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  1. LostMyDucK

    UCSD vs Columbia CS MS

    I have been accepted to UCSD and Columbia for Masters in CS. They are both ranked #15, so I was wondering what the advantages/disadvantages would be for attending one over the other. I plan to live in California (I am not a California resident so I will have to pay OOT) so UCSD seems attractive in that regard, but Columbia is an IVY LEAGUE! (I don't know if companies really care about this though). I have read that Columbia only really beats UCSD if you plan on working with firms/investors/start ups, though I'm not sure how much this thought holds true. Another thing about Columbia that is a negative is that it's difficult to attain funding where it would be much easier to score an RA/TA position at UCSD; however, I have no debt leaving undergrad so I am willing to take 2 years off debt because I'm not too worried about paying it off. Are my thoughts valid? What would be your opinion on this? Thanks in advance!
  2. LostMyDucK


    From your list, I have UCSD
  3. LostMyDucK

    UCR CS PhD

    It is indeed April 15th for UCR.
  4. LostMyDucK

    UCR CS PhD

    They only admit so many PhDs and I would say it's safe to assume that others are still waiting to see if they have been accepted to more favorable programs. That being said, even if those reject admits it doesn't necessarily mean you'll be next in line. Personally, I was accepted to their PhD (as you should know from the previous topic), but I had initially applied for MS and they were the ones to offer to swap me to PhD free. Oddly enough, I was accepted, but since I applied for MS and some MS still haven't sent out decisions, I will still be waiting. When I had emailed them, I was told they accepted 33 PhDs which means it'll take more time barbecue there's less applicants to reject it I guess?
  5. Dear All, Background: Currently I have 3 admits so far and I am torn between them. I am from a small state school and all of these admissions are top notch and beyond what I ever expected to gain admit to. I am also only trying to achieve my masters because I wish to go to industry and the pay bump for having a PhD isn't worth it if you're aiming for industry. Note: I have no debt from my undergraduate so I am willing to pay for masters because I believe I will be able to manage to pay it off for a two years masters. I just don't want to spend extra $$$ for a minute difference between schools. UCR (Ranked #56, they only accepted 33 PhDs)- Accepted to their PhD with a fellowship of 208k for 5 years. However, I have heard that UCR's social life is dead and it's a commuter college which implies that it's dead on the weekends. Furthermore, I have heard the area around UCR isn't the most exciting which is another downfall. Despite this, they said I am allowed to stop after masters which means I can attain it for free. USC (Ranked #20, MS seens as cash cow and high admit) - The main factor drawing me to USC is their insane social life. However, I don't think 100k~ for the two years is reasonable, but it's better by a large margin than both UCR and UCSD (from what I've read online). UCSD (Ranked #15, MS has an acceptence rate of 7.5%) - UCSD is a top tier university and the most reputable out of the three programs I have been accepted to. On top of that, they're on the beach and have beautiful weather! The one thing that's making me doubt UCSD is that it's a commuter college so it's dead the weekends (there seems to be a consensus on this). The social life also seems to be lacking which is another thing that I value which it does not have. I would love some opinions of what you guys have to think. Does UCSD prestige weigh that much more than USC and UCR? I know it ultimately depends on my own skills, but I wish to have every advantage I can have for when I enter industry.
  6. LostMyDucK

    Fall 2016 Admits Computer Science

    I did not. UCR emailed me offering me to swap my application (originally MS) into the PhD pool. I agreed and then received this official email two weeks later. The only contact I have had with my POI was about my interest with him, but I stated I was unsure of UCR until I knew all my offers. I apologize for my ambiguity. The total award is 208k, the stipend is 23k. The total award includes the stipend, TA/GSR (Graduate Student Researchship), Fees (im not sure what all goes into this category, but it does include health insurance), NRT, and misc. The award is for 5 years.
  7. LostMyDucK

