Thursday, May 10, 2012
Call for papers: EvoStar 2013
The paper submission deadline for EvoStar 2013 is 1 November, 2012. This conference will be held in Vienna, Austria, 3-5 April, 2013.
Wednesday, May 9, 2012
Deadline extension: UKCI 2012
The paper submission deadline for the 12th UK Annual Workshop on Computational Intelligence (UKCI) 2012 has been extended to May 31, 2012. This workshop will be held in Edinburgh, Scotland, UK, 5-7 September, 2012.
Wednesday, May 2, 2012
Reminder: conference paper deadline for NIPS 2012
A reminder that the deadline for submitting papers to Neural Information Processing Systems (NIPS) 2012 is 2 June 2012. This conference will be held at Lake Tahoe, Nevada, 3-6 December, 2012.
Tuesday, May 1, 2012
Reminder: submission deadline for ELM 2012
A reminder that the deadline for submitting papers to the International Symposium on Extreme Learning Machines (ELM) 2012 is 1 June, 2012. This symposium will be held in Singapore 11-13 December, 2012.
Thursday, April 26, 2012
There's no un-gameable metric
I've been a bit quiet on the blog front lately, mostly because I've been working like a dog on several projects, including writing tools for ecological modelling, re-working some websites, and fulfilling my duties both as guest editor of my special issue of Evolving Systems on Applications of Evolving Connectionist Systems, and as vice-chair of the IEEE CIS Social Media Subcommittee. It was also school holidays the last two weeks here in South Australia, and I was able to spend some quality time with my little girl.
Never fear, I'm working on several new blog posts on a variety of topics, including: the relationship between computational intelligence and data mining; further thoughts on doing a PhD (a follow-up to this post); my thoughts on the value of a computational intelligence degree; and my thoughts on collaborating with other researchers. The topic of today's post, though, is assessing academics and universities.
My alma mater has been in the New Zealand news lately (see here and here) after the release of a report by accounting firm KPMG that suggests that Otago had gamed the New Zealand government research assessment process to give themselves a higher score than they were entitled to.
The Performance-Based Research Funding (PBRF) framework rates the research outputs of eligible staff and uses those ratings, along with metrics of institutional performance such as number of research degrees completed, to assign an overall score to the institution. Staff can be rated as R (research inactive - bad for this exercise), C (research active / good), B (very good) or A (world-class). The fewer R's and C's an institution has, and the more B's and A's, the better the institution's score. Something like 25-30% of an institution's income will be determined by this score. There is also the huge marketing advantage of an institution scoring highly in relation to the other universities: in the first PBRF round in 2004, Auckland University made a lot of the fact that their staff were, on average, ranked highest in the country, while Otago made a lot of the fact that they were ranked highest as an institution. This is despite the government of the day clearly saying that PBRF wasn't supposed to be used for such comparisons, or as a management tool.
Eagle-eyed readers may have noticed the term "eligible staff" earlier in the previous paragraph: it is this facet of the process that Otago is accused of gaming.
The accusation is that Otago inappropriately classified staff it knew would get low scores as ineligible for assessment, and thus artificially boosted its ranking compared to other New Zealand institutions. Otago is also accused of firing, or pushing into retirement, staff based on their anticipated PBRF score. The vice-chancellor denies these accusations, and the whole thing is turning into a "he said / she said" situation.
Did Otago really do this? I honestly don't know. I do know that when I was working at Otago in 2004 (the first PBRF assessment round), I was assessed fully, and fairly, even though it would have been pretty easy to classify me as ineligible for assessment. I don't think my score in PBRF at the time was particularly helpful to their overall ranking, but maybe it wasn't too harmful, either. My point is, this entire drama shows that there is no metric of academic performance, of an individual, an institution, or a publication, that can't be gamed. That is, there is no metric that can't be manipulated so that an individual, institution or publication gets a higher score than they otherwise would. Journals can boost their impact factor by asking authors to cite articles from within that publication (and I have had editors ask me to do this). Individuals can boost their h-index by auto-citations, or by organising a special issue and asking every author to cite a review article they have written. Institutions can raise their assessment by head-hunting the top-performers in their fields, or by hiding staff from assessment. Some might argue that it is only prudent to game metrics whenever possible: after all, the future employment prospects of an academic, or the future financial security (and, therefore, job security of staff of) an institution depends on getting a good score on whatever metric is being used. As long as no rules are being broken, and the questions are being answered honestly, what's the harm? If there is wiggle-room, or room for gaming of the metric, isn't it the assessor's fault for designing an inexact metric? Others might argue that adherence to the spirit of the assessment is more important, more fair, and that gaming should be avoided.
