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Hello, I have applied to the following programs for PhD UC Berkeley (MSE) Carnegie Mellon University (BME) Iowa State University (MSE) University of Delaware (MSE) Drexel University (BME) University of Central Florida (MSE) University of Massachusetts - Amherst (ChE) What do you think about my chances in these schools? Should I apply to few more schools? Here is my brief profile B.Sc. in Materials and Metallurgical Engineering (3.61/4.0, Bangladesh Uni. of Eng. and Tech.) GRE: 315 (Quant 165, Verbal 150, AWA 3.5) IELTS: 8 (Reading 9, Listening 7.5, Speaking 7.5, Writing 7) Research Experience: Working as a RA from December 2017 Publications: 1 published (Materials Research Express, IOP), 1 submitted

I would like to provide some information regarding the reality of getting admitted to top 5 ranked Canadian graduate schools in the Computer Science Program. I work in the field and it appears to me that many applicants are not aware of some of the basic requirements to be admitted that are not overtly stated but definitely required. Unfortunately, I am unable to reveal my university or position as I wish to remain anonymous. Most of the time, you MUST have previous degree from a top school of your country, especially for students with a degree outside of Canada/USA/UK. This is extremely crucial for international students and unless you meet this requirement, it is extremely difficult to be admitted. For most countries, you will need to be in the top 5-10 universities in your country (excluding Canada/US/UK/India). For India, UK, and Canada you will generally need to be in the top 20 universities and for the US, top 50 may be considered, however, top 20 has a greater chance of being admitted. One of the first considerations of the reviewer is the school in which you graduated and how that school ranks in your country. To elaborate, having a degree from a top university is important because this is the only sure way to prove that you are performing well academically because the teaching standard and research caliber of top schools are widely recognized and can easily be compared top Canadian universities. It is impossible for each top Canadian university to understand the teaching, grading and research standard of hundreds of thousands of universities in the world, including many in a foreign language with public and private systems and most reviewers will not dig around for information regarding unknown institutions. For example, there are some universities that give a grade of 75% or above to only one in a few thousand students, whereas another university can have a graduating average of 3.7 GPA. With variations like these, unless you graduated from a top university in your country where the general grading trend and teaching quality is recognized by the Canadian school, your chances of admission are slim to none. Furthermore, the other reason a top university is important is that reviewers want to see reference letters from colleagues or faculty they know and value the opinions of. Since most top researchers in Computer Science meet in major conferences, presentations and events around the world, they are aware of each other’s work, reputation and standards when writing and reading reference letters. Most of these outstanding members of the academic community are also positioned in top schools coinciding with the reviewer’s search applications from top schools. The top Canadian graduate programs in Computer Science receive over 1000 and sometimes even over 2000 applications per year, with three reference letters per application this is an astronomical number of letters to read. Taking this number into account, while the content of reference letters matter, the respectability of the reference writer is arguably even more important. For example, a reviewer reading 100 applications a day would have to read 300 reference letters, 100 of them may indicate that the student is in the top 10% of their program. In the end, being top 10% may not mean anything because there are too many top 10%s and it does not indicate the quality of the student or education. Moreover, there have been examples where the same reference writer indicated that three different students from the same year and class were the number one student in their class. In cases like these, reviewers go back to looking at the top universities, since the caliber of education is known, and they may know the reference writers, therefore, ensuring the letter is reliable. If you believe that there are many exceptions to the rule, consider that the admission data from the previous year from one of the top Canadians schools: only TWO offers out of more than 100 offers made were outside of the guidelines above. Of course, an excellent statement, GPA, reference letters, GRE, and English proficiency are also required even from a top university. Moreover, other factors such as publications, conference experience, research projects and work experience, other achievements are also considered, however, if you do not meet the top university requirement, you will likely need astounding achievements in the other factors to even be considered for admission. The information provided refers to research Master’s and PhD programs in top Canadian universities and does not necessarily reflect industry targeted master’s programs in Computer Science. I am happy to answer any questions or clarify any points, feel free to contact me or respond to this post.

