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Found 12 results

  1. Hi Everyone, My profile is as follows BS (India) GPA 3.75/4, MS USA 3.6/4, GRE 301 V-149, Q-152, AWA-4 TOEFL - 106 (R-23, W-25, L-28, S-30) I have around 2 years of research exp and 6 months of teaching experience as TA during my MS No publications , working on a paper currently though. and a year of software engineering experience all in the US I am interested in human computer interaction and machine learning programs. I have shortlisted following universities. 1. Colorado state University 2. university of Texas Dallas 3. Iowa State University 4. Kent state University 5. SUNY buffalo 6. university of North Texas Do, I have any chances of a fully funded admit with this profile or should I retake gre and apply next term? I did email professors and mostly all of them encouraged me to apply and mention them in SOP. please let me know if there are any other universities I should look into. Thank You.
  2. Undergrad Institution: (School or type of school, such as big state, lib arts, ivy, technical, foreign (what country?)) Masters Institution: (if applicable, otherwise delete this)Major(s):Minor(s):GPA in Major:Overall GPA:Position in Class: (No numbers needed, but are you top? near top? average? struggling?)Type of Student: (Domestic/International, male/female, minority?)GRE Scores (revised/old version):Q:V:W:TOEFL Total: (if applicable, otherwise delete this)Research Experience: (At your school or elsewhere? What field? How much time? Any publications (Mth author out of N?) or conference talks etc...)Awards/Honors/Recognitions: (Within your school or outside?)Pertinent Activities or Jobs: (Such as tutor, TA, etc...)Any Miscellaneous Accomplishments that Might Help:Special Bonus Points: (Such as connections, grad classes, famous recommenders, female or minority status etc...)Any Other Info That Shows Up On Your App and Might Matter:Applying to Where:School - MS/PhD? - Department - Research InterestSchool - MS/PhD? - Department - Research InterestSchool - MS/PhD? - Department - Research Interest
  3. How does each of the universities fare in ML research at Masters level (please justify, that would be very helpful :)? What is the placement scenario at each of the universities? Please try to rate the universities out of 5 with 0.5 increments.
  4. I urgently need feedback on my SoP draft for my application for a Master's in Computer Science. Anyone willing to help? I'll PM the SoP to you. Thanks in advance
  5. GPA: 3.37 TOEFL: 115 GRE (unofficial): V164 Q168 I want to pursue a Master's degree with a focus on machine learning and / or natural language processing, but I'm having a difficult time determining the range of schools I should be applying to. Ultimately, I would like to get a PhD at a top 20 university, and get involved in CS research at a competitive R&D division or laboratory. Therefore, it's important for me to find a place that is productive in terms of research in ML / NLP. I'm especially interested in grad schools in Canada, but I'm certainly open to other suggestions. To give you an idea about my profile: I graduated with a degree in computer engineering from the most internationally esteemed university in my country with a subpar GPA, which was mostly caused by poor performance over a couple of semesters during which my family was going through a rough time. I did get back on track, and did fairly well in the last three semesters though. I was wondering how those obvious and sudden transitions in my transcript would be interpreted by the admission office? Should I address the reason in my SOP, or just leave it alone? I also ended up graduating in the top 10 of my class anyway, so that might be worth mentioning. (Yes, the highest GPA that year was ~3.7, and the second ~3.5, which I know seems ridiculously low compared to most other schools.) As for experience, I worked at a large defense company as an intern, and later at a robotics laboratory participating in deep reinforcement learning research for a few months. I also spent two years working part-time as an undergraduate TA. Unfortunately, I have no publications or serious research experience to speak of. Not sure if these are at all relevant, but I also played chess in the national junior team, and the violin in my country's first amateur symphony orchestra, whose establishment I took some part in. I have a few decent LORs, but I'm still unclear as to what constitutes a "strong LOR". That's basically it. I feel incredibly incompetent, and afraid that I might not get in at all. Currently, I'm considering U of Montreal, U of Alberta, McGill and Simon Fraser to begin with. Are all of these too ambitious for me? Should I aim somewhat higher - or lower? What other schools should I look into? Many thanks in advance!
  6. Hola! I am having a tough time selecting universities to apply to for MS -CS (AI / ML ). Tough cause I am trying to shortlist universities that will take me and are ranked in the top 50. Profile: GRE: 169Q, 158 V, 4 AWA TOEFL: 117 GPA: 7.2 ( 65% Mumbai university) 3-4 projects 2 years work experience (software developer) Please help me shortlist universities as safe/mod/ambi. Right now I am looking at - ASU, UC Davis, UCI, Virginia Tech, Indiana bloomington.
  7. Hi I have received 2 admits for MS in CS from UCLA and Columbia University. I am very confused and unable to decide one. Any inputs on which one i should lean onto? Pros/Cons of both? I am interested in ML/AI.