This all means that there is no one metric you can use to assess an academic. You have to look at the entire picture: you have to look at their publication count; where they have published; what fields they have published in; how much teaching they have done; their teaching assessments; the quality of their institution; and their service to their institution(s), to professional societies, and to the community. I hope that one day I will rate highly in all of those areas, but for now, don't judge me just by my h-index alone.
Never fear, I'm working on several new blog posts on a variety of topics, including: the relationship between computational intelligence and data mining; further thoughts on doing a PhD (a follow-up to this post); my thoughts on the value of a computational intelligence degree; and my thoughts on collaborating with other researchers. The topic of today's post, though, is assessing academics and universities.
My alma mater has been in the New Zealand news lately (see here and here) after the release of a report by accounting firm KPMG that suggests that Otago had gamed the New Zealand government research assessment process to give themselves a higher score than they were entitled to.
The Performance-Based Research Funding (PBRF) framework rates the research outputs of eligible staff and uses those ratings, along with metrics of institutional performance such as number of research degrees completed, to assign an overall score to the institution. Staff can be rated as R (research inactive - bad for this exercise), C (research active / good), B (very good) or A (world-class). The fewer R's and C's an institution has, and the more B's and A's, the better the institution's score. Something like 25-30% of an institution's income will be determined by this score. There is also the huge marketing advantage of an institution scoring highly in relation to the other universities: in the first PBRF round in 2004, Auckland University made a lot of the fact that their staff were, on average, ranked highest in the country, while Otago made a lot of the fact that they were ranked highest as an institution. This is despite the government of the day clearly saying that PBRF wasn't supposed to be used for such comparisons, or as a management tool.
Eagle-eyed readers may have noticed the term "eligible staff" earlier in the previous paragraph: it is this facet of the process that Otago is accused of gaming.
The accusation is that Otago inappropriately classified staff it knew would get low scores as ineligible for assessment, and thus artificially boosted its ranking compared to other New Zealand institutions. Otago is also accused of firing, or pushing into retirement, staff based on their anticipated PBRF score. The vice-chancellor denies these accusations, and the whole thing is turning into a "he said / she said" situation.
Did Otago really do this? I honestly don't know. I do know that when I was working at Otago in 2004 (the first PBRF assessment round), I was assessed fully, and fairly, even though it would have been pretty easy to classify me as ineligible for assessment. I don't think my score in PBRF at the time was particularly helpful to their overall ranking, but maybe it wasn't too harmful, either. My point is, this entire drama shows that there is no metric of academic performance, of an individual, an institution, or a publication, that can't be gamed. That is, there is no metric that can't be manipulated so that an individual, institution or publication gets a higher score than they otherwise would. Journals can boost their impact factor by asking authors to cite articles from within that publication (and I have had editors ask me to do this). Individuals can boost their h-index by auto-citations, or by organising a special issue and asking every author to cite a review article they have written. Institutions can raise their assessment by head-hunting the top-performers in their fields, or by hiding staff from assessment. Some might argue that it is only prudent to game metrics whenever possible: after all, the future employment prospects of an academic, or the future financial security (and, therefore, job security of staff of) an institution depends on getting a good score on whatever metric is being used. As long as no rules are being broken, and the questions are being answered honestly, what's the harm? If there is wiggle-room, or room for gaming of the metric, isn't it the assessor's fault for designing an inexact metric? Others might argue that adherence to the spirit of the assessment is more important, more fair, and that gaming should be avoided.
