Berkeley, with an affiliate appointment in the Computer Science Division. Her primary research interests are user interfaces for search engines, HCI and information visualization, natural language processing, and empirical analysis of social media. She wrote the first academic book on Search User Interfaces and is leading the Twitter-UC Berkeley course. Her PhD, MS, and BA are all from the CS department at UC Berkeley.
Gilad Mishne manages the Search Quality team at Twitter; previously, he worked on search at Yahoo. He holds a Ph.D from the University of Amsterdam.
Othman Laraki is Twitter’s Vice President for Growth, International and Revenue. Prior to Twitter, Othman cofounded MixerLabs (creator of GeoAPI), which got acquired by Twitter. Before that, he was at Google, where he led several products, including performance efforts, the Google Toolbar, Google Gears and early Firefox extensions.
Raffi Krikorian: At @twittereng, @raffi is the Director of the Platform Services group, the custodians of Twitter’s core logic and application infrastructure. Hiis teams manage, amongst other things, the business logic, scalable delivery, APIs, and the internal development model of all of Twitter. His group, from the @twittereng side, helped create the iOS 5 Twitter integration, the upcoming OS X Mountain Lion (10.8) integration, the “The X Factor” + Twitter voting mechanism, as well as rolling out SPDY support throughout Twitter. Previously, he was the lead of the public APIs as well as being the one of those behind Twitter’s Geospatial APIs. He is also the current chair of Twitter’s Architecture Group, which manages and looks after Twitter’s overall software architecture.
Before Twitter he used to create technologies to help people frame their personal energy consumption against global energy production (Wattzon – Business Week’s “Best Idea” 2008), and also ran a consulting company building off-the-wall projects. At one point, he used to teach at NYU’s ITP (created the class Every Bit You Make) and spent way too much time as a student at MIT and the MIT Media Lab.
Bill Graham is a Data Systems Engineer at Twitter. Before Twitter Bill was a Principal Engineer at CBS Interactive and CNET Networks and a Senior Software Engineer at Logitech, Inc. He contributes to a number of Hadoop-related projects including HBase, Hive and Avro and is an Apache Pig committer. Bill holds a BS and an MS in Civil Engineering from Lehigh University.
9/4/2012 Jonathan Coveney Intro to Pig
Jonathan Coveney is a Data Systems Engineer at Twitter. Before Twitter, Jon was a Senior Data Analyst at comScore, and an Investment Banker with Credit Suisse. He is an Apache Pig committer, and holds a BS in Business and in Computer Science from the University of Pennsylvania.
Rion Snow leads a team building relevance and discovery technologies at Twitter. Before joining Twitter, he pioneered award-winning research in natural language processing, machine learning, and human computation. Rion received his Ph.D in Computer Science from Stanford, his B.A. in Mathematics from UCSD, and has previously worked for numerous research labs and startups, including Google Research, Microsoft Research, and Powerset.
9/13/2012 Kostas Tsioutsiouliklis Trend detection in social data at Twitter
Kostas Tsioutsiouliklis is a Software Engineer in the Search & Relevance team at Twitter, working on trend detection. He has been with Twitter since mid-2011. Prior to that, he was a Research Engineer and Manager at Yahoo! Labs for 7 years, working mainly on Search Relevance. He holds a PhD from Princeton University.
Brian Larson is the tech lead of the Search & Relevance group at Twitter, where he works on overall architecture. Brian was also one of the authors of Earlybird, Twitter’s realtime search system. Previously, Brian spent 6 years at Google, working on shopping search
and ads quality. He holds an MS in CS from Stanford University.
Stephen Sorkin, Vice President of Engineering at Splunk, is responsible for the Splunk Enterprise and Free products. His team’s product gathers, processes, indexes, searches over, reports on and visualizes massive streams of machine-generated data. Before Splunk, Stephen was a research scientist at HP Labs in Palo Alto. Stephen has a BS in Computer Science from Stanford and a MS in Computer Science from UC Berkeley. He is the author of several peer-reviewed papers and patents.
