All posts filed under “conferences

Predict Conference – Great Analytics Starts with Great Foundations

Predict is an analytics conference that took place in Dublin’s RDS in October 2016. Its mission was to:

mobilise an international community to solve important human challenges through the power of data and predictive analytics.

The theme of this year’s event was the Journey from Data to Predictive Analytics.

It was my first time to attend and present at the conference and I wasn’t disappointed! I gave a talk on what it means to deliver great analytics and shared the 4 key areas that my team and I in Intercom have been focusing on to build a strong analytics team. Specifically:

  1. Foster an open feedback culture
  2. Develop close partnerships
  3. Use a common language
  4. Educate

RecSys 2016 – Highlights

This year’s RecSys was jam packed and fantastic. The dual track 3-day conference took place in beautiful MIT in Boston and showcased lots of great talks around advances in recommendation system algorithms and approaches.  Below are some of my highlights from the conference.  Full proceedings are available here

#1 Awesome Industry Track

I co-chaired the industry track along with Paul Lamere, Director of Developer Platform at Echonest / Spotify and Hrishi Aradhye, Engineering Director at Google. This involved selecting and curating a set of industry track talks / speakers from a diverse range of companies who actively work in the recommender systems space.  The industry track resulted in a set of 15 talks across 3 sessions featuring speakers from Mendeley, Meetup, Bloomberg, Foursquare, Spotify, Netflix, Pandora, Stitch Fix, Expedia, Nara Logics, GraphSQL, Retail Rocket, Quora, Google and Pinterest. Here’s just some of the awesome industry track talks that were presented.

#2 Record Attendance at Women’s Lunch!

I co-organized a women’s lunch with Tao Ye, Principal Scientist at Pandora. We had a record number of women attend (almost 50). The lunch resulted in a range of action items for next year’s conference including (hopefully) the organization of day care and a listing of female speakers so that future organizers can choose from a set of talented female researchers and practitioners who want to speak at conferences.


#3 Combining Machine Learning with Human Curation

A prominent theme at this year’s RecSys is the combination of machine learning techniques with large-scale human curation to improve recommendations. Stitch Fix, a clothing delivery service where customers get their own personalized selected of five clothing items called a “Fix”, gave a great talk on this topic. Stitch fix employ over 3000 stylists across the globe! They have a large algorithms team who build recommendation algorithms to help the stylists choose what to send to customers. Customers keep only what they like and send back the rest so it’s important that the recommendations are good! Katherine Levins, a data scientist from Stitch Fix talked about how they approach understanding, measuring and optimizing the role of human selection in a recommendation system. It turns out that they employ a combination of cognitive research, eyetracking, and machine learning models to tune the behavior of stylists. As data related initiatives like merlin take shape in Intercom, it feels like this combination of algorithm and human curation is something we could learn from and try going forward. Katherine’s talk is available here. Earlier this year Katherine published a great related blog post.

#4 Deep Learning

There were lots of talks around deep learning at this year’s RecSys, with several papers accepted accepted to the main conference track and an entire workshop dedicated to deep learning for recommender systems. Paul Convington presented a really interesting talk on deep neural networks for YouTube recommendations. The problem he’s working on is how to predict what movie a user will want to watch next. He discussed how they’ve implemented an age feature designed to remove the bias towards recommending movies / videos from the past. What was most intriguing is that despite the promise of deep learning to advance the field of recommendation, he said that they still have to do lots of feature engineering in YouTube. And overall they have found that user’s interactions with similar items are the best features for improving recommendation.

#5 The Explainability Spectrum & Signal Decay

Shashi Thakur, a Distinguished Engineer and head of the Google Now team gave an interesting keynote on personalization, recommendation and exploration in Google Now. Shashi talked about the importance of setting the right expectations for users and explaining why recommendations are being made at a given point in time. He talked about the explainability spectrum where on one end a recommendation is so clear that it doesn’t require any explanation, and on the other end the recommendation is higher risk / less clear and so needs a clear, concrete explanation. Depending on the circumstances surrounding the recommendation and the person for whom the recommendation is being made, the spectrum of explainability will shift in one direction or the other. I thought this was interesting to consider in the context of merlin and how we surface merlin’s recommendations.

Another interesting point raised across a few talks (including Google and Netflix) related to signal decay. The general advice is to revisit recommendation features often because signals that were once useful may not longer be as useful / as impactful as when the recommender system was first built.

MobileHCI 2016 – My Highlights

MobileHCI is a conference near and dear to my heart and one  I’ve been involved in for almost 10 years. I’ve been publishing and attending the conference yearly since 2007. I’ve also helped organize different tracks over the years — I gave an invited tutorial in 2012 in San Francisco and co-organized the interactive tutorials track in 2014 in Toronto. This year’s conference took place in beautiful Florence, Italy. And I was one of the conference program chairs alongside Prof Antonio Kruger from the German Research Center for AI (DFKI); Prof Jonna Hakkila from the Industrial Design at Faculty of Art and Design, University of Lapland; and Dr Marcos Serrano, from University of Toulouse.