    Fall 2016 Admits Computer Science

    So far I have been accepted to UCR's PhD with a 200k Fellowship and USC's Masters. Still have pending offers though from UIUC, Columbia, UCSD, UCI, UCSB ... this is so tough! For those questions regarding UCR, I did get an official letter. UCR offered to swap my Master's application to PhD for free and then my POI contacted me. Though the only thing we discussed was how I was uncertain of going to UCR..
  8. Applying for a M.S. (and possibly a PhD). How do I fare for top master programs, i'm worried about my GRE score and that my undergrad institution is a state school. My Letters of Recommendation includes both Advisers from my two REU experiences (UNT and GSU) and the Chair of Computer Science from my University so i'm confident my LoRs will be strong since all those writing my LoRs have shown high satisfaction in me and my SoP has been reviewed by them all as well so i'm sure those are strong points. Quant: 160 (I'm hoping this will be offset by my mathematics major and competence with higher level math; i'm not a very good standarized test taker ) Verbal: 155 AWA: 4.5 Another strong point which I think is unique on top of my research experience is " Mathematics Professor Selection Committee: Selected as the only student to work with faculty from the mathematics department to fill the vacant mathematics position. Responsibilities include reading applications, attending committee meetings, telephone interviews, and attending campus interviews." Here's my profile: Education · Bachelor of Science in Computer Science expected May 2016 · Double Major: Computer Science GPA: 3.86; Mathematics GPA: 3.56; Cumulative GPA: 3.76. · Enrolled in Honors Program Experience · Researched electroencephalogram (EEG) waves at University of North Texas (REU) during summer of 2015 o Assisted in developing an approach to distinguish between normal activities and malicious activates for the purpose of insider threat detection. · Researched Deep Learning at Georgia State University (REU) during summer of 2014 o Developed an algorithm to categorize documents into a fixed number of predefined categories using Word2vec. · Tutoring Mathematics & Computer Science: 2012-2016 · Computer Science Lab Assistant: 2013-2016 Skills · Operating Systems: Windows, Unix · Languages: C++, Visual C++, MySQL, Java, AWK, SED, Python, GREP. C# · Soft Skills: Selected for two REU research opportunities which have only an 8% acceptance rate (competitive). President or leadership roles in multiple organizations (confidence, leadership, adaptability & conflict resolution). Participated in programming, sports, and research teams (cooperative, communication, assertive & teamwork). Selected to work with the mathematic departments search committee (collaboration, attentive & critical observer). Accomplishments Publication · Conference publication as first author: Lilleberg, J.; Yun Zhu; Yanqing Zhang, "Support vector machines and Word2vec for text classification with semantic features," in Cognitive Informatics & Cognitive Computing (ICCI*CC), 2015 IEEE 14th International Conference on , vol., no., pp.136-140, 6-8 July 2015 DOI: 10.1109/ICCI-CC.2015.7259377 Honors and Awards · Mathematics Professor Selection Committee: Selected as the only student to work with faculty from the mathematics department to fill the vacant mathematics position. Responsibilities include reading applications, attending committee meetings, telephone interviews, and attending campus interviews. · Math & Computer Science Club: Elected as Vice President 2013. Elected as President 2014 & 2015. · ACM-International Collegiate Programing Contest: Honorable mention in 2013, 2014, and 2015 · National Honor Society of Leadership and Success: Promoted to Presidential status in 2013 · Dean’s List: Achieved Dean’s List award ten times. · League of Legends Club: Founded the League of Legends Club in the fall semester in 2014. · Chess Club: Elected as Officer in 2012 · University Newspaper Spotlight: Interviewed for founding the new League of Legends Club. Scholarships · Schwan’s Scholarship: annual renewal; 4 year recipient: 2012-2016; academic excellence · Schwan’s Computer Science Scholarship: non-renewal; 1 year recipient: 2014-2015; academic excellence · Science, Math & Computer Science Scholarship: annual renewal; 3 year recipient: 2013-2016; academic excellence · Dean’s Award Scholarship: maintain GPA requirements; 4 year recipient: 2012-2016; academic excellence · College Now Scholarship: maintain GPA requirements; 4 year recipient: 2012-2016; academic excellence · Ann C Peters Scholarship Endowment: annual renewal up to 2 years; 2 year recipient: 2014-2016; academic excellence and active participation in organizations · Lillian Mellenthin Scholarship Endowment: non-renewal; 1 year recipient: 2015-2016; academic excellence and leadership Activities and Interests · Math and Computer Science Club: Member 2012-Present | Vice President 2013-2014 | President 2014 – 2016 · National Honor Society of Leadership and Success: Member 2012-Present | Presidential member 2013-2016 · League of Legends Club: President 2014 – 2016 · Honors Club Member: 2012-2016 · Chess Club: Officer 2012-2016 Schools that I have applied to thus far 1. University of Illinois at Urbana Champaign 2. University of Southern California 3. University of California, Santa Barbara 4. Columbia University 5. Rensselaer Polytechnic Institute 6. University of California, Riverside 7. University of California, Irvine 8. University of Pennsylvania (I have expressed interest in my SoP in a professor who's research interests directly correlates to my publication which I was first author) 9. University of California, San Diego Thank you!