Archana Ganapathi is a Research Engineer at Splunk, where she focuses on big data analytics. Before Splunk, she gained extensive experience in analyzing large production datasets and modeling system behavior at Microsoft as well as HP Labs. Archana received her PhD in Computer Science from UC Berkeley in 2009. Her research explored data-driven techniques for predicting and optimizing performance of parallel systems including decision support databases, multicore processors and MapReduce.
Aneesh is a software engineer in the Personalization and Recommender Systems group at Twitter. His is working on Twitter’s social graph computation infrastructure that powers a host of products in Twitter. Before joining Twitter, Aneesh received a Ph.D. from Stanford University where he was fortunate enough to be advised by Rajeev Motwani and Tim Roughgarden.
10/2/2012 Joey Gonzalez GraphLab
Joey Gonzalez is a postdoctoral researcher who completed his PhD student at CMU in August 2012 and is visiting UC Berkeley this year as a post doctoral researcher. His research addresses the challenges of designing and building large-scale machine learning algorithms and systems. In particular, my thesis work focuses on large-scale structured machine learning using probabilistic graphical models (Markov Random Fields) that are capable of reasoning about billions of related random variables. The resulting algorithms and systems have achieved state-of-the-art performance in tasks ranging from predicting ad preferences in social networks to solving complex protein modeling tasks. As part of my thesis work I created GraphLab (http://graphlab.org), a framework that dramatically simplifies the design and implementation of high-performance large-scale machine learning systems
Delip Rao (@deliprao) works for the Search and Relevance group at Twitter in San Francisco. His research interests are in Machine Learning and Natural Language Processing, and in particular, scalability of learning algorithms, graph-based methods, information extraction, and resource-poor languages. Prior to this he worked on his PhD with David Yarowsky at CLSP, Johns Hopkins University. His other industrial experience include Google Research (Mountain View), IBM Research Labs (New Delhi), Oracle, and Motorola.
10/9/2012 Alpa Jain Recommendation Algorithms at Twitter
Alpa works on monetization algorithms at Twitter. Prior to that, she was a scientist at Yahoo! Labs. She has an M.S. and PhD in Computer Science from Columbia University.
Kurt Thomas (http://inwyrd.com) is a computer science PhD candidate at the University of California, Berkeley. His research focuses on the abuse of social networks by criminals. Kurt’s recent projects include the development of a real-time framework for detecting spam and malicious URLs; mapping out the criminal infrastructure that supports Twitter spam; and investigating politically-motivated attacks on social networks. While at Berkeley, Kurt collaborates with Twitter’s spam and abuse team to develop new systems that protect Twitter’s users. Kurt is the recipient of the Facebook Graduate Student Fellowship and is advised by Vern Paxson.
Stan is an engineer in Search & Relevance at Twitter. He graduated from MIT in 2012 with S.B. and M.Eng. degrees in electrical engineering and computer science. Stan is interested in systems that are intelligent and systems with interesting structure or dynamics — and where these intersect. He has worked on AI for mobile autonomous robots, cortex-like learning algorithms, models of cellular self-organization, event detection in timeseries, intelligent crowdsourcing, and underactuated control of vehicle traffic. He impulse-buys way more books than he has time to read.
Matei Zaharia is a sixth-year PhD student at UC Berkeley, working with Scott Shenker and Ion Stoica on topics in systems, cloud computing and networking. He is also a committer on Apache Hadoop and Apache Mesos. Matei got his undergraduate degree at the University of Waterloo in Canada, and is currently supported by a Google PhD fellowship.
Oscar Boykin is data scientist on Twitter’s revenue engineering team. He is a co-author Scalding ( https://github.com/twitter/scalding), a library for large-scale Hadoop programming. Scalding offers standard functional programming abstractions for Hadoop and is the primary tool used by Twitter’s revenue data scientists. Prior to joining Twitter, Oscar was an assistant professor of electrical and computer engineering at the University of Florida.
Argyris Zymnis is working as a data scientist on Twitter’s revenue team. Prior to joining Twitter, Argyris was a co-founder of AdGrok, a Y Combinator funded startup in the online advertising space. He is a co-author of Scalding (https://github.com/twitter/scalding) and holds a PhD in EE from Stanford.