  8. I have been admitted to the Masters program at Virgina Tech, Blacksburg Campus. I have completed my undergraduation in electrical engineering. My work experience lies in the automotive industry. My area of focus is in Software and Machine Intelligence or Signals and Systems. I could choose between these two. I intend to study subjects concerning Machine Learning and work towards a thesis in autonomous systems. Since, I do not have any substantial coding experience, just self-taught Python etc., I would like suggestions on choosing the coursework for the graduate program. I plan to have the following courses to satisfy the program requirements - Pattern Recognition Convex Optimization Deep Learning Advanced Machine Learning Probabilistic Graphical Models and Structured Predictions Advanced Topics in Intelligent Systems Theory of Algorithms I plan to learn Data Structures, Java, Python and build up a strong mathematical background in the next three months, before graduate school starts. I also intend to work in a lab, to perform research for my thesis or towards a project. I am afraid that my coursework is quite heavy, though those fears may be unfounded. Any advice on choosing the coursework for a non CS background guy would be appreciated. Any leads on preparing for this courses would also be appreciated! Thanks! ECE5524, Pattern Recognition
  9. Hi, I have an admit from Rutgers University for masters in fall 2017 (AI/ML). I looked around on linked in and looks like the alumni network of Rutgers is not very strong in the field of computer science. How will it impact my job oppotunities after MS. Should I even go there ?
  10. Looking at a masters in CS, either coursework or research (I likely will not be pursuing a PhD). Profile: School: Current junior at school ranked ~60th in CS in the south. GPA: Major: 4.0, Overall 3.90 Research: Working with a professor for a year, name on a paper and REU funding for next semester. Internships: Some industry internships at local companies and FinTech in NYC. GRE: Not taken yet, expect to target SAT roughly (800R, 700M) or better. Strengths: 1) Good GPA 2) Professor I do research with doesn't hate me. Weaknesses: 1) GPA could go down to 3.9 Major/3.8 overall after this semester, but I only have 1 full-time semester left. 2) No focused coursework - no very high level maths yet, no graduate level courses until senior year. Any thoughts? I'm primarily interested in ML and Computer Vision, and my research focuses on applications of ML in security. Currently, the schools I've been looking at have been UNC, Duke, UCSD, UW-Madison (with faculty introductions) GaTech, Columbia, UPenn CIS, CMU MS CS (far reach), Stanford MS CS (far reach) Thanks!
  11. Hi,I am a 4th-year student from Anna university, Chennai (India).My profile is:8.87 CGPA (till 6th sem)320 GRE (163 quants/157 verbal; 4.0 AWA)TOEFL - yet to take (expecting 105+)Papers/Research published : NoneExperience:2.5 months summer research internship at Indian Institue of Technology-Madras (IIT-M) in Machine learning.3-4 projects done in machine learning (all in github profile)Recommendations: Expecting 3 from my univ profs and 1 from my IIT-prof (internship guide)Interests: AI (specifically, machine learning) Univs I have selected so far:Top preferences:Univ of California - LA, SD campus Umass Amherst Georgia tech CMU Univ of Illinois - UC campus Univ of southern California Univ of Wisconsin - Madison Univ of Texas Austin,ArlingtonUniv of Maryland - college park Univ of ChicagoSecondary choice: UC - Irvine NCSU ASU NYU Penn statePlease help in evaluating my profile and suggesting suitable universities.Also, since I have about 1.5 months to apply, should I take GRE again? I am confident that I will improve my quant score by at least 2 or 3 marks, but not sure about verbal - might stay same or even decrease. Will the 2-3 mark improvement significantly affect my chances in the above-listed universities?Thank you!
  12. Hi, I have been fortunate to get two wonderful offers: Berkeley and UW. I would appreciate any comments about them and advice on where to go. I visited both places, and liked both universities. Both cities seem to be huge tech hubs (Berkeley more so than Seattle, but the latter is great too), have good weather, and look gorgeous. I can see myself doing good work at either place and also living comfortably. For many people, Berkeley would almost look like an obvious choice, but surprisingly I find myself leaning towards UW. I have summarized my reasoning below. Am I shooting myself in the foot? Berkeley has many great researchers in my area, but they are not as accessible as I had imagined. Most top POIs are oversubscribed with 15+ grad students and postdocs. Hence, it would be hard to get face time with them, or I have to compromise and work with junior faculty. On the other hand, UW CSE is expanding at a good pace with great funding. Many top faculty were hired over the past 2-3 years and are in the process of expanding their labs. Sergey Levine joined recently, and the general consensus is that he was the brain behind most of the robotics work at Berkeley over the past 2-3 years. The situation boils down to sub-optimal POI support (either face time or researcher) at a more prestigious place vs ability to work freely with anyone I want at a (slightly?) less prestigious place. Can anyone offer advice on how to navigate this landscape? Is the difference between Berkeley and UW very significant, that too in ML/AI/robotics? I believe both are top 5 schools. Thanks!
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