  9. First Issue: Educators should teach facts only after their students have studied the ideas, trends, and concepts that help explain those facts. Write a response in which you discuss the extent to which you agree or disagree with the recommendation and explain your reasoning for the position you take. In developing and supporting your position, describe specific circumstances in which adopting the recommendation would or would not be advantageous and explain how these examples shape your position. Essay: First, we must acknowledge that not all facts become lucid to individuals even after they have studied the ideas, trends, and concepts. They may not be able to make connections between the fragment parts that form the fact. One reason for this case can be contributed towards the fact that some individuals might need to see the whole before they are able to understand the parts. That is, they must be able to see the fact in order to make sense of the parts that help explain it. Therefore, since students are not all coterminous it may prove detrimental to teach in the style claimed in the statement. Mathematics, in my personal experience, is more detrimental to teach facts last. In mathematics, proofs range from a few lines to entire pages and usually, the longer the proof the harder it is to digest. When being taught, most of my mathematic teachers taught us the definition and how to apply it before they showed us the proof. The reasoning for this, they told me, was because those ideas, trends, and concepts can seem abstract and showing us the conclusion will help our focus on what we are looking for. In my case, if math teachers taught the proof before showing the definition it would be more detrimental to the students. For example, all the students in my Real Analysis taught us the proof first before showing us the definition and the entire class failed the first exam. When questioned on what could be done to change how he taught for us to better understand, the class desired him to define the definition first so that they had an idea of where the proof was headed. The class proceeded to pass the following exams for the rest of the year. In conclusion, teaching facts only after students have studied trends, ideas, and concepts is a haphazard approach to teaching. However, we must acknowledge that teaching in such a way does can be successful in many scenarios but making a universal claim is audacious. Some educators teaching this way would more pragmatic. claim 2: Society should identify those children who have special talents and provide training for them at an early age to develop their talents. Essay: I think Identifying children who have special talents and providing training for these early talents seems logical but elicits a concerns that make such a claim unviable. Before we can identify children with special talents, we must define what those talents are. We must be able to identify what constitutes a talent because it can be quite ambiguous. What one individual considers a talent, another may not. Is a talent one that is recognized by the majority or is there some prerequisite required to be considered a talent. For example, an individual may consider his ability stay under water for five minutes a special talent worth developing but individuals who don’t care for the water may disagree. There are too many what ifs regarding special talents and therefore it’s imperative that we are able to clearly express what a special talent is because not doing so would be a waste of resources. Once we are able to define what a talent is and what it is not, we must be able to determine if that talent is even worth developing. Which talents trump others or are they all equal? If there are talents that trump others, it would only follow that we would invest more into the higher tiered talents rather than those deemed less important. We must also consider the amount of resources we allocate to developing these talents. There is too much ambiguity and there would be too much controversy in determining which talents trump others and which are worth developing. Moreover, providing training to children with special talents can be quite beneficial; however, it can pose detrimental to children are not identified with special talents. If society recognizes children with special talents, then it also recognizes children without special talents. This can segregate the population because families without children with special talents might feel belittled by society because they don’t receive the same special benefits that families with children with special talents do. For anyone that takes the time to evaluate these, thank you!

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