We saw the rise of smart phones as a huge opportunity for disruptive changes in existing computing paradigms, and have started doing research in mobile and social computing in 2008, as a part of the NSF Expedition Programmable Open Mobile Internet (POMI 2020). Results from this work have attracted industry interest and the MobiSocial Computing Laboratory, an industrial affiliates program, was formally launched in April 2011.

The mobile is the fourth of the world's major computer revolutions. The transition from mainframes to PCs gave individuals an unprecedented amount of computing power at their disposal and has led to the automation of offices and more. Cloud technologies shift computing back to centralized services, giving individuals access to their data from anywhere. The resulting Big Data phenomenon has had significant impact on the market as well as personal privacy. With mobile, control will swing back to the individuals as the aggregated power and communication bandwidth of billions of smart phones will surpass any centralized cloud service. The phones are more available than just the cloud, as they can operate offline. Moreover, the phones have a full record of the individual's digital life. All this translates to huge opportunities for paradigm shifts.

ThingEngine is our new research project (starting 2015) in the area of Internet of Things. ThingEngine is an open source implementation of a distributed IoT control hub and personal data store. The main goal of this project is to design an IoT system that gives users ownership over their own data; also our system aims to provide user-friendly interface that helps make use of one's own data. To this extent, we are designed as a distributed system and are able to run on a variety of devices, including shared cloud services, private cloud servers, private home servers such as the Raspberry Pi and even mobile phones, allowing the user the flexibility of choosing the storage solution he prefers.

Access control is also at the core of ThingEngine, making it possible by design to share the data with multiple parties such as doctors and health institution, in a manner as seamless as possible, but also retaining the revocation privilege. All data is grouped by access control, and all parties can subscribe to changes only to the data they have access to at any given time.

Additionally, a goal of ThingEngine is to be programmable by educated people without a computer science background (such as doctors and care givers), such that the programming logic can be distributed using a crowdsourcing platform (called the ThingPedia) to all endpoints running the engine. To this extent, we're designing a declarative domain specific language, with an intuitive syntax but also a powerful set of semantics that would cover most, if not all, the use cases of IoT control hubs.

We also don't want to sacrifice the ability to do rich static analysis and automated code generation, with the ultimate goal of automatically suggesting the most useful programming based on observed behavior pattern, as well as being able to infer the desired pattern from the shared collection based on natural language analysis, using the Sabrina chat interface.

SociaLite is a high-level query language for large-scale graph analysis. SociaLite is based on Datalog, and extended theoretically as well as practically to make large-scale graph analysis possible. For example, SociaLite is extended to support aggregate functions inside recursive queries as long as they are meet operators; the functions can prune out unnecessary computations for faster convergence. Also, its tail-nested tables can compactly store graphs for faster data access. With the two optimizations, SociaLite is more than 30 times faster than the state-of-the-art Datalog engines including LogicBlox, a commercial Datalog system, and as fast as highly optimized Java programs. Moreover, its location operator makes it easy to efficiently partition tables on cluster of machines, and apply distributed join operations. When we compare SociaLite with other distributed frameworks for shortest paths algorithm, SociaLite is more than two orders of magnitude faster than Hadoop and Haloop, and an order of magnitude faster than Hama and Giraph [2]. When we compare with Giraph, SociaLite programs are 4 to 12 times faster for six core graph algorithms including PageRank and Connected Components; yet SociaLite programs are 22 times more succinct than Giraph programs.

With Intel research lab, we compared state-of-the-art distributed graph frameworks including GraphLab, Giraph, and Combinatorial Blas, and we demonstrate that the performance of SociaLite is very competitive across different benchmark programs. On one benchmark, Triangle, SociaLite is the fastest among the four frameworks; for the rest benchmark programs (BFS, PageRank, and Collaborative Filtering) SociaLite is second in the performance, next to Combinatorial BLAS.

This project is partly supported by AWS Research Grants.

Musubi attempts to create a social mobile INTERNET where users can have a rich and carefree social sharing experience with any group of friends, with the freedom to choose their own cloud storage provider and apps on their mobile devices. This open architecture can disrupt the lock-in seen in existing social INTRANETS which imposes rigid control over both the users and the developers.

The social network infrastructure consists of a set of core secure encrypted messaging services. Data are decrypted on users' phones and can be backed up to PCs or cloud services of the user's choice. The Musubi social platform supports a new class of applications: peer-to-peer applications, centralized applications with identity protection, peer-nominated proximity applications, leverage of local devices, and personal analytics.

