Future Goals

The recent years in the technological education has witnessed a tremendous activity in all interdisciplinary fields. Elements of quantum physics and computer science were amalgamated in quantum information processing, molecular biology and Computer Science joined hands to create Bioinformatics, and Mechanical engineers worked with biologists to develop artificial limbs of extraordinary precision and maneuverability. Computer Science in particular, covering an array of fields such as Bioinformatics, Bio-mechanics, Electrical Engineering and Bioengineering, Systems Analysis, 3-D modeling, etc, has shown a tremendous potential for research and also an increasing number of applications in today's world of medicine and technology. So it is well known that future research in the varied fields of science, engineering and humanities will heavily depend on computers in general. As a result of which I look forward to a career of research after my graduation from U.T.E.P.

In view of the above I am currently involved in a lot of research activities to make that goal feasible. I have been working on problems related to Computer Vision, Machine Learning which is my area of interest and have managed to develop some excellent algorithms which are both efficient and cost effective to solve them. My recent research on surveillance motion detection has resulted in a publication which was accepted at the International Conference on Image Analysis and Recognition. Also as a sequel to this work I have developed a Foveal Visual System which simulates the behavior of a system that detects motion in real time using low resolution images and then foveates the area of interest similar to a human eye. I will be submitting this work very recently in a renowned Computer Vision Conference.

Apart from the above I have been also worked in biological sequence analysis research such as RNA structure prediction mechanisms using Machine Learning algorithms formally known as "Optimizing cut in RNA sequences using Machine Learning" or “Predicting the 3D structures of protein molecules using Electron Microscopic Cryo images” etc. Some of the other vision related projects include “Face Detection using Principal Component Analysis”, “Face Recognition and Tracking" and “Automatic Image Enhancement using a Genetic Algorithm”.

My motivation in research and ability for independent thinking is amply vindicated through my projects and my continued interest in them and a lifetime devoted to research seems to be the most exciting proposal for me. Being a researcher in computer science would enable me to solve real world problems first hand and thereby serve the society most directly. I feel that this is a most rewarding vocation and definitely one that I intend to pursue after my graduation.

Resources at UTEP

While writing research papers in scientific journals a significant portion of the work is dedicated to literature review. As a student of UTEP this has proved to be quite simple due to the numerous facilities that exist for students who have to simply login to the system and download related material of choice. Especially the library database that has a well established collection of journals, scientific magazines, e-books reduces much of the time and effort in actually retrieving a copy of the required material. Also since all of these materials are licensed under the University of Texas system Copyright Act the legal hazards associated also are taken care of.
Another facility which many students and I myself have used extensively is the my utep system which has a large number of resources listed under it for online services. These includes the Goldmine for registration purposes, the mspace for allowing students to upload and download documents, and the Blackboard learning system which helps students to take online courses. For example I have often made payments for my courses online using the Goldmine credit payment system which has in fact proved to be quite useful since I did not have to turn up at the Academic Services building to pay my tuition. Similarly in the case of mspace I have often uploaded documents and important material related to my T.A. work or my research and instead of having the fear of losing it all the time simply downloaded the necessary from the Internet. On the other hand Blackboard was a facility that I recently learnt of since I have not taken any online courses before. I was hoping we could make use of it even for regular courses like in the case when the faculty uploads an assignment and we finish the assignment on time and submit it online.

Apart from all the resources mentioned above I have also learnt about a recent one known as the 'Turnitin' where as a T.A. or faculty it is easy to detect plagiarized documents submitted by the students. But I am not sure about the rate of accuracy involved in such predictions or how much useful it would prove to be in the case when there is a match with documents belonging to students of the previous year.

Research Philosophy

In addition to my graduate and undergraduate coursework, I have had the opportunity to work on some projects and supervised research. This has helped me gain insight into both the practical and the theoretical aspects of computer science as well as develop the analytical skills, the knowledge base and the level of maturity necessary for excelling in graduate studies and research. My current research is based on “Real time Motion Detection using Structure and Color” which has recently been accepted in the International Conference of Image Analysis and Recognition (ICIAR), 2009. Here detection using structure is carried out with the aid of information gathered from the Census Transform computed on gradient images based on Sobel operators and using color is done by computing temporal histograms, which allow efficient characterization without prior assumptions about color distribution in the scene. Also work is in progress for Developing a Foveal Visual System which was submitted at IEEE Workshop on Applications of Computer Vision (WACV) at Snowbird Utah, 2009.