This all means that there is no one metric you can use to assess an academic. You have to look at the entire picture: you have to look at their publication count; where they have published; what fields they have published in; how much teaching they have done; their teaching assessments; the quality of their institution; and their service to their institution(s), to professional societies, and to the community. I hope that one day I will rate highly in all of those areas, but for now, don't judge me just by my h-index alone.
Saturday, April 21, 2012
The future of universities
Or, why contract lecturers are probably a bad idea.
The last time I was job-hunting, I noticed a number of positions advertised as "sessional" or "contract" lecturers. These were positions where a person would present a few lectures a week for a certain course, for a fixed period of time, then leave the institution. In this article, the use of contract lecturers in American universities is described as a crisis, where quality of teaching is suffering and the highly-skilled educators end up severely under-paid. While administrators justify this as a way of cutting monetary costs, the educational costs are huge.
Firstly, contract lecturers are not available for struggling students. This is because they are seldom paid full-time, which makes it difficult to find time for out-of-class student consultation: people don't like to work for nothing.
Secondly, the fly-by-night nature of contract lecturers prevents them from forging bonds with cohorts of students: the students see them for one course, then never see them again. In other words, the contract lecturer has no motivation and little opportunity to see their students as anything other than faceless blobs that sit in the lectures absorbing information. This is not conducive to high-quality teaching.
This also makes it harder to recruit post-graduate students. I vividly remember the first time I was lectured by the man who would go on to be my PhD supervisor: I was a first-year undergraduate, sitting in a lecture theatre on a cold Dunedin evening, and he described a world of computational intelligence that I knew right then was a world I wanted to explore myself. I knew that if I worked hard in my first and second year courses, I would be able to do his third-year honours-track course, and if I did well in third-year, I could do his fourth-year honours course, and if I did well in that, I could do a PhD with him. If he had been a fly-by-night contract lecturer, would I have been as inspired? I probably would have skipped honours and gone into the workforce straight after third year. While that might have placed me in a slightly better financial position, my life would be much less rich than it is now.
While I don't have evidence for it, I suspect that contract lecturing does not overall attract the best teaching talent. Now, I'm not trying to denigrate contract lecturers, and I know several people who have worked as contract lecturers to support themselves while looking for post-docs, immediately after completing their PhDs. But as a highly-trained professional (which is what anyone with a PhD is) it is hard to justify taking a contract lecturer position if there are any other options available. I never even bothered applying for the contract lecturing positions I saw advertised, even though I was capable of doing them well, simply because it was not worth my while to shift myself and my family to do the job. If I were a single man, perhaps I could embrace the digital nomad lifestyle, and drift about doing contract lecturing here and there. But with a family to support, including a primary-school age daughter, it simply is not an option.
On the flip side, contract lecturing can provide a way for junior staff to get some experience lecturing. Also, technology is getting to the point where the lecturer no longer has to be in the same physical location as the class: the success of the Khan Academy and open courses (like the courses run by Sebastian Thrun) has shown that it is possible to have a class that is far away from the instructors. If the option to teach remotely were there, it might be easier to get top-talent as contract lecturers. I wouldn't mind being a contract lecturer if it meant I didn't have to relocate. That is, I wouldn't mind the job so much if I didn't have to move to do it. Of course, the alienation between lecturer and student that I discussed above could become even greater.
I think that the use of contract lecturers is probably going to increase, especially for first-year or general "service" courses, like for introductory programming or basic web development. But for more advanced under-graduate courses, or for post-graduate teaching, permanent staff are absolutely essential, due to the multi-year nature of post-graduate study. This also requires a level of specialisation that contract lecturers simply cannot develop: they are treated like interchangeable parts, which is no way to treat anyone, let alone someone who you expect to teach, and to inspire, students.
The last time I was job-hunting, I noticed a number of positions advertised as "sessional" or "contract" lecturers. These were positions where a person would present a few lectures a week for a certain course, for a fixed period of time, then leave the institution. In this article, the use of contract lecturers in American universities is described as a crisis, where quality of teaching is suffering and the highly-skilled educators end up severely under-paid. While administrators justify this as a way of cutting monetary costs, the educational costs are huge.