• This research has led to the spinoff of a startup called MobiSocial Inc. which has produced an iPhone app called OMlet. OMlet stands for Open Messaging with applets. You can download it from here.
  
  
• The Musubi open-source code is used as the underlying technology of Dispatch. (See below).
  
  
• Musubi is used in the high-school summer research program Migo that teaches kids the excitement of software inventions.
  
  
• Grandma's Trunk, a cross-generational collaborative game, with Stanford School of Education.

Corktastic is software that is designed to run on mobile devices and large displays that are typically situated in public places. The software converts a large display into a digital corkboard on which people can post messages and images by using their mobile device. A person uses their mobile device to text a message to the display. The message then appears on the display in the form of a “Post-it” note. Images can also be emailed to the board and appear as Polaroid pictures. Additionally, different types of multimedia such as videos and posters can be added to the board.

Along with the gathering and sharing information in a specific location, Corktastic can be used to gather information from the Internet that is relevant to the users to keep them aware of local events. For example, there are applications built for the Corktastic that will display relevant tweets on the board depending on the context of the setting. There is also an application that gives local weather information, for which the board can automatically suggest clothing options.

Moreover, Corktastic is an application platform that can have other third party applications run on it. Some of the other applications that have been built are a refrigerator magnet poetry game that allows people to use their mobile devices to move magnets around on the display. There is also a photo booth application that uses a camera attached to the display to take pictures. The pictures can then either be shared through email or sent to a mobile device.

We are continuing to bridge the connection between applications on the display and the mobile device. For example, just as people can add information to the screen using text or email, we are adding functionality for people to move information from the display to their mobile device. For example, if a user sees an event on the screen that they would like to attend, that event could be added to the calendar on their mobile device. Additionally, a person could walk up to the display in a hotel lobby and choose from a list of events that are currently happening. They could then transfer a mini application from the screen to their mobile device that would direct them to the event.

Corktastic is enabled by three current trends in computer hardware. Firstly, the decrease in price and increase in size of flat panel displays is a trend that enables displays to frequently appear in public spaces and in new buildings. Secondly, the trend of smart mobile devices becoming increasing ubiquitous and tied to users' preferences allows for increasing modes of interactions and personalization with the display. Thirdly, new small form factor computers are being developed which use the same chipsets as mobile phones but do not have the screen or 3G connection. With Corktastic, these computers can be made to transform a passive display into an active piece of communal computational infrastructure. Thus, the implementation of Corktastic binds these three trends together. By turning public displays into a resource that can be personalized to the user, we envision an ecosystem of applications that tie together public displays and mobile devices.

Social media has played a significant role in the Arab Spring movement that has toppled oppressive regimes in many countries. Regimes under attack often responds with crackdowns on protesters and shutting down the internet to disable social media. Dispatch is a mobile app that allows users to publish instantly, to Tumblr for example, authenticated information based on an anonymous identity. We will also make it possible for Dispatch messages be passed around person-to-person, in case the internet is not available from a locale.

Many journalists, let alone citizens, are not aware of the danger of publishing with their real identities. This project works closely with journalists to get the word out and to use Dispatch in real-life scenarios.

Dispatch is a joint project with the School of Journalism and the Computer Science Department at Columbia University and Tumblr. It was awarded a Magic Grant from the Brown Institute.

• Dispatch was used in a trial for reporting on the US election, November 2011. You can view the results at here.
• Dispatch has been released on the iPhone app store! You can download it from here.
  Dispatch is built on top of the open-source Musubi software.

Much of our lives is captured in online communication and digital transactions. Our passively acquired digital life-logs capture interesting stories and facts about ourselves. Who were our forgotten friends in high school or college? What are the significant people, places and things in our lives? When were we happy, sad, angry or in love? What happened in our lives in the year 1999?

We are particularly interested in solutions that respect privacy, e.g. by processing information on our own devices, so users can be comfortable to use all their data from different sources.

muse

Muse (Memories Using Email) is a program that helps users muse over long-term email archives. It mines email to help the user to reminisce about the past. It automatically derives the user's social topology based on email patterns and lets user browse and further edit groups in the topology.

