One of the things I think can change in higher education is that having mentors for graduate students to be mandatory like having advisors. Essentially, how I think is that grad students especially PhD students in their early years of study will need more general advice that can help them survive the PhD and solve their challenges they face. I think there are more challenges in the first years of study than the later years. Later years in PhD study is more dedicated to the research than other things. In early years students have to get very serious decisions like choosing the advisor, selecting the area of study, selecting the topic of research and many other decisions that need to be made probably by the help of more professional and senior people than the student alone because I think these kinds of decisions effect our PhD and later our carrier path a lot. We actually have mentors in the departments but I think the role of mentors are not very serious or at least many students are not aware of them. The other thing that I really like to be changed in university and we discussed it a little bit in class was that students can give feedback to the faculty members. Right now we have students’ feed back on how well faculties teach in class but we don’t have this kind of feed back for other things. For instance, if some one is in charge of graduate coordinator of the department but never answers any emails by students or an advisor who is very aggressive and doesn’t behave properly or respect well the students.
The other thing is the way students get assessed in graduate school and basically I mean the grades and the GPA. I think the weight of grades and GPA should be lower for grad students and there must be other ways to assess the graduate students depending on the course and area of study. The topic of grades and assessment of students are quite controversial and there are lots of debates on that from primary school all the way to the grad school. But, we all know the fact that the pressure of the grade can lower the quality of learning. Students at higher level of education should be trained in a way to be more creative and bring new ideas. Still, I don’t have clear solution in mind but as I sayed this topic is very controversial and many expert people in education design program have worked on it.

I found maybe some interview tips might be useful for grad students seeking academic jobs and so I started searching for it and here I share the summery of what I got:

The academic interviews are usually 1.5 to 2 days and the candidate should give a talk and 30 minute meetings from breakfast through dinner.  Be positive and think of yourself as a faculty member from the time you start applying for jobs. Do some research about the university, department, the program and probably the people interviewing you then you can come up with ideas how to have future contribution for the department. Show enthusiasm and excitement to work in that university department and especially in that position.

The top 4 interview questions are as follows:

Describe your research:

• What research you will do next.
• What are the limitations of your research.
• What is the broader significance of your research.
• What will be the first research project for a student working with you.

How will you teach:

• What are the courses you like to teach and how will you teach them.
• Certain courses especially the ones in your CV and you think you can teach.
• How your research will effect your teaching.

Why do you want to work in this university:

• What are the interesting things about the university you completed your degree in.
• In what ways you can contribute to the department.

Do you have any questions:

• You can come up with, What, in particular, are you looking for in filling this position?
• What research funds are available at different levels of the university?
• What, in particular, are you looking for in filling this position?
• What type of summer support is available?

You should speak with pride a bout your achievements and accomplishments in your research. Take responsibility for the work you have accomplished. For the questions about the marital status, family, religion and etc, you can answer and say that it doesn’t affect the job or you can say that it makes you feel uncomfortable

One of the challenges of PhD students is either go for academic jobs or a job in industry. Especially as we get closer to the graduation, this question obsess our minds unless one is very motivated to teaching and research so he/she will be pretty determined about academic jobs. The choice between academia and an industrial research lab involves many tradeoffs, and the best “fit” often depends on individual preferences and working style.

So, in this post I’m going to talk a little bit about the advantages and disadvantages of both academic and industry jobs and share with you what I’ve got so far. You are also very welcome to put comment and share your ideas and experiences with me and other readers.

So, let’s take a look of the some of the things that working in academia can offer:

• Freedom: Freedom in job is very important. Working in academia gives you more freedom in terms of time. Scheduling the time of meetings, research, writing paper, visiting students and teaching is all on you. Summer and the free time you have during the summer is another advantage working for academia. Working in industry you need to give monthly reports to the boss (even weekly reports), some times work very hard for the project deadlines and less flexibility to arrange and schedule your times. Professors generally have to report to their funding agencies about progress on research projects on an annual basis and there is not usually strict deadlines except writing proposals for the fund.

• Interaction with students: Working with students (usually younger than you) is a very joyful thing that you can not get it any where in industry. Advising and mentoring the students and sharing with them the experiences you have is a very wonderful opportunity. Moreover, as an instructor in class you have the opportunity to reach a large number of students. Working with students and helping them develop research taste, presentation skills, and life skills is simply one of the most rewarding aspects of the job.

• Interaction with expertise: Needless to mention that academia creates an extraordinary opportunity for learning, cross-disciplinary thinking and research with professional and expertise both in your area as well as other areas in the department you are working. Moreover, you can always reach out other people as well in other departments in order to work interdeciplinary.