Hi, I graduated in December with a degree in Entertainment Design & Tech., and it was during my last semester that I realized my passion was really history and the arts. I applied at Rice and Emory (didn't make the cut, surprise!) because my fiancé's company has offices in Houston (where we currently live) and Atlanta. I'm not sure whether I should apply again, look elsewhere, finish the Master's program at UH and then try to find a Ph.D. only program? In the end, I've never had a good academic advisor so I've been making it up as I go. I'm not sure if my application/writing sample/supporting materials are strong enough, or if I should be reaching out to professors. I've never published any papers, so should I attempt that? I should also probably retake the GRE, but I don't do insanely well on timed standardized tests, so I'm not sure it's worth the time or money. In the end, I guess I'm just looking for a way to make myself more competitive, and perhaps clarify some of my confusion. I'd appreciate any thoughts you all might have. Thanks!

Please also point out any flaws in Technical Details if you see any. Thanks a lot. Statement of Purpose The scientific approach has always been a fundamental facet of my outlook towards life, belief system and academic pursuits. Driven by my scientific curiosity, I have arrived at a juncture where I am confident that a graduate research course with an initial M.Eng. Thesis and leading to a PhD is the most suitable step for me towards a career in research that I aspire to have. My principle interest is to conduct research in the broad area of Machine Learning (ML) and Signal Processing including their application in fields ranging from Robotics, Auditory Perception and Computer Vision. I am particularly fascinated by the application of Reinforcement Learning in Robotics, navigation and object recognition and identification. My goal is to learn and understand the decision making process of present day artificial agents under uncertainty and figuring out ways to improve them for novel applications in future. Thus one of my research interest is on tasks that can be framed as Markov Decision Processes in general and solved by Reinforcement Learning and dynamic programming. Furthermore, having an interest in Neuroscience and Behavioral Psychology, I am quite intrigued by how concepts of learning and intelligence from these fields can help make artificial intelligent systems more capable of human like decision making. I became interested to pursue a graduate degree at the School of Computer Science at XYZ University due to the world-class research going on here in the fields of my interest. At XYZ University, the works of Dr. XY are well suited to my research experiences and goals. I was particularly fascinated by his Lab's project "WWWW” as it utilizes RL techniques to make robots adaptive to changing ocean conditions without directly engineered controllers. I would also like to work on similar projects like Dr. XY’s work, “WWWW”, as it directly aligns with my research interest of working in the field of computer vision and scene understanding. His upcoming project utilizing Reinforcement Learning to identify objects based on how they sound to interact with has attracted me to apply to the program due to my past experience of working with audio classification and future goal of working with Reinforcement Learning. Moreover, the work performed in the Reasoning and Learning Lab is also well aligned with my research interests. My interest in Machine Learning research developed in my junior year while participating in IEEE Signal Processing Cup 2016. Working in this global competition helped me gain enormous experience and insight into the world of research. To participate in this event, I put together a team of likeminded peers. With Machine Learning being a relatively fringe topic in our university without many experts, we resorted to independent study. As I was the principle programmer and signal processing researcher in the team, I conducted literature survey to learn, understand and implement the necessary algorithm and make improvements to the classification system with the help of another team mate; while the rest of the team worked on hardware implementation and data gathering, all within a narrow window of three months. In this event, we classified audio recordings according to the location those recordings were made, exploiting the unique Electrical Network Frequency (ENF) embedded in those recordings. We extracted a wide array of statistical features ranging from mean and variance to more subtle ones, such as those derived from Multilevel Wavelet Decomposition and Auto-regressive models, for the implementation of a Supervised Multiclass Support Vector Machine (SVM). During this work, while implementing a classification system based on high dimensional features, I became introduced to concepts and techniques such as Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Fisher’s Linear Discriminant Analysis (LDA). Moreover, I became familiarized with Bayesian Inference, Gaussian mixture models (GMM), and weighted SVM as well among other concepts from statistics and machine learning. This work taught me how to develop an end-user platform from scratch by taking a concept from existing literature and improving it. Eventually, I managed to lead the team to 11th position among 52 teams worldwide. An extension of this work has been accepted for publication in the peer-reviewed conference proceedings of IEEE R10HTC 2017. This success coupled with the theoretical understanding acquired through great performance in coursework on Data Structure and Algorithms, Random Signals and Processes, Discreet Mathematics, Numerical Analysis, Signals and Systems, and Control System Engineering convinced me that a career as a researcher in the field of Machine Learning or its application is the one I should pursue. I was accepted into two of Bangladesh’s premier universities, Bangladesh University of Engineering and Technology (BUET) and Dhaka University, ranking above 95 percent of the test takers in their entrance exams. At my undergraduate university, Islamic University of Technology (IUT), I received the prestigious OIC scholarship, which provided a tuition waiver for three years of my stay and included a generous monthly allowance. In my senior year at IUT, I designed and instructed a MATLAB based signal processing course for IEEE IUT Student Branch, which was attended by over a 100 students from various levels of my university. Even though I struggled in the initial semesters at IUT due to family problems as my mother passed away from cancer, I showed grit and determination by consistently ranking around the top of my class in the core courses of the last five semesters. At IUT, I worked on many projects ranging from voice pattern recognition system to hardware and software implementation of Microcontroller based temperature sensors for electric motor control. These experiences helped me develop my programming and logical skills. Concurrently, I engrossed myself into machine learning and mathematics by learning from massive open online courses: Machine Learning (Stanford Online, Coursera), Introduction to AI (Udacity), and independent study of books such as Linear Algebra by Gilbert Strang, Reinforcement Learning: An Introduction by Sutton and Barto, and Calculus by Michael Spivak. I also kept following online streams of International Conference on Machine Learning (ICML) and Neural Information Processing Systems (NIPS) to keep in touch with the latest developments in the general field of Machine Learning. In my senior year, I worked in IUT’s nanophotonics group for my undergraduate thesis on computational nanophotonics. We computationally investigated the effects of the near-field enhancements of metal nanoparticles in GaAs, CdTe and Perovskite absorber layers and worked on finding efficient and cost effective materials. The resultant work was published in the proceedings of 2016 IEEE APACE conference. I believe I have the research exposure, determination, and academic preparation to be a part of the world-class graduate research community of XYZ University. I am confident that XYZ University is the best place for me to have a career in the forefront of cutting edge research that I intend to have.