Click here to try out Muse on your own email archives.
Muse is reviewed by New Scientist.
Muse is being commercialized by Stanford Libraries to give readers access to email archives of eminent individuals. Click here to see an early demonstration.

slant: personal search engine

Why get served thousands of results from unknown and untrusted websites when you search the web? Instead, create custom search engines that index only websites mentioned in social chatter (e.g. email and tweets we read). The search engine knows what's on our mind and can return results with very little typing. Just type in 243, and you may get the home page of the CS243 course you are taking currently. Our user study suggests that the results of just thousands of web pages can return different but equally rated results than the billions indexed by generic search engines. Slant respects privacy by running on behalf of the end user and only submits a list of preferred domains to a Google custom search engine.

Click here to try out Slant.

personalized browser

Our personal browser reads pages we visit and highlights all the terms that are meaningful to us based on the names mentioned in our email archives. This helps us read dense pages faster and is useful to tackle the constant information overload we face. We may also be serendipitously reminded of people we have forgotten; simply click on the highlighted term to get transported to the exact conversation involving the individual of interest.

Click here to try out our browser extension that annotates your web pages with connections to your email archives indexed by Muse. You can also try out Bookify, our new project that reads multiple web pages and lets you scroll through them smoothly. If Muse is running, Bookify will personalize the experience, introducing highlights and reordering pages according to relevance.

bspoke: personalized news

Bspoke is a project that builds an online profile of a user at their end, and uses it for news personalization. The profile is gathered automatically from online activities such as Email, Facebook, PC Documents, and Browsing history. This profile is private to the user, portable and transparent. It is used to automatically identify personalized news by an agent that monitors hundreds of news sources and applies filters that surface only the most relevant articles based on the profile.

Click here to try out Bspoke.

Personalized Memory Testing for Names

Personalized Memory Testing for names is a novel research approach to testing human memory. Using text analysis techniques, our system automatically generates fill-in-the-blank questions a user's email archive; the answers to these questions are names that appear frequently in the archive.

Click here for more information.

groupgenie--discover your social groups without tears

By analyzing our tagged photos and email correspondences, we can deduce and discover our circles of friends, including important social subgroups within larger groups of friends. This presents a much richer, nuanced view of our social landscape, which is missing from today’s plain, old view of our flat social graph. We have developed an algorithm that derives our social topology from our personal data, and a publicly available system called GroupGenie, that enables users to deduce, browse, edit and save their social topologies. Eliminating the tedium of group creation encourages more private sharing, and helps users make sense of their ever-growing social graph of friends.

GroupGenie is publicly available as a Facebook application, try it out here.
Our project, previously known as SocialFlows, was reported on the front pages of MIT Technology Review Today's Stories.

We view the phone as an extension of ourselves--we can wield our digital identity and personality to interact with people we meet and things we see directly. We carry our favorite bookmarks, photo, games, and share them with people we meet. We can also connect different devices together for activities, such as playing music on a friend's jukebox or sharing youtube on a big-screen TV with a tap using NFC (near-field communication) technology. It is important that we can interact socially with the assistance of our phone without requiring any prior arrangement such as signing up to the same social website, nor do we wish all our activities be monitored by a big-brother portal.

We coin the term partyware to refer to the class of social software that assists us in our real-world social encounters. Junction is an infrastructure designed to support partyware. On the Junction platform, partyware run on end-point devices, with the help of a generic rendezvous service in the network, thus enhancing privacy as well as scalability. We believe this design will encourage the creation of more multi-party software. The conventional server-client model used in multi-party software is a barrier to entry--many would-be application developers do not have the ability to write and host scalable services. We have created a large number of applications using Junction including multi-party games, collaborate media sharing, and collaborative learning applications for under-served children.

For more information: read about our NFC demos in an Engadget article.
Junction is publicly available and its documentation is available here.
Junction is used as the underlying platform in SMILE, the Stanford Mobile Inquiry-Based Learning Environment.

Currently, friends wishing to participate in social networking must join the same proprietary social network. We believe proprietary social networks will give way to open, federated social networking systems that are supported by a variety of vendors. Competition made possible by openness will offer consumers more choice and better services.

Our approach is to leverage email, allowing anybody with an email address to participate in social networking. Why email? Email is more pervasive than any social network; it is an open, federated platform that lets consumers choose their providers, including hosting their own if they so wish. Mr. Privacy keeps the communication in users' email. It provides an API that allows any application developer to define the data structures, which are automatically saved in distributed email repositories. Developers need not provide a central server; this requires significantly less effort and provides consumer with privacy automatically. We have validated the concept with SocialBar, an extension to Firefox for social browsing, and a GPS sharing application for both Android and iPhone.