Firstly, contract lecturers are not available for struggling students. This is because they are seldom paid full-time, which makes it difficult to find time for out-of-class student consultation: people don't like to work for nothing.
Secondly, the fly-by-night nature of contract lecturers prevents them from forging bonds with cohorts of students: the students see them for one course, then never see them again. In other words, the contract lecturer has no motivation and little opportunity to see their students as anything other than faceless blobs that sit in the lectures absorbing information. This is not conducive to high-quality teaching.
This also makes it harder to recruit post-graduate students. I vividly remember the first time I was lectured by the man who would go on to be my PhD supervisor: I was a first-year undergraduate, sitting in a lecture theatre on a cold Dunedin evening, and he described a world of computational intelligence that I knew right then was a world I wanted to explore myself. I knew that if I worked hard in my first and second year courses, I would be able to do his third-year honours-track course, and if I did well in third-year, I could do his fourth-year honours course, and if I did well in that, I could do a PhD with him. If he had been a fly-by-night contract lecturer, would I have been as inspired? I probably would have skipped honours and gone into the workforce straight after third year. While that might have placed me in a slightly better financial position, my life would be much less rich than it is now.
While I don't have evidence for it, I suspect that contract lecturing does not overall attract the best teaching talent. Now, I'm not trying to denigrate contract lecturers, and I know several people who have worked as contract lecturers to support themselves while looking for post-docs, immediately after completing their PhDs. But as a highly-trained professional (which is what anyone with a PhD is) it is hard to justify taking a contract lecturer position if there are any other options available. I never even bothered applying for the contract lecturing positions I saw advertised, even though I was capable of doing them well, simply because it was not worth my while to shift myself and my family to do the job. If I were a single man, perhaps I could embrace the digital nomad lifestyle, and drift about doing contract lecturing here and there. But with a family to support, including a primary-school age daughter, it simply is not an option.
On the flip side, contract lecturing can provide a way for junior staff to get some experience lecturing. Also, technology is getting to the point where the lecturer no longer has to be in the same physical location as the class: the success of the Khan Academy and open courses (like the courses run by Sebastian Thrun) has shown that it is possible to have a class that is far away from the instructors. If the option to teach remotely were there, it might be easier to get top-talent as contract lecturers. I wouldn't mind being a contract lecturer if it meant I didn't have to relocate. That is, I wouldn't mind the job so much if I didn't have to move to do it. Of course, the alienation between lecturer and student that I discussed above could become even greater.
I think that the use of contract lecturers is probably going to increase, especially for first-year or general "service" courses, like for introductory programming or basic web development. But for more advanced under-graduate courses, or for post-graduate teaching, permanent staff are absolutely essential, due to the multi-year nature of post-graduate study. This also requires a level of specialisation that contract lecturers simply cannot develop: they are treated like interchangeable parts, which is no way to treat anyone, let alone someone who you expect to teach, and to inspire, students.
Thursday, April 19, 2012
Reminder: paper submission deadline for CIDU 2012
A reminder that the deadline for submitting papers to the 2012 Conference on Intelligent Data Understanding (CIDU) 2012 is 18 May 2012. This conference will be held in Boulder, Colorado, 24-26 October, 2012.
Wednesday, April 18, 2012
Special session: Computational Intelligence and Social Media
The below is a call for papers for a special session of the 2012 IEEE Workshop on Computational Intelligence for Security and Defence Applications (IEEE CISDA) 2012. The deadline for submitting papers for this special session is 23 April, 2012. This conference will be held in Ottawa, Canada, 11-13 July 2012.
Contact: john.verdon -at- drdc-rddc.gc.ca
Military and security communities are hard-pressed to develop the capabilities required to exploit the huge volumes of data, the new forms of information, and rapidly changing content of Social Media (SM) such as blogs, wikis, videos, social graph based systems (such as Facebook, Twitter) and many other SM systems that are being deployed. SM is also in its infancy, so there is a huge potential for SM to evolve far beyond its current capabilities and types of information.