I have been also worked in sequence analysis research such as RNA structure prediction mechanisms using Machine Learning algorithms formally known as "Optimizing cut in RNA sequences using Machine Learning". Apart from that my research activities include “Face Detection using Principal Component Analysis”, “Face Recognition and Tracking”, and “Predicting 3D structures of protein molecules” etc. However it was my undergraduate project on “Automatic Image Enhancement using Genetic Algorithms” that developed my interest in Computer Vision especially in Image Processing Techniques. The genetic algorithm has the capability to find an optimal solution and hence GA is used to determine the value of the parameters and multipliers, to obtain the exact form of the function for image enhancement. Here enhancement is being done by gray level rescaling where each pixel is directly quantized to a new gray level in order to improve the contrast of an image and the evaluation function is needed for quantifying the desired amount of enhancement.

I look forward to a career of research in the broad area of Computer Science after completing my graduate education at UTEP. It is well known that future research in the varied fields of science, engineering and humanities will heavily depend on computers in general. Being a researcher in computer science would enable me to solve real world problems first hand and thereby serve the society most directly. I feel that this is a most rewarding vocation and definitely one that I intend to pursue after my graduation.

Observations

In the fall of 2007 I was teaching the same course as I am teaching now in Elementary Data Structures and Algorithm. It was the first time I was doing a T.A. and I was a bit shaky. My classes revolved more around the traditional ways of teaching techniques involving fewer interactions with the students. As a result of which I had a lot of class reviews which directly stated that I needed to be more interactive and use active learning strategies such as group discussion, pair-share, problem-solving or the minute paper.
So this time I started with that in my mind and not surprisingly I have completed almost three parts of the semester using this strategy and I have been doing pretty well. Also one thing that has to be kept in mind is that this course is not the easiest to teach, covering a syllabus that would normally have been taught in almost 2 dedicated courses. The benefit of a course like this is that, the student gets a very broad overview of all these interrelated topics such as programming, design and partial analysis of algorithms. But on the other hand, because of a huge and diverse syllabus, all of which are again interdependent, if anybody gets left behind, it is really difficult to catch up. Teaching this course is made even more difficult by the fact that the audience is from a very diverse background. There are students from Electrical Engineering, students from Computer Science, students from Engineering Science and several others. Each of these students has different reasons, motivations and interests. So the course had to be constructed and presented in such a way, to be of use to everybody.
 In applying these ideas, I am really fortunate to get such helpful feedbacks from the peer observation and the teaching observation projects. The feedbacks are encouraging but have lots of important suggestions. For example, as mentioned earlier, the practice of breaking the pace of the lecture from time to time, the practice of encouraging the students when solving a difficult problem, by being part of their team in the endeavor rather than just giving out the solution, from a position of superior knowledge. I believe that all these things have been really helpful in improving my teaching and should continue to help me, when I teach this course next time.

Uncertainties in Professional Development Plan

“All the world's a stage”. Nowhere do Shakespeare’s eternal words ring more true than in the teaching profession. Each time a professor faces his class, it’s a challenge, and it’s a performance. Now sometimes in class I have a tendency to ask trivial questions to make sure everybody understands what I am trying to say. As a result, an estranged silence follows that does not signify the ability but indifference towards answering the question. On the other hand answering difficult questions involves understanding as well as assimilation of the material, and that takes time. The result of such a question is again an awkward silence. The trick, it appears is to ask the right questions which will challenge the students without intimidating them.

Similarly in a big class full of students with a wide range of intellectual abilities, there is often a natural tendency on my part to advance at a rate suitable to the more gifted students. In all fairness, that does not seem the right approach, rather the right speed has to be struck, so that no one is left behind. However I do try to know each of my students by name, but more than that, as persons. I believe it is this personal touch which makes all the difference. Obviously, all this is no substitute for knowledge and the content of the course but I think this creates the perfect friendly atmosphere where everybody can participate whole heartedly.

Also with the best interest of the students in mind, I often challenge my students with all sorts of interesting problems while teaching. And it is gratifying to note that the students could stand up to the challenge making the whole teaching process highly interactive. Interactive teaching has its pros and cons. As students you always have to be on your toes, but that way you really imbibe what you learn.

The most effective method that can be employed in this respect is to help students understand and retain the material discussed in class is through continuous evaluation and instant feedback. In fact every day felt like a quiz – not a formal intimidating quiz, but quite an exhilarating challenge which will help them take interest in the subject and retain as much as possible.