The project is reviewed in an MIT Technology Review blogpost.
You can download SocialBar here.

Especially because of the mobile phone, there is a digital record of just about everything we do these days: our entire GPS traces, photos, videos, events on our calendar, emails, phone records, credit card histories, music and movies played. We refer to this body of knowledge as our personal cloud. We imagine that everybody will have a safe haven that enables one to store all this information in one place without hesitation. Automatic or semi-automatic techniques help us control access to our personal cloud. Not only can we access our own data, we can also tap into what our friends allow us to see.

Controlled sharing of possibly large amounts of personal data is supported by our Personal-Cloud Butler platform. The Personal-Cloud Butler service can be hosted at home on existing consumer products such as set-top boxes, game consoles, and broadband gateways. The Butler works in concert with mobile devices. Mobile devices collect data, which are then backed up to the Butler, they also provide users quick access to the data while on the road. Our Personal-Cloud Butlers implement the decentralized and standard OpenID protocols, support search of all data with an semantic index, and provide a high-level query language that hides the complexities of authentication, communication, and distribution from application developers.

Faculty	Students
Monica S. Lam (Faculty Director) Michael Bernstein Dan Boneh Paul Kim Jure Leskovec Nick McKeown Roy Pea	Giovanni Campagna Hristo Bojinov Jesse Cirimele Michael Fischer Joy Kim	Nicolas Kokkalis Diana MacLean Jiwon Seo Arvind Satyanarayan

Lab Personnel Sudheendra Hangal (Consultant) (Program Manager)

Previous Members Jeff Heer Scott Klemmer Ian Vo T.J. Purtell Ben Dodson Te-Yuan Huang Kanak Biscuitwala Chris Brigham Chanh Nguyen Aemon Cannon Ruven Chu Alex Favaro Steve Fan Bobby Georgescu

Abhinay Nagpal Matthew Nasielski Andreas Nomikos Neil Patel Seok-Won Seong Debangsu Sengupta Seng Keat Teh Kazuya Yokoyama, Sony Hiroaki Kameyama, Fujitsu YongQiang Liu, NEC Kazumine Matoba, Fujitsu KwangYong Lee, Samsung Sangho Yi, Samsung Munjo Kim, Samsung

Papers

• ThingTalk: A Distributed Language for a Social Internet of Things
  Giovanni Campagna, Jiwon Seo, Michael Fischer and Monica S. Lam
  Work in progress
  
  
• Historical Research Using Email Archives
  Sudheendra Hangal, Vihari Piratla, Chaiyasit Manovit, Peter Chan,
  Glynn Edwards, Monica S. Lam
  In CHI-2015 Case Studies: ACM Computer Human Interaction,
  Seoul, Korea, April 2015.
  
  
• Improving Communication in a Dorm with Interactive Public Displays
  Michael H. Fischer and Monica S. Lam
  In Information Technology and City Life Workshop,
  In conjunction with the 18th ACM CSCW,
  Vancouver, March 2015.
  
  
• Effect Of Phonemic Cuing On Recall Of Personally Relevant Names Derived From Email
  Allyson C. Rosen, Ankit Mathur, Monica S. Lam, Sudheendra Hangal
  Poster at the 2015 International Neuropsychological Society Annual Meeting,
  Denver, CO, February 2015.
  
  
• SociaLite: An Efficient Graph Query Language Based on Datalog
  Jiwon Seo, Stephen Guo, and Monica S. Lam
  In IEEE Transactions on Knowledge and Data Engineering, February 2015.
  
  
• Personalized Memory Testing for Names Using Email Archives
  Sudheendra Hangal, Allyson C. Rosen, Ankit Mathur, Monica S. Lam
  In BrainKDD: International Workhop on Data Mining for Brain Science,
  in conjunction with ACM SIGKDD'14,
  New York City, August 2014.
  
  
• Distributed SociaLite: A Datalog-based Language for Large-Scale Graph Analysis
  Jiwon Seo, Jongsoo Park, Jaeho Shin, and Monica S. Lam
  In Proceedings of the 39th International Conference on Very Large Data Bases,
  Hangzhou, China, September 2014.
  
