One of the projects I have been involved with recently was a collaboration with the Agents, Interaction, and Complexity group at University of Southampton. The same group who we are also involved with in the Orchid project. This particular project was on Measuring and Predicting Departures from Routine in Human Mobility, building on the PhD work by James McInerney (now at Princeton) and his paper Breaking the Habit.
It is well known that humans generally follow very regular and predicable mobility patterns, both spatially and temporally. Lots of work has looked at exploiting and predicting those patterns but much less so on looking specifically at departures from those regular patterns. What can we learn from those departures from routine? How predictable are they?
Update: Unfortunately I purposely withdrew from the DL meetup after a very unprofessional experience with the co-organisers Persontyle. I Instead I joined forces with the London Machine Learning Meetup.
It has been almost half a year since I announced I would take over the London Big-O Algorithms meetup and bring it back to life. 5 Months later I am very happy to say all has gone extremely well, interest and attendance far exceeding my expectations. We have had a great set of meetups so far and all speaker slots are booked until June with talks from Google, The founder of ZeroMQ, Microsoft Bing, and many others. Really nice to see there is strong interest in good, solid, technical content.
However, enough about Big-O. This post is to announce a new meetup group that I have been convinced into setting up. The Deep Learning London meetup. The aim of this group is to bring together people interested in the family of machine learning methods that are concerned with learning distributed, hierarchical (“deep”) representations. Neural Networks being the most popular implementation. Its an area I have been looking at for a while and will be getting into quite deeply over the next couple of months (no pun intended). The format will be based around guest speakers sharing new research ideas and applications covering a wide range of fields from computer vision and natural language processing to autonomous systems and prognostics.
Note we are not assuming deep learning is the be-all end-all silver bullet of machine learning and welcome critical thoughts and benchmarks.
Sound interesting? Get in touch!
Earlier this month a report was released entitled: A strategic vision for UK e-infrastructure: a roadmap for the development and use of advanced computing, data and networks.
The report was chaired by Professor Dominic Tildesley (a University of Southampton alumni by the way) and was commissioned by David Willetts, Minister for Universities and Science. It was triggered by a July 2011 meeting bringing together academics, industrialists, hardware and software suppliers and experts from the Research Councils to discuss the establishment of an e-infrastructure for the UK. The participants concluded at the end of the meeting:
.. we are experiencing a paradigm shift in which the scientific process and innovation are beginning in the virtual world of modelling and simulation before moving to the real world of the laboratory. [… and] that to exploit this revolution we would require a fresh, collaborative approach to software development to bring scientific, industrial and public sector users and hardware and software developers and vendors closer together.
Some months ago I attended the 2012 Collaborations workshop in Oxford, something which I blogged about in my post The Researcher Programmer, a New Species?.
This then triggered some discussion on the LinkedIn group for scientific software engineering, and that eventually led to a collaborative paper, presented at this weeks Digital Research Conference, also in Oxford.
I didn’t find a link to any kind of proceedings and in the interest of the discussion thought I would reproduce the paper here.
In my day job Im lucky and happy to be working on cool UAV technology for civilian applications, in particular our research focus is on search and rescue. While Im still not totally clear about what I want to do beyond my current contract I have always had an interest in helping to tackle humanitarian problems through engineering and technology (e.g., my recent RHOK event attendances). I was born in Burundi and grew up in various countries around East Africa. Experiences that have definitely left their mark and part of the reason I am writing this post.
Update: There has been some good discussion on this post at the LinkedIn group on Scientific Software Development and Management. See also the papers by Victoria Stodden and the great complmentary article by Ilian Todorov.
Update 2: There is now a Part 2 to this post: The research software engineer.
Last week I attended the 2012 Collaborations Workshop at Queen’s College in Oxford. Organized by the Software Sustainability Institute its goal was to bring together software developers and researchers and relect upon how both groups interact and if anything needs to be changed.
I only found out about the two day workshop and the existence of the SSI a few weeks before but immediately signed up. It was the first time I attended a conference so relevant to my own position and work. There were about 50 attendees, all in a similar position: PhD degree, working in academia or research lab, strong computational/software skills and working closely with researchers from at least one other scientific field (with a strong representation from biology/chemistry).
The conference went very smoothly, expertly managed and organized by Simon Hettrick and Neil Chue Hong. There were hardly any conventional talks, rather lightning talks and a whole series of break-out sessions which resulted in a lot of interesting discussions. One of the fundamental problems that kept coming up was the problem of defining ourselves as a group. What kind of species were we?
A few months ago an email was sent out to all researchers here at the university to solicit volunteers to give lectures/workshops for visiting secondary schools, the TEAtime lectures. As I always enjoy this kind of outreach I volunteered, went through some info sessions and did my lecture yesterday. Basically I gave an overview of UAV technology and did a simplified walk through of the aircraft design process. It was a bit ironic though, a computer scientist explaining airflow and aerodynamics :). No slides on slideshare as they’re too big to upload and Im to cheap to pay for PRO :).