Can someone suggest me for any low-cost online courses associated with biomedical engineering? Since i don't have any research papers i planned to rise my sop using online courses. Will online courses really help in improving my sop??

Does it have to be Times New Roman 12pt? Can I use Arial 11pt-will this appear to be too small/tight for the readers?

The UCLA graduate application requires a personal history statement where you have to talk about how your life experiences and how they led to the decision to pursue the graduate field of interest. It specifically says that "this statement should not duplicate the statement of purpose". In my SoP, I am already writing about how my experiences, both personal and academic, made me apply to XXX programs so I am not sure how this personal history statement is different from the statement of purpose.

In CV, if I want to list a class I took in the fall semester of, let's say, 2014. Should I write out the months, ie: August-December 2014, or simply Fall 2014 is fine?

Hi all! I'm in the midst of applying to programs for fall 2017. At least one of my programs has asked me to write two statements of purpose, one in English and one in the target program language, Spanish. I have no problem with this, but I'm curious - are committees looking to see how well I write the same things in both languages or are they looking for two independent essays? What I mean to say is, should I more or less be writing the same content but in two languages, or are they looking for something else? Looking for students/scholars who have had experience with this, but anyone with any insight can offer their $.02 of course. Thanks!

I am applying to master's programs right now and am in a bind. My professor accused me of academic misconduct in one of my undergraduate classes. I had asked a question on an online forum about an assignment and posted a short excerpt of my work. This had not been an issue with other professors. This professor was strongly against posting anything online, he found my post online and stated that I violated his rule of knowingly or unknowingly making my solutions available to other students. I felt this was a stretch, but the school sided with the professor and he will Fail me for the class. My school says the records of this academic misconduct process are sealed, and there will be no notation on my transcript, just the failed grade. Graduate school applications ask if one has been involved in any type of academic hearings and to explain the circumstances. The application also asks me to explain any failed grades. I fear if I disclose all this information it will hurt my application. As far as I know the graduate school will not be able to find out there was any misconduct. Unless they contact student affairs and I permit them to see those records. Any guidance on what I should do? Thank you.