  
Navigating the Maze of Graph Analytics Frameworks using Massive Graph Datasets
Nadathur Satish, Narayanan Sundaram, Mostofa Patwary, Jiwon Seo, Jongsoo Park, Muhammad Hassaan, Shubho Sengupta, Zhaoming Yin, Pradeep Dubey
In Proceedings of the ACM SIGMOD International Conference on Management of Data,
Snowbird, Utah, USA, June 2014.


• Integrating Technology and Pedagogy for Inquiry Based Learning: The Stanford Mobile Inquiry-based Learning Environment (SMILE)
  Buckner, E. and Kim, P.
  UNESCO Prospects. 10.1007/s11125-013-9269-7. (2013)
  


• SociaLite: Datalog Extensions for Efficient Social Network Analysis
  Jiwon Seo, Stephen Guo, and Monica S. Lam
  In Proceedings of the 29th IEEE International Conference on Data Engineering,
  Brisbane, Australia, April 2013.
  
  
• Reshaping Reminiscence, Web Browsing and Web Search Using Personal Digital Archives
  Sudheendra Hangal
  Ph.D. thesis, Stanford University. Dec. 2012.
  
  
• Processing Email Archives in Special Collections
  Sudheendra Hangal, Peter Chan, Monica S. Lam, and Jeffrey Heer
  In Proceedings of the Digital Humanities Conference (DH2012),
  Hamburg, Germany, July 2012.
  
  
• Who Killed My Battery: Analyzing Mobile Browser Energy Consumption
  Narendran Thiagarajan, Guarav Aggarwal, Angela Nicoara, Dan Boneh, and Jatinder Pal Singh
  In Proceedings of the 21st International WWW Conference (WWW2012)
  Lyon, France, April 2012. (Best Student Paper).
  
  
• Musubi: Disintermediated Interactive Social Feeds for Mobile Devices
  Ben Dodson, Ian Vo, T. J. Purtell, Aemon Cannon, and Monica S. Lam
  In Proceedings of the 21st International WWW Conference (WWW2012)
  Lyon, France, April 2012. (Finalist for Best Student Paper).
  
  
• A Mobile Social Network on ESP: an Egocentric Social Platform
  T. J. Purtell, Ian Vo, and Monica S. Lam
  February 2012.
  
  
• Effective Browsing and Serendipitous Discovery with an Experience-Infused Browser
  Sudheendra Hangal, Abhinay Nagpal, and Monica S. Lam
  In Proceedings of the 2012 International Conference on Intelligent User Interfaces (IUI)
  Lisbon, Portugal, February 2012.
  
  
• Friends, Romans, Countrymen: Lend me your URLs.
  Using Social Chatter to Personalize Web Search.
  Abhinay Nagpal, Sudheendra Hangal, Rifat Reza Joyee, and Monica S. Lam
  In Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW)
  Seattle WA, February 2012.
  
  
• MUSE: Reviving Memories Using Email Archives
  Sudheendra Hangal, Monica S. Lam, and Jeffrey Heer
  In Proceedings of the 24th ACM Symposium on User Interface Software and Technology (UIST)
  Santa Barbara CA, October 2011.
  
  
• Micro-Interactions with NFC-Enabled Mobile Phones
  Ben Dodson and Monica S. Lam
  In Proceedings of the Third International Conference on Mobile Computing, Applications, and Services (MobiCASE)
  Los Angeles, CA, October 2011.
  
  
• An Algorithm and Analysis of Social Topologies from Email and Photo Tags
  T. J. Purtell, Diana MacLean, Seng Keat Teh, Sudheendra Hangal, Monica S. Lam, and Jeffrey Heer
  In Proceedings of the Fifth ACM Workshop on Social Network Mining and Analysis
  Held in conjunction with the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)
  San Diego, CA, August 2011.
  
  
• Email Clients as Decentralized Social Apps in Mr. Privacy
  Michael Fischer, T. J. Purtell, and Monica S. Lam
  In Proceedings of the 4th Hot Topics in Privacy Enhancing Technologies (HotPETs 2011)
  Waterloo ON, Canada, July 2011.
  
  
• OpenConflict: Preventing Real Time Map Hacks in Online Games
  E. Bursztein, M. Hamburg, J. Lagarenne, and D. Boneh
  In Proceedings of the 32rd IEEE Symposium on Security and Privacy
  Oakland CA, May 2011.
  (Best student paper award).
  