Grading

Ever since I was a kid I have watched my parents, who were both professors, grade the exams of students by taking great pains to understand what they meant to convey through their answers even though they might not have written down the exact correct thing. I guess I took heart after that. I always try to keep in mind the intention of the student behind writing that particular answer instead of their direct action in writing it. Often it so happens as in the C.S. course I am teaching this semester that a trivial mistake like ending a brace prematurely may disrupt the entire flow of the program. But truly that is not an issue to be harsh about, and reduce the grade of the student. Because in the obvious sense he was writing far more important things which on the other hand happened to be perfect and he sort of overlooked this tiny thing. The fact that he changed the entire result of the program did not make him a bad performer since writing a program without a computer is almost similar to trying to win a war without an army.

In other aspects I sometimes do grade out of instinct and then I go so far as to talk with the concerned student to understand his motivation behind writing it. I have often asked such students whenever I get a chance to meet with them that if they wanted to change one thing about the piece of code they have written, what would it be? That says a lot. Now in other cases like suppose I have already graded a class and found out some common mistakes I go over it in the next class/lab and indirectly lead them to find out their own mistakes. I try never to tell it to them myself. I guess this is another old practice I learnt from my peers. Somewhat unsurprisingly I find students learn more that way rather than spoon-feeding them by directly stating their mistakes in class/lab.

Since one part of my work in grading this semester is grading quizzes, homeworks and another is the lab grading part both of which has a different bunch of students the first thing I try to do is to associate the names of the students with their faces. That way when I return the graded answer sheets back I can let them know about the small things they missed. Usually I grade quizzes and assignments out of a total of 100 marks and split up the entire total into smaller subdivisions so that even if it is one single program I have marks allotted for comments, program correctness, compilation errors, modularity etc. In the case of the labs I always make sure to have a one on one sessions so that I get a clear understanding about their approach and I assign a part of the grade here. It helps because I know where the student is headed and if they are moving in the wrong direction I have an opportunity to bring them back. Also another part of this is I get to take notes on which parts the student needs to improve on before they submit the final version of the lab and I later I can check if they have indeed worked on the changes promised.

I distinctly remember the first time I was grading and I clearly was a novice then. I surely did not have much of an idea regarding grading. I remember turning up at the professor’s office who was teaching that course more than often to understand what it takes to be a good grader. I always had a million questions then most of which I can solve myself now. But is guess that a lot of effort in this has made whatever I am now and that is surely a good thing.

Learning Styles

After I completed the Felder and Solomon’s learning inventory I found out that I am very well balanced between being a reflective and active learner. I absolutely agree to that. I like doing lots of hands on as well get engaged in brainstorming sessions. Everybody gets thrilled when they have a new thing to play with. But when it comes to understand a concept I would rather sit down quietly and think through it. When I requested some of my friends and students to use the inventory I found some have a tendency to be on the active learner side whereas most tend to be reflective by nature when it comes to learning processes.

Also I found out I stand in the exact middle when it comes to being judged as a sensing or an intuitive learner though I must admit that I am more of the latter then former. Sometimes I do not like to memorize facts, I am horrible at general knowledge and I do not like plug and chug problems. And so when few of the graduate students that I know also opted for being an intuitive learner it was kind of unsurprising because graduate students usually have a tendency to think intuitively rather than going over the facts they have learnt in class. Undergraduates on the other hand depend heavily on fact based learning. As a graduate student myself I must say I do not really mind if I have to work something out from first principles in the exam rather than memorizing the final formula, probably which brings out the intuitive side of me and often other fellow graduate students.

In visual vs. verbal learning, I am definitely inclined towards being a visual learner considering that I always associate a name with a face, and I do not remember many things that I hear. However when it comes to music I can remember most songs that I have heard. Even then I would say that my visual learning capabilities are better and I would sincerely persist on the fact that we need to have a lot of visual learning techniques in class because almost everyone remembers a picture better than a thousand words that are used to describe it.

A different case exists for sequential vs. global learning. It usually depends mostly on the specific problem. However, if possible I like to get a clear notion of the broader philosophy before thinking of the details. So all in all, I think that the Felder and Soloman's learning inventory did a reasonably good job of determining my learning habits.

I think that as far as classroom teaching is concerned, learning habits of individual students can make a considerable impact on the teaching style. Particularly for large classes, teaching methods should only make sure that students with all kinds of learning patterns can benefit from the course and use their own particular learning method to their full advantage. That means as a teacher I should make sure that I am aware of the learning methods of my students.