From 6ae2a9b49024a746309a8d85c31d8b9a07754c4b Mon Sep 17 00:00:00 2001 From: Wang Ma <118039414+wma17@users.noreply.github.com> Date: Tue, 20 Aug 2024 20:40:26 +0800 Subject: [PATCH] Yua's share (#115) * Create Yua * Delete docs/src/people/Yua * Create me * Add files via upload * Create [US]-20-Yua.md * Update README.md * Update [US]-20-Yua.md * Rename give a reward.png to snacks.png * Update [US]-20-Yua.md * Create me * Add files via upload * Rename give a reward.png to snacks.png * Update [US]-20-Yua.md * Delete docs/src/people/yua directory --- .../math/statistics/README.md | 7 + .../math/statistics/[US]-20-Yua.md | 235 ++++++++++++++++++ docs/grad-application/math/statistics/yua/me | 1 + .../math/statistics/yua/snacks.png | Bin 0 -> 147958 bytes 4 files changed, 243 insertions(+) create mode 100644 docs/grad-application/math/statistics/[US]-20-Yua.md create mode 100644 docs/grad-application/math/statistics/yua/me create mode 100644 docs/grad-application/math/statistics/yua/snacks.png diff --git a/docs/grad-application/math/statistics/README.md b/docs/grad-application/math/statistics/README.md index 519dcf2..0da140b 100644 --- a/docs/grad-application/math/statistics/README.md +++ b/docs/grad-application/math/statistics/README.md @@ -28,3 +28,10 @@ To be continued. ##### 就业: To be continued. + + +## 数据科学与大数据技术 + +#### PhD Programs: + +[20级-Yua-Rensselaer Polytechnic Institute](grad-application/math/statistics/[US]-20-yua.md) diff --git a/docs/grad-application/math/statistics/[US]-20-Yua.md b/docs/grad-application/math/statistics/[US]-20-Yua.md new file mode 100644 index 0000000..e9603af --- /dev/null +++ b/docs/grad-application/math/statistics/[US]-20-Yua.md @@ -0,0 +1,235 @@ +# \[US\]20-Yua-CSE Ph.D.@Rensselaer Polytechnic Institute + + +## 平庸背景的泛计算机博士申请——未曾讲述的故事们 + + + +By Yua + + + + + +### 0 个人背景 + +> [!NOTE] +> +> 2020级统计与数据科学系 数据科学与大数据技术专业 +> +> 成绩:3.42/4.00,rank:18/25(2020秋学期GPA - 2.54/4.00) +> +> TOEFL:98 (R28/L27/S19/W24,准备了10天,口语没法速成w), 无GRE(懒) +> +> 主干课程:数学分析I&II&III、线代精讲、运筹与优化、数理统计、统计线性模型、统计学习|凸优化算法、实变函数、数值分析、随机过程 +> +> 其他知识背景:Reinforcement Learning、Variational Inference,Diffusion Models +> +> +> +> 去向:Rensselaer Polytechnic Institute: PhD in Computer & System Engineering +> +> 主要申请的方向:Machine Learning Theory/ Deep Learning Theory(但要去做Probabilistic Machine Learning了) +> +> 其他申请的项目:CS@Rice,CE@URochester,CS@NEU,CS@ASU,CS@UVA,CS@IUB,CS@TTIC +> +> 申请前面试过的:CS@NJIT,ECE@IowaState,CS@RIT,CS@Auburn,CS@UAlbany + +备注:我在申请前和IUB一位非常厉害的新AP(和我兴趣非常match,做 foundation of deep learning 和 reinforcement learning的)面试过几次,当时从他的语气、表情、说话的内容,我都觉得他肯定会要我了,所以申请的时候放弃了很多面试过的老师,结果这位IUB的老师最后并没有要我,他后来给出的理由是我的口语太低不能给我TA offer(这个是委婉的拒辞。