• Stability:The level of stability that academia offers especially when one get tenured can not be compared with industry jobs. Research labs disappear, often with very little warning and there is tremendous variation in industry that sometimes is very risky.

Notably, various former professors have bemoaned the difficulty of obtaining funding, the difficulty of doing large-scale systems research, quixotic panels and program committees, the lower salaries, and so forth.

Now, let’s look at the some of the benefits that working in industry can offer:

• Discipline and organized: By working in industry you will have to meet peers and manager regularly that often, this type of structure can be extremely helpful for people’s productivity.

• Money: Especially for research labs the researchers do not have to worry about writing grants, visit funding agencies and etc.,

• Problem focus: Professors often work on many different problems at once. A researcher in an industrial lab typically has much more time to think deeply about a problem, hack on code, and directly contribute to the solutions that find their way into published papers.  Some people appreciate the opportunity to spend countless focused hours on technical work. Professors are distracted with many different tasks—teaching, committees, fundraising, advising, and so forth.

• Team Work: Academic work is pretty solitary. For people that enjoy being a part of a team or leading a team this aspect of industry can be a big pro.

Today I’m going to talk about some information about women in computing. I just returned back from a trip for CRA-W Grad Cohort workshop in San Diego. The aim of the work shop was to help new female grad students in the area of computing to overcome the problems they face during their studies, and also to encourage female under grad students to continue for the higher education in computing fields.

The CRA-W Grad Cohort workshop, was first started in 2004 and is supported by many sponsors from industry like Microsoft, google, IBM, Intel, some national labs as well as academia such as a lot of universities and institutions (This year Virginia Tech was also a sponoer), the National Science Foundation, and the computing community.

It was so effective for me that I wanted to share it with others. I got to know a lot of people in my area and I was able to make a stronger network with professional and expertise people in my area. We had a chance to interact with about 20 senior female computing-related researchers and professionals, who share their expertise, survival skills, as well as more personal information and insights about their experiences. The workshop was a mix of formal presentations and informal discussions and social events. A lot of them could give me advise and tips how to improve the quality of my studies, resume advising sessions, career advising sessions, discussing the academic jobs or non-academic jobs, how to improve the self esteem, how to have a good presentation and many more helpful sessions.

But the main reason I wanted to talk about here in my weblog is showing the importance of encouraging women in computing related as well as STEM majors. The fact is that men tend to dominate the tech industry jobs and for women, the numbers aren’t growing. A 2011 report by the U.S. Department of Commerce shows only one in seven engineers is female. Women have seen no employment growth in STEM jobs since 2000. As in my field, women hold only 27 percent of all computer science jobs. Even though female graduates hold 60 percent of all bachelor’s degrees, less than 20 percent of bachelor’s degrees in computer science are women.

Attracting more women in STEM fields will maximize innovation, creativity, and competitiveness. Scientists and engineers are working to solve some of the most difficult challenges of our time, and engineers design many of the things we use daily. When women are not involved in science and engineering, experiences, needs, and desires that are unique to women may be overlooked.

A number of things can enhance a young girl’s interest in science and for sure holding such events such as CRA-W grad cohort, ACM-W, association for women in computing fields at each university can overcome help this a lot.

The graph is taken from: http://cs.stanford.edu/people/eroberts/cs181/projects/women-in-cs/statistics.html#nsfdata

Nowadays, very complex phenomena happen all over the world that regular academic disciplines are not sufficient to solve or figure out the problems. Each discipline addresses only one specific aspect. Connections among diverse studies lead to better understanding the nonlinearity of the problems. Hence, the need for interdisciplinary studies grow every day and many interdisciplinary majors have been developed during the recent years to accelerate the progress of exploring and understanding the problems better.

In general, interdisciplinarity involves combining of two or more academic disciplines in to one discipline to develop more creative and powerful way of thinking and solving the problems. Interdisciplinary involves researchers, students and teachers in the goal of connecting and combining several academic schools in to one consistent and goal-oriented study. Some examples of interdisciplinary majors are Applied Mathematics, Environmental Science, Mathematical Economics, Cognitive Science, Biomedical Science and Healthcare Systems. Cognitive science that also counts for one of the interdisciplinary majors in my area is the combination of psychology, philosophy, computer science and neuro science. The main aim of this major is to enable human being understand the learning process that happens in the brains of human. Figuring out the learning process is very important for the scientist of many majors. From computer science perspective, understanding the learning process in human and animal brains help us design and build machines that can learn like human and react smartly and wisely. The application mostly goes to robotics and smart machines that try to act like humans.