Computational Intelligence techniques (Neural network, Evolutionary computation, Fuzzy Systems, Particle Swarms, etc) have often been based on, and and have been related to, highly complex, structured, and dynamic natural systems in [biology, neuroscience, brain, psychology, sociology]. This may make them particularly well suited for the extraction of intelligence from existing forms of SM, for the [modeling, prediction, control] of SM activity, as well as for providing some capability of keeping up with rapidly evolving and new forms of SM. Papers that deal with massive datasets are of particular interest, and, naturally, papers should relate to defense and security needs, applications, and tool-sets. Security & Defense needs and Social Media [some examples from Forrester 2011, Verdon 2012] topics include, but are not limited to:
Computational Intelligence and Social Media
Organizers: John Verdon, DRDC Ottawa, CanadaContact: john.verdon -at- drdc-rddc.gc.ca
Military and security communities are hard-pressed to develop the capabilities required to exploit the huge volumes of data, the new forms of information, and rapidly changing content of Social Media (SM) such as blogs, wikis, videos, social graph based systems (such as Facebook, Twitter) and many other SM systems that are being deployed. SM is also in its infancy, so there is a huge potential for SM to evolve far beyond its current capabilities and types of information.
Computational Intelligence techniques (Neural network, Evolutionary computation, Fuzzy Systems, Particle Swarms, etc) have often been based on, and and have been related to, highly complex, structured, and dynamic natural systems in [biology, neuroscience, brain, psychology, sociology]. This may make them particularly well suited for the extraction of intelligence from existing forms of SM, for the [modeling, prediction, control] of SM activity, as well as for providing some capability of keeping up with rapidly evolving and new forms of SM. Papers that deal with massive datasets are of particular interest, and, naturally, papers should relate to defense and security needs, applications, and tool-sets. Security & Defense needs and Social Media [some examples from Forrester 2011, Verdon 2012] topics include, but are not limited to:
- Language translation - filtering a collection of documents down to those that should be translated by humans
- Knowledge extraction - validating facts from unstructured and questionable sources
- Document summarization - extracting the sense of a document or a group of topically-related documents, and establishing the main points of consensus and divergence
- Trend identification - as well as possible causal linkages among trends and supporting evidence
- Active learning - determining where information is lacking and which data would be most productive to acquire
- Security - at what threshold does secrecy become a liability rather than an asset for security?
- Reputation and/or Recommendation - ‘quick trust’ of the participants and possibly of the information
Tuesday, April 17, 2012
Deadline extended: IEEE CISDA 2012
The deadline for papers submitted to the IEEE Workshop on Computational Intelligence for Security and Defence Applications (IEEE CISDA) 2012 has been extended to 23 April 2012. This workshop will be held in Ottawa, Canada, 11-13 July 2012.
Call for papers: NCEI'12
The deadline for submitting abstracts to the Neuro-Computing and Evolving Intelligence2012 (NCEI'12) is 30 April 2012. This conference will be held in Auckland, New Zealand, 30 June 2012.
Monday, April 16, 2012
Reminder: paper submission deadline ICONIP 2012
A reminder that the paper submission deadline for the International Conference on Neural Information Processing (ICONIP) 2012 is May 15, 2012. This conference will be held in Doha, Qatar, November 12-15, 2012.
Friday, April 13, 2012
Reminder: paper submission deadline for IDA 2012
A reminder that the deadline for submitting papers to the Eleventh International Symposium on Intelligence Data Analysis (IDA) 2012 is 12 May 2012. This symposium will be held in Helsinki, Finland, 27-27 October, 2012.
Thursday, April 12, 2012
Call for papers: iFuzzy 2012
The deadline for papers submitted to the International Conference on Fuzzy Theory and its Application 2012 is 20 August 2012. This conference will be held in Taiching, Tuiwan, 16-18 November, 2012.
Wednesday, April 11, 2012
Reminder: paper submission deadline for IEEE-SSCI 2013
A reminder that the deadline for the IEEE Symposium Series in Computational Intelligence 2013 is 10 October 2012. This series of symposia will be held in Singapore 16-19 April 2013.