他最后一次面试明确和我说过我这个英语成绩是问题不大的、哪怕是TA offer,也可以入学后先参加课程和测试;他还提到他的funding比较充足(真的给暗示拉满了,但最后没要我😭)。幸好后来RPI有一位正教授捞了我,让我这么激进的申请有个还不错的结果。 + + + +### 1 首先最强烈推荐 + +16级数学系徐源诚学长:[PhD申请的“游戏规则”、科研、英语、绩点与其他](https://sustech-application.com/?utm_source=online#/grad-application/math/applied-mathematics/[US]-16-xuyuancheng) + +> [!IMPORTANT] +> +> 推荐信(research-based) > 高质量研究经历 > (本科学校/教育背景,项目本身申请难度) > (GPA/年级排名,课程,与项目的fit程度,套磁) > (SOP, 托福口语,性别,面试,GRE Sub) > (托福,GRE) > 奖项/学生工作 >= 0 >(黑推,灌水的工作,虚假的申请资料) + +之后的讨论里,我尽量避免内容和徐源诚学长的文章过度重复。 + + + +### 2 (作为一个南科大的学生,申请的话)我该考虑哪些学校的PhD/研究型项目? + +> [!TIP] +> +> For AI/ML,CSranking美国前70的学校都是可以考虑的!(排名只是参考!参考!参考!!!) +> +> https://csrankings.org/#/fromyear/2019/toyear/2024/index?ai&vision&mlmining&nlp&inforet&us + +> [!CAUTION] +> +> 美国学校的择校非常复杂,较为简单的方法是**找到这个学校的中国博士生,然后去看他们的履历,如果他们本硕的水平与南科大差不多(中等、中上985),那这个学校就是可以考虑的**。 +> +> 目标是毕业后就回国的话(尤其是希望去传统高校、国企、公务员等),需要考虑到世界排名。 +> +> 一个北美硕士的经历能够**一定范围内**让你申请PhD更加简单。(我认识一位本科GPA3.2的华五学生,在美国1年制硕士之后去了csranking美国前50的学校读计算机博士) + + + + +**个人其他有印象的:研究向**(括号里是我知道的一些老师/补充的信息) + +> [!NOTE] +> +> 港新:大家熟知的7所。 +> +> 欧洲和澳洲我不太熟。 +> +> +> 日本(SGU英文项目): +> +> 1. 东京大学 (Suzuki Taiji +> 2. 东京工业大学 (**IGP项目** Sakuma Jun,Kanamori Takafumi,Watanabe Sumio +> 3. 东北大学(去年新设立一个NLP研究中心 +> 4. 早稻田大学 +> 5. 大阪大学(Fujisaki Yasumasa +> 6. OIST:Okinawa Institute of Sicence and Technology 只颁发5年博士学位、纯英环境(日本人占比仅30%)、在美丽的冲绳、宣传片:【OIST - University of the Future 新時代の教育研究を切り拓く】 https://www.bilibili.com/video/BV1yW411a7TG/?share_source=copy_web&vd_source=6996eff0c0f4047c83d18791025d4a1e +> 7. Naist/Jaist 大学院大学(研究生院) +> +> 韩国: +> +> 1. Kaist(Junmo Kim,本硕博奖学金全覆盖、纯英环境 +> +> 欧亚其他地区学校: +> +> 1. Kaust +> 2. MBZUAI:Mohamed bin Zayed University of Artificial Intelligence 沙特、前年成立、专攻人工智能的大学、Eric Xing去做校长了 +> 3. Tel Aviv University ,以色列 +> 4. Singapore Management University 新加坡管理大学,新学校、有些履历不错的老师 +> 5. Max Planck Institute +> 6. 上海纽约大学*, +> 7. 西湖大学(可以招收没有保研资格的直博生),浙大/复旦联培 + + + +### 3 (野路子)如何找目标导师? + +1. 目标学校的官网一个一个看(或者 Google “学校 + 研究方向 + lab/group”,比如Google 搜索 “University of Florida Machine Learning lab” + +2. 看论文找到感兴趣的课题组 + +3. 一亩三分地研究生申请、导师招生等板块 + +4. **一些微信公众号/知乎/小红书**,会推哪些老师在招生 + + 公众号:Ivynue工作室、AI求职、北美PhDLeague、ConnectED、科研Doge、研真清 + +5. 