  
• Sentiment Analysis on Personal Email Archives
  Sudheendra Hangal and Monica S. Lam
  In Proceedings of the CHI 2011 Workshop--Personal Informatics & HCI: Design, Theory, & Social Implications.
  Held in conjunction with CHI 2011.
  Vancouver B. C., Canada May 2011.
  
  
• The Junction Protocol for Ad Hoc Peer-to-Peer Mobile Applications
  Ben Dodson, Aemon Cannon, Te-Yuan Huang, and Monica S. Lam
  April 2011.
  
  
• Groups Without Tears: Mining Social Topologies from Email
  Diana MacLean, Sudheendra Hangal, Seng Keat Teh, Monica S. Lam, and Jeffrey Heer
  In Proceedings of the 2011 International Conference on Intelligent User Interfaces (IUI)
  Palo Alto, CA, February 2011.
  
  
• Location privacy via private proximity testing
  A. Narayanan, N. Thiagarajan, M. Lakhani, M. Hamburg, and D. Boneh
  In Proceedings of the 18th Annual Network and Distributed System (NDSS)
  San Diego, CA, February 2011.
  (Distinguished paper award)
  
  
• Touch and Run with Near Field Communication (NFC)
  Ben Dodson, Hristo Bojinov, Monica S. Lam
  October 2010.
  
  
• Secure, Consumer-Friendly Web Authentication and Payments with a Phone
  Ben Dodson, Debangsu Sengupta, Dan Boneh, and Monica S. Lam
  In Proceedings of the Second International Conference on Mobile Computing, Applications, and Services (MobiCASE)
  Santa Clara, CA, October 2010.
  
  
• PhoneNet: a Phone-to-Phone Network for Group Communication in a LAN
  Te-Yuan Huang, Kok-Kiong Yap, Ben Dodson, Monica S. Lam, and Nick McKeown
  In Proceedings of the Second ACM SIGCOMM Workshop on Networking, Systems, and Applications on Mobile Handhelds
  Held in conjunction with SIGCOMM 2010
  New Delhi, India, August 2010.
  
  
• Towards Software-Friendly Networks
  Kok-Kiong Yap, Te-Yuan Huang, Ben Dodson, Monica S. Lam, and Nick McKeown
  In Proceedings of the 1st ACM Asia-Pacific Workshop on Systems (APSys 2010)
  Held in conjunction with SIGCOMM 2010
  New Delhi, India, August 2010.
  
  
• All Friends are Not Equal: Using Weights in Social Graphs to Improve Search
  Sudheendra Hangal, Diana MacLean, Monica S. Lam, and Jeffrey Heer
  In Proceedings of the Fourth ACM Workshop on Social Network Mining and Analysis
  Held in conjunction with ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)
  Washington DC, July 2010.
  
  
• PrPl: a Decentralized Social Networking Infrastructure
  Seok-Won Seong, Jiwon Seo, Matthew Nasielski, Debangsu Sengupta, Sudheendra Hangal, Seng Keat Teh, Ruven Chu, Ben Dodson, and Monica S. Lam
  In Proceedings of the 1st International Workshop on Mobile Cloud Computing & Services: Social Networks and Beyond
  (Invited Paper)
  Held in conjunction with Mobisys 2010
  San Francisco, June 2010.
  
  
• Life-Browsing with a Lifetime of Email
  Sudheendra Hangal and Monica S. Lam
  In Proceedings of the CHI 2010 Workshop--Know Thyself: Monitoring and Reflecting on Facets of One's Life
  Held in conjunction with CHI 2010 Atlanta GA, April 2010.
  
  
• InvisiType: Object-Oriented Security Policies
  Jiwon Seo and Monica S. Lam
  In Proceedings of the 17th Annual Network and Distributed System Security Symposium,
  San Diego, February 2010.
  
  

Demonstrations

• SocialFlows: A System for Mining Social Topologies from Ego-centric Social Networks
  Diana MacLean, Sudheendra Hangal, Seng Keat Teh, Monica S. Lam, and Jeffrey Heer
  In the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  Washington DC, July 2010.
  
  
• Dunbar: Mining Email Archives for Reviving Memories
  Sudheendra Hangal and Monica S. Lam
  In the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  Washington DC, July 2010.