Tuesday, April 10, 2012
Building an online presence as an academic
There are several reasons an academic might want to establish an online presence. The first is good old-fashioned self-promotion: this is especially important for early-career academics. No-one else is going to promote your work, so you have to do it yourself. Carefully building an online presence that connects your name with your area of expertise is one way to build your profile and to get your name known.
I have quite a common name ("Michael" and "John" are something like the second or third most common given names for males in my generation, and "Watts" is the second or third most common surname for people of English ancestry) but if you Google for "Michael Watts computational intelligence" 45 of the first 50 hits are either my pages or pages that specifically mention me, such as committees I serve on. So, as far as Google is concerned, my name is linked pretty strongly with computational intelligence (certainly more strongly than it is with ecological modelling - 29/50 - which is what I get paid to do).
Secondly, communicating your work to other scientists and to the public is at the heart of what scientists do: idealistically, our work is done to benefit humanity, but it cannot do that if no-one knows about what you do. Of course, the primary means of communicating with other scientists is via papers and conferences, but papers are not very accessible to the general public: they are written for other scientists, that is, they can be quite abstract and hard to read, and papers can be hard to find, that is, locked behind pay-walls. An online presence, however, can be made much more accessible. It does not need to be written in the strict "scientific style", it can include links to supporting material to assist reader comprehension, and it is freely available.
Having a website is a good start, and is a good place to put things like software and teaching materials that you want to make available for others to use. If you have something to say though (and every scientist should have something to say) then a blog is an excellent way of saying it. I started this blog because I was inspired to do so by two of the people I work with, both of whom run popular blogs, on climate change and conservation biology respectively. After studying their blogs and realising that there was nothing equivalent for computational intelligence, I started this blog. It takes me an hour or two per week to produce new content for the blog, which I personally think is time well spent.
There are many social media and networking sites out there, and it is worth your time to establish profiles in as many of them as you can. The obvious ones are Facebook*, LinkedIn, Twitter and Google+ but there are also a number of networking sites specifically for academics. The big ones appear to be Academia.edu and ResearchGate, but others are network.nature.com, Epernicus, KES International, Research pages, the Research Cooperative, scholarz.net, biomedexperts.com, scispace.com, mynetresearch.com, labroots.com, researchiscool.com, iamresearcher.com, researchr.org and hypertope.com. There are also publication trackers like Google Scholar Citations and Researcher ID. Most networking and social media sites allow you to specify a research interest and a home page, so I always list computational intelligence and point them all to my own web site. This has the effect of creating a lot of points on the web that, firstly, associate my name with computational intelligence, and secondly, associate my name with my website. This has the effect of boosting my name in the search engine results. It can be a lot of work to set these profiles up, especially if you have a lot of publications, but maintenance after that is limited to updating sites when you publish new papers.
Having a website isn't that expensive (I pay about AU$110 per year for the website and domain name). Blogs are free (unless you want to associate it with a domain name, which is still pretty cheap), as are the social media and networking sites I use. The best thing is, many of these can be linked together so that an update on one site is propagated to others (see the report I wrote here about linking this blog to other sites).
There are several articles about scientists and social media that are well worth a read: here, here, here, here, and here. These cover things like using Twitter to communicate more effectively. So, why not invest some time and a bit of money, and start establishing your own online presence?
*You may notice that I haven't linked to my Facebook profile: this is because I mostly use Facebook to keep in touch with old friends and family members, who aren't particularly interested in Computational Intelligence.
Edited 17 April to add link to researchr.org
Edited 11 April to add link to iamresearcher.com
I have quite a common name ("Michael" and "John" are something like the second or third most common given names for males in my generation, and "Watts" is the second or third most common surname for people of English ancestry) but if you Google for "Michael Watts computational intelligence" 45 of the first 50 hits are either my pages or pages that specifically mention me, such as committees I serve on. So, as far as Google is concerned, my name is linked pretty strongly with computational intelligence (certainly more strongly than it is with ecological modelling - 29/50 - which is what I get paid to do).