Today I’m going to post about the definition of freedom in academia, what the freedom includes and what restrictions and limitations it has, as well as the importance of freedom in academia.
Generally speaking, the academia freedom is an essential right of faculty members in most legal systems. In US. It is defined as “Teachers are entitled to freedom in the classroom in discussing their subject.” Academic freedom in US is written by American Association of University Professors (AAUP) and the Association of American Colleges. The freedom of academia is necessary to the mission of the academy and that scholars and teachers should have freedom to teach or communicate ideas without the fear to lose their jobs unless the manner of expression substantially impairs the rights of others. However, it has some limitations including that teachers should be careful to avoid controversial matter. In public teachers and scholars can represent their idea without any fear but they should know that what they believe and talk is not the voice of institution. Moreover, it doesn’t mean a faculty member can threaten, harass ridicule, or impose his or her ideas on students. It gives faculty members and students the right to challenge one another’s views, but not to penalize them for holding them. More importantly, academic freedom does not give students or faculty the right to ignore college or university regulations.

For this post I found two articles the first article discusses the concerns and worries of the faculties and professors on MOOCs and there some ideas from professional people on education is expressed. The second article discusses the reasons why professors can use MOOCs to improve their proficiency in teaching.

The first article was mainly discussing the reactions of the professors and faculty members to the MOOCs. Friedman the columnist in the New York times had published an article that by means of MOOCs the courses from top universities are available to the students all over the world and the consequences of that. This column actually raised the reaction of some faculty members and they were blogging some complaining about this column while also worrying about their own future. They were mainly criticizing that a lot of funding about higher education should go to MOOCs. They had the concern of losing a lot more things than their jobs. For example, one of the faculty members believes that we should only be worried that MOOCs should not be a cost-cutting means for traditional universities. They also had concern that top professors from elite universities replace the lectures by faculty members at other universities which would represent the de-skilling of the faculty and also reduce the dynamism and the engagement of the professors and harm them with low pay and finally lead them to be teaching assistant for the online professors.

Cary Nelson, the outgoing president of the American Association of University Professors said that online models such as courseara can be terrific for delivering educational materials but its not education and its not even a reliable means for credentialing people. Nelson has this idea that education calls for real interaction between the students and the faculty members and the process that the faculty member can develop degree program while online courses are a bunch of online lectures that can not substitute for the degree program. Mark Smith, senior policy analyst at the National Education Association also believes that the faculty member should take over the control of the curriculum, structure and assessment of the course and finally the quality of the education. Sandra Schroeder, chair of the American Federation of Teachers Higher Education Program and Policy Council and president of AFT Washington also believes that these kind of course materials to what extent can answer the needs of the students. According to the AFT surveys students need more structure and stability in their coursework and students wont be succeeded unless a strong academic program is provided for them. Online program is very inferior compared to the face to face education.

The second article which I looked over discusses the five reasons why professors should also try MOOCs. The first reason is to look how other professors at other schools teach and observe the strengths and week points. If they find good points they should take it and otherwise they should try to avoid repeating their mistakes. The second reason is to join the community about the topic that interest them. The discussions and the forums that each topic of the online course can have will be continued and remain active even after the course is finished and this can never be found any where else except the online courses and online learning. The third reason why professors should also try MOOCs is that with online course they can relive student experience. Teachers can find out what is it like to be on the receiving side of the learning and they can experience the learning as a student which can effect the quality of professors teaching. The third reason is to learn new things in an structured manner which means instead of reading the books and browsing the internet for materials watching the lectures can make learn new things in more organized way.

So overall what I think is that MOOCs definitely can no take the place of the face to face learning. What I believe is that learning at each school is different and unique based on the design of the program and organizing the course materials. The assessment and evaluation process makes the program very structured that learning through that have deep impact than any other sources and even online courses. So far, based on my personal experiences the online courses can be considered as kind of assistantship beside the things students learn at their school. I personally have started many courses online but I couldn’t manage to finish the course because of the lack of motivation, and mainly the lack of proper assessment in the online courses. The fact that the learner can not ask questions and have appropriate interaction during the learning process is another important matter in this issue. Although I think MOOCs are on their early stage of development and can be enhanced and improved significantly in future and can be considered as precious source specially for those who don’t have access to proper education all over the world.

The title of the case I studied in the ORI scholarly integrity website website is “Data sharing fever” which is essentially the case of data acquisition and management.

The case is about a postdoctoral scholar named Mary who is also preparing herself to seek an assistant professor position. She is working on the NIH funded project with her postdoctoral advisor Henry who is also very pioneer for the fever treatments due to infections disease.

On their project they have succeeded to create a giant and precious data base that was ever collected tracking different infectious agents. Mary’s contribution is mainly due to her big effort on assisting to collect the data. Henry’s analysis suggest that alternative medicines is very effective for certain kind of infections but they don’t have effective impact on other kinds of infections. Henry is about to finalize his analysis and submit his manuscript and Mary would be the co-author because of her contribution on the project.

