eastVillageWest

Hey guys! As the title is saying, I want to pursue my PhD in PDE or ML after my master and i'm going to pursue my master soon after I graduate from my college, but i don't know how to be prepared to apply in fall 2020. So a little about myself first, I'm at my senior year majoring in Financial Mathematics at a public university in NYC (GPA: 3.8); A/A- at my math classes, and took two graduate level math class; I won some national trading competitions (cause I wanted to do quant research before... ); currently doing some Deep learning/PDE research work with a professor. I planned to do QR right after my graduation, but my passion for pure math won. But as you may realize, it's a bit difficult for me to apply to PhD last fall (I didn't have any research experience or any conference/presentation... ), and as my professor suggested, I applied for some math programs offering master degree to get some research experience. I recently heard back from Johns Hopkins Financial Mathematics program, they will provide me 25% scholarship, and also UW at Seattle for CFRM. I know my background is not strong at all. But I do want to pursue my PhD at NYU Courant/MIT/Stanford/Berkeley (almost all my math professors are from the four, and i love them!). I just wanna know what to do during the first year of master (it's gonna be a 1.5 year program) to apply to them in 2020 fall and which school I should choose to have a better edge. As my professors are saying, UW has a very good applied math department and J.Nathan Kutz is pretty good at DL; but i guess Johns Hopkins has a bit better stats department (they rank almost the same for that...) and a better name (i guess?). I do hope the program I choose goes hard on math proofs and have better way to provide opportunity for PhD path. I'd love to hear all of your ideas! Thanks in advance.

Hey guys! As the title is saying, I want to pursue my PhD in PDE or ML after my master and i'm going to pursue my master soon after I graduate from my college, but i don't know how to be prepared to apply in fall 2020. So a little about myself first, I'm at my senior year majoring in Financial Mathematics at a public university in NYC (GPA: 3.8); A/A- at my math classes, and took two graduate level math class; I won some national trading competitions (cause I wanted to do quant research before... ); currently doing some Deep learning/PDE research work with a professor. I planned to do QR right after my graduation, but my passion for pure math won. But as you may realize, it's a bit difficult for me to apply to PhD last fall (I didn't have any research experience or any conference/presentation... ), and as my professor suggested, I applied for some math programs offering master degree to get some research experience. I recently heard back from Johns Hopkins Financial Mathematics program, they will provide me 25% scholarship, and also UW at Seattle for CFRM. I know my background is not strong at all. But I do want to pursue my PhD at NYU Courant/MIT/Stanford/Berkeley (almost all my math professors are from the four, and i love them!). I just wanna know what to do during the first year of master (it's gonna be a 1.5 year program) to apply to them in 2020 fall and which school I should choose to have a better edge. As my professors are saying, UW has a very good applied math department and J.Nathan Kutz is pretty good at DL; but i guess Johns Hopkins has a bit better stats department (they rank almost the same for that...) and a better name (i guess?). I do hope the program I choose goes hard on math proofs and have better way to provide opportunity for PhD path. I'd love to hear all of your ideas! Thanks in advance.