Secondly, communicating your work to other scientists and to the public is at the heart of what scientists do: idealistically, our work is done to benefit humanity, but it cannot do that if no-one knows about what you do. Of course, the primary means of communicating with other scientists is via papers and conferences, but papers are not very accessible to the general public: they are written for other scientists, that is, they can be quite abstract and hard to read, and papers can be hard to find, that is, locked behind pay-walls. An online presence, however, can be made much more accessible. It does not need to be written in the strict "scientific style", it can include links to supporting material to assist reader comprehension, and it is freely available.
Having a website is a good start, and is a good place to put things like software and teaching materials that you want to make available for others to use. If you have something to say though (and every scientist should have something to say) then a blog is an excellent way of saying it. I started this blog because I was inspired to do so by two of the people I work with, both of whom run popular blogs, on climate change and conservation biology respectively. After studying their blogs and realising that there was nothing equivalent for computational intelligence, I started this blog. It takes me an hour or two per week to produce new content for the blog, which I personally think is time well spent.
There are many social media and networking sites out there, and it is worth your time to establish profiles in as many of them as you can. The obvious ones are Facebook*, LinkedIn, Twitter and Google+ but there are also a number of networking sites specifically for academics. The big ones appear to be Academia.edu and ResearchGate, but others are network.nature.com, Epernicus, KES International, Research pages, the Research Cooperative, scholarz.net, biomedexperts.com, scispace.com, mynetresearch.com, labroots.com, researchiscool.com, iamresearcher.com, researchr.org and hypertope.com. There are also publication trackers like Google Scholar Citations and Researcher ID. Most networking and social media sites allow you to specify a research interest and a home page, so I always list computational intelligence and point them all to my own web site. This has the effect of creating a lot of points on the web that, firstly, associate my name with computational intelligence, and secondly, associate my name with my website. This has the effect of boosting my name in the search engine results. It can be a lot of work to set these profiles up, especially if you have a lot of publications, but maintenance after that is limited to updating sites when you publish new papers.
Having a website isn't that expensive (I pay about AU$110 per year for the website and domain name). Blogs are free (unless you want to associate it with a domain name, which is still pretty cheap), as are the social media and networking sites I use. The best thing is, many of these can be linked together so that an update on one site is propagated to others (see the report I wrote here about linking this blog to other sites).
There are several articles about scientists and social media that are well worth a read: here, here, here, here, and here. These cover things like using Twitter to communicate more effectively. So, why not invest some time and a bit of money, and start establishing your own online presence?
*You may notice that I haven't linked to my Facebook profile: this is because I mostly use Facebook to keep in touch with old friends and family members, who aren't particularly interested in Computational Intelligence.
Edited 17 April to add link to researchr.org
Edited 11 April to add link to iamresearcher.com
Monday, April 9, 2012
Conference paper deadline: ICIIC 2012
The paper submission deadline for the International Conference on Information and Intelligent Computing 2012 is 20 July 2012. This conference will be held in Chengdu, China, 8-9 December, 2012.
Sunday, April 8, 2012
Website on Evolving Connectionist Systems updated
I've updated my website on Evolving Connectionist Systems at ecos.watts.net.nz. The major change is that the equations are all rendered using MathML, which makes them much neater and easier to read.
Friday, April 6, 2012
Call for papers: IEEE ICACI 2012
The deadline for submitting papers to the IEEE International Conference on Advanced Computational Intelligence 2012 is 15 May 2012. This conference will be held in Nanjing, China, 18-20 October, 2012.
Thursday, April 5, 2012
Conference paper deadline: MLSP 2012
The deadline for submitting papers to the IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2012 is 7 May 2012. This workshop will be held in Santanda, Spain, 23-26 September 2012.
Wednesday, April 4, 2012
Deadline extended: Special Issue: Applications of ECoS
The deadline for submitting papers to the special issue of Evolving Systems on Applications of Evolving Connectionist Systems has been extended to 14 May 2012.
Subscribe to:
Posts (Atom)
Posts
