Hi all, would like to apologise for my messy posts around the forum lately at first. So finally, I have decided to move to quant finance and apply, I am mainly looking at MMF at U of Toronto, possibly some decent UK schools. I guess my low GRE (310+800) is killing me off for US. Would like to have some evaluations on my profile, hopefully its not a direct kill for you guys
So detailed info:
Schools in mind: U of T, LSE, Oxford, Imperial, possibly UNSW, ANU (Australia), all quantitative related master
School: Nanyang Tech Univ, Singapore
Master of Computer Engineering (wrapping up) (2 A- for Embedded operating systems + digital image processing, and 1 B- for neural networks, zzz)
Bachelor of Mechanical Engineering (Mechatronics) (2nd Upper Honours), Class rank: possible within 120/800 engineers, no GPA given
Research: Computer vision + machine learning (highly quantitative field, 2 years + experiences)
Math contents (A A A- B, something happened to my family in a term and I got B for the last one): Calculus, series, multivariate calc, ode, linear algebra, vector differential + integral calc, basic prob+stats, pde, laplace, fourier, complex...
Coding: 6 years of C, almost 2 years of Matlab, learning and using C++ for current project. Others include assembly, basic stamp, octave...
Publication: 1 CVPR Oral as third author (top destination, <5% acceptance rate) + 1 from undergraduate conference (1 citation since 2008), all about computer vision. We have another submission to a top machine learning journal (I am second author), hopefully good news can come before I send application. I am planning for few more too.
Recommendation letter expected to be top 10-15%.
What do you guys think about my profile?
Just a last question, do you guys think I have a chance at some good US schools like Stanford/UCB/Columbia? I don't know if I can fix my GRE verbal with publications. I guess I was just too nervous that time but I really don't have time to redo GRE before coming admission year. Quite tied up with research work.
Thanks a lot for your guidance
So detailed info:
Schools in mind: U of T, LSE, Oxford, Imperial, possibly UNSW, ANU (Australia), all quantitative related master
School: Nanyang Tech Univ, Singapore
Master of Computer Engineering (wrapping up) (2 A- for Embedded operating systems + digital image processing, and 1 B- for neural networks, zzz)
Bachelor of Mechanical Engineering (Mechatronics) (2nd Upper Honours), Class rank: possible within 120/800 engineers, no GPA given
Research: Computer vision + machine learning (highly quantitative field, 2 years + experiences)
Math contents (A A A- B, something happened to my family in a term and I got B for the last one): Calculus, series, multivariate calc, ode, linear algebra, vector differential + integral calc, basic prob+stats, pde, laplace, fourier, complex...
Coding: 6 years of C, almost 2 years of Matlab, learning and using C++ for current project. Others include assembly, basic stamp, octave...
Publication: 1 CVPR Oral as third author (top destination, <5% acceptance rate) + 1 from undergraduate conference (1 citation since 2008), all about computer vision. We have another submission to a top machine learning journal (I am second author), hopefully good news can come before I send application. I am planning for few more too.
Recommendation letter expected to be top 10-15%.
What do you guys think about my profile?
Just a last question, do you guys think I have a chance at some good US schools like Stanford/UCB/Columbia? I don't know if I can fix my GRE verbal with publications. I guess I was just too nervous that time but I really don't have time to redo GRE before coming admission year. Quite tied up with research work.
Thanks a lot for your guidance