Mary who is preparing her self for the assistant professor positions is trying to write her research statement for her job applications. In her research statement she is claiming to use other approaches and methods to do the analysis on the same data set. She is also trying to write the project proposal to get the grant from NIH. Hence she is asking for Henry’s permission to use the dataset and Henry doesn’t seem to be very pleased mainly because he is not willing to share the dataset before publishing his own work.

Since Mary has access to the dataset she thinks its ethical to look more closely on the dataset and she spends quite a lot of time to look on the dataset and also on Henry’s analysis and there she finds out that Henry has excluded some important data from the dataset on to his analysis which can change the results of analysis significantly. Of course this doesn’t indicate any falsification of data since Henry has explained in detail the justification for the exclusion of some parts of data from their dataset on to the analysis. Mary has obtained very precious knowledge on the dataset as well as Henry’s analysis that can lead to the new therapies to treat fever. She feels so excited about her findings which can also have impact on her future results and NIH project. However, she has many concerns how to discuss this with her advisor.

Several questions can be raised here;

• when is the right time to share the dataset? Before publication or after the publication?
• Who owns the dataset? NIH? Public? Henry? Henry and collaborators?
• Is it ethical that Mary looks in to the dataset more closely and Henry’s analysis? Should she share her understanding with her advisor?
• If Henry doesn’t share the dataset before publication is this in conflict with the NIH research policy about sharing biomedical resources?

Here, I totally understand the Henry’s concerns about his work. The fact that he has put a precious effort and time collecting a very valuable dataset can not be denied. On the other hand we see that he has missed some understanding on the dataset that if he doesn’t share the dataset with others it can harm the result of the analysis. On the other way Mary has a contribution on the project since she has assisted on collecting the dataset but she wants to involve the dataset as part of her future research and get some project funding with that. So, its very controvericial when is the right time for sharing the dataset and should Mary uses the dataset before Henry’s publication. Which is ethical to proceed? To leave Henry with his understanding and analysis or engage him with the new prospective of the dataset that Mary found.

·   Volumes 49-60 ·       Issues 12

One of the very important journals in my field of study and specially in my research area is the journal of Pattern Recognition. Pattern recognition is a branch of machine learning that focuses on the recognition of patterns and regularities in data. Generally, pattern recognition, machine learning, data mining and knowledge discovery in databases (KDD) are hard to separate, as they largely overlap in their scope. The main goal of this journal is to publish articles on different learning techniques which essentially improve the performance of intelligent systems.

Journal Metrics:

• Print ISSN: 0031-3203
• Publisher: Elsevier
• SNIP (Source Normalized Impact per Paper): 524i
• SJR (SCImago Journal Rank): 477i
• Impact Factor: 096i
• 5 year Impact Factor: 613i
• Number of downloads: 243,375
• Review Speed (The average number of weeks it takes for an article to be reviewed): 16 weeks

• Where (location, organization, university, etc.) is the journal from?

The Editor-in-Chief is  Ching Y. Suen:

Dept. of Computer Science & Software Engineering, CENPARMI, Building EV, Concordia University, Suite 3-105, 1455 de Maisonneuve Blvd West, Montréal, QC H3G 1M8, Quebec, Canada

The publisher of the Pattern Recognition journal is Elsevier. Elsevier annually publishes approximately 350,000 articles a year in 2,000 journals. Its archives contain over 13 million documents. Total yearly downloads amount to 750 million. It was founded in 1880 and the head quarter is in Amsterdam, Netherland.

• What are the purpose, goals, scope, etc. of the journal?

The journal tries to expedite communication among research scientists interested in pattern recognition and it gives the scientist the opportunity to get together in one place to publish their work. Articles can be published in wide different areas including but not limited to computer science, information theory, optical processing techniques, and other miscellaneous fields. The application for the pattern recognition goes to biometrics, target recognition, biological taxonomy, meteorology, space science, classification methods, character recognition, image processing, industrial applications, neural computing, and many others. The journal emphasizes that the articles are being reviewed by competent scientific people. Moreover, special issues will be organized from time to time on current topics of interest to Pattern Recognition.

• How does the journal address/explain open access? How (if at all) does it position itself within the open access movement?

Open access journals are scholarly journals that are freely available online to the reader. There is no financial barrier for the reader, however, they might be some costs associated with the publication and production of such journals. And this journal specifically, has a part in the website itself which supports the open access and has a bar which shows the most recent open access articles in the journal. Moreover, the publisher of this journal is a world famous publisher Elsevier which uses science direct as a platform to give access to readers to the articles and there also we can see the open access articles of this journal.