Cheesy smiley photo overlooking the Ponte Vecchio taken by the lovely @aquigley

Cheesy smiley photo overlooking the Ponte Vecchio taken by the lovely @aquigley

I also took part in an invited panel on the Future of Mobile Interaction, Computing and Life. My fellow panelists included Daniel Ashbrook, Associate Professor in Rochester Institute of Technology; Anind Dey, Director of the HCI Institute in Carnegie Mellon University (CMU); Kori Inkpen, Principal Research at Microsoft; Lucia Terrenghi, UX Researcher and Designer at Google; and Kaisa Väänänen, Professor in the Human-Centered Technology Group at Tampere University of Technology. It was an amazing conference and while there is just too much to mention, what follow’s are just a few highlights from this year’s conference.

#1 All about Emoji!

There were 3 emoji related research papers which shed light on how and why people use emoji in their communications. Super interesting and fun! We’re looking into exploring similar patterns of emoji usage in business communication at Intercom so watch this space!

#2 The Future of Communication

Adrian's keynote on Everysense Everywhere Human Communication

Adrian’s keynote on Everysense Everywhere Human Communication

Adrian David Cheok gave a super opening keynote entitled Everysense Everywhere Human Communication. He talked about new types of communication environments which use all the senses, including touch, taste, and smell, to increase support for multi-person multi-modal interaction and remote presence.  Some of his quirky demo’s included:

  • A device that attaches to your mobile phone and enables you to feel (and give) a kiss remotely
  • A device that attaches to your mobile phone and emits a smell/scent instead of audio sounds to act as an alternative alarm clock. He demoed an actual use case — Oscar mayer, the bacon company in the US, have an alarm called called “wake up and smell the bacon”!! 
  • A device that enables taste signals to be transmitted virtually. This prototype “digital taste machine” was featured on BBC One’s Tomorrow’s Food and enables people to taste certain things like sweetness, sourness, etc.

While much of what Adrian presented is pretty out there, it opens up a bunch of questions about the future of personal and digital communication :)

#3 Handling Notifications

Demos, demos, demos!! Photo courtesy of @aquigley

Demos, demos, demos!! Photo courtesy of @aquigley

Notification management was a key theme in many talks. That is, understanding if/how the growing number of mobile notifications impact on people, how people attend to notifications, the cost of interrupting the user and methods for helping them manage inbound notifications they receive on their mobile phones and smartwatches. Research included:

In fact there was an entire workshop dedicated to the topic of notifications and attention management.

2016 Conference Org – Mobile HCI & RecSys

2016 looks set to be a busy year for conference organization with 2 super exciting announcements to make.

(1) I’m serving as paper co-chair for ACM Mobile HCI, a conference very near and dear to my heart. My fellow papers chairs are Jonna Hakkila from University of Lapland (Finland), Antonio Kruger from DFKI (Germany) and Marcos Serrano from University of Toulouse (France). Please check out the Mobile HCI 2016 website and get thinking about your paper submissions! Deadlines for paper submissions are 12th February 2016.

(2) I’m also serving as industry track co-chair for ACM RecSys 2016 alongside. My fellow chairs are Paul Lamere from Spotify and Hrishi Aradhye from Google. Our aim is to devise a super interesting industry line up so if (a) you work in industry and (b) your work involves “recommending things to people” why not consider submitting a proposal to the track?

Honorable Mention Award @ MobileHCI 2015: The Challenges of Mobile Phone Usage Data

A collaborative paper with Denzil Ferreira of University of Oulu, Nikola Banovic of Carnegie Mellon University and Kent Lyons a past colleague from Yahoo, in which we explore the challenges of mobile phone usage data through an analysis of three diverse smartphone application usage datasets, has been given an honorable mention award for the upcoming Mobile HCI 2015 conference in Denmark.

The goal of this work was to broaden our understanding of smartphone usage by investigating if differences in mobile device usage occurred not only across our three datasets, but also in relation to prior work. We provide an extensive review of prior work on related mobile data sets and mobile studies, present details of our comparative analysis focusing on top apps and micro-usage behaviors but most importantly we discuss the challenges and issues of conducting mobile research of this nature and reflect on caveats related to the replicability and generalizability of such work.

We’re delighted with the award / nomination!

Denzil worked on a beautiful visual table in our review of related work (see below). And you can read a pre-print of the paper here.


Presentation @ CHI2015: Understanding mobile search & app interactions

Last week JP Carrascal presented our study on the interactions between mobile search and mobile apps at CHI 2015 in Seoul, Korea. JP did a fantastic job presenting and handled the flurry of questions afterwards very well! In fact JP gave two talks in the same “Understanding Everyday Use of Mobile Phones” session chaired by Matt Jones!

The idea behind this work is to understand more about the behaviors and motivations around smartphone users transitioning between mobile search engines and mobile apps (and vice versa) when trying to find information to satisfy their daily information needs. We were also interested in exploring the various triggers and actions associated with mobile search. To shed some light on these mobile search and app interactions we designed and conducted a 2-week, mixed-method study involving 18 Android users in the Bay Area. The deck explains the core motivations, approach alongside key results. Questions or comments feel free to contact JP or I. And if interested in reading the full CHI 2015 paper it’s available here.