养好一个的推特账号(关注一大堆相关方向的教授、学者 ->继续关注推特给你推荐的其他相关的账户 -> 申请季能刷到相关的招生帖子 -> 去点开、点赞这些帖子 -> 推送更多相关的内容) + + 那些老师,做了什么研究、组里有什么进展-->就会发推特 + + **Remark.** 我通过这个方法收集了大量相关领域的老师、甚至和其中一人加了好友,当然他们都在很厉害的学校也不缺厉害的学生,我基本上够不到他们的bar,但其中有一位老师非常热心和我聊了很多,我们加了微信、打了微信电话。他给我讲了科研和申请的东西,我受益很多。 + +6. 关注到一些即将毕业、在academic market的博士/博后;一些学术会议/组织评选的Rising Stars(高年级博士生、博后、年轻的助理教授 --> 正在、即将招生),例如:马毅教授搞的CPAL评选的rising star:https://2024.cpal.cc/rising_stars_awardees/ + +找到老师后,发个邮件问候一下呗~(套瓷 + + + +### 4 什么样的导师呢?大佬/新AP/避雷华人女AP?? + +> [!CAUTION] +> +> ***没有绝对的标准,在这里尽量case by case地考虑!(通过你面试时自己的体验)*** + +以下只是一些听说/自己理解的小想法,不能作为一个可靠绝对的标准! + +1. 新AP(助理教授)通常比较积极回复邮件、安排面试。但是他们对于学生的能力要求可能会比较高(数学功底、推公式能力好//代码功底、做项目好)、需要你一过去就能尽快开始做东西(即战力 +2. tenured的老师(副教授、正教授)可能太早套瓷没有什么用(10月、11月之后可以开始套瓷了),他们不是很缺学生(去主页里看看组里有多少人,有人写代码、有人推公式,课题组结构比较完整)。但组里各方面比较完整的话,他们不急着你做东西,对学生的“完成度”要求会稍微低一些(可能会招不同背景的学生来开一个新方向// 老师觉得你有潜力、想慢慢培养你 +3. 相对门槛可能比较低的是,组里正常运转了2-4年的AP,这时组里学生数量够(但是有人要毕业了、需要有人填空子),科研稳步推进,老师可能拿到了新的funding,有意愿招人来做东西(但对于“即战力”需求低一点 + +总而言之还是case by case,看到了方向感兴趣的、长得好看的、你觉得会喜欢的老师就发个邮件问问吧! + + + +#### 老师招不招学生? + +1. 有写招学生的一定招 +2. 关注组里人多不多、今年是不是会毕业几个(例子:组里8个人,有5个要毕业了 +3. 看看老师最近有没有拿到funding +4. 发条邮件问问 + + + +### 5 老师说了xxx,是不是就算稳了? + +> [!Caution] +> +> ***在拿到正式Offer之前,一切的“口头承诺”都不能完全相信!*** + +你会见到包括但不限于以下的情况: + +1. 老师在面试时候说了会在短期内给你发offer(“口头offer” +2. 老师说会在n周/1个月后给你结果(说明你在他的waitlist上,他在等排在你前面的人的结果;例子:面试了5个人,排序1-5,你是第五个,老师给每个人1周时间答复。1-2-3-4-==5==(老师一个月后) +3. 老师疯狂给你各种心理暗示(夸你、表达很想要你),但是没有明说给你offer或者给你说什么时候有结果(不可信,你该申请、该面试都还是继续做 +4. 明明面试时大家和声和气非常愉快,然后就联系不到老师了??他不再回复你了(很显然,老师不太想要你 +5. …… + +但是,虽然说不能完全相信、信任,我们也要把握好分寸,做一个礼貌、有道德的人。要及时回复老师的邮件、和老师follow up的时候语气要平和( + +在最终结果(offer)出来之前,你都可以/应该去为自己争取出路,这不是做海王!对面老师没有给你一个确切答复的情况下,你去寻找其他出路都是合理的(这不是不道德的!) + + + +(某种意义上)北美PhD申请的理想的时间线: + +​ (大四) + +1. 9-11月:丰富完善背景(研究、成绩、英语一类的)、陶瓷(给老师发邮件)、面试 +2. 11-12月:和一些老师进行了多轮面试,拿到了几个口头offer +3. 12月:提交了所有的申请,对于最想去的老师,follow up一下(表达他是你的top choice、非常想去);给这个老师发了之后,可以再给其他想去的老师发一些update(这时就不要明说是“top choice”了,要诚实) +4. 12月底-2月初:拿到了一些新的面试机会、(可能)收到了一些老师给的正式offe(在==gradcafe==/1亩3分地上看看申请的项目的情况)。1月中如果还没有面试(工科类)的话可以考虑发邮件继续“求爱”,要主动!对于已经确定不会去的项目,早早拒绝。 +5. 3月中旬:基本拿到了所有可能的offer(3月中旬往后还能有offer就是真的开奖、运气好了),做出最后的选择。 + +### 6 其他闲聊 + +> [!TIP] +> +> **为什么出国读PhD?** +> +> 因为想做。回顾以往,让我总是后悔的往往是“没能做xx”,做了的事、无论结果如何,我都能从中成长、看到它的价值与意义;而没有做的事情,只会“后悔的要死”。 +> +> **读硕与读博?** +> +> - 硕士:就业导向?/博士的跳板?境内理工科硕士也要做科研、可以作为“跳板”,优点是花销比较小,缺点是时间久(3年)、可能没有宿舍住/宿舍条件一般、思政课、公共课会占用大量时间。境外硕士以授课项目为主(当然也有mphil、研究性硕士)、没有毕业论文要求,没有自我驱动力的话很难坚定做科研作为跳板升学(但是能坚持下来的话,机会是比在境内多),花销高、需要克服生活语言压力,时间太短可能一开学就要准备找工作了。 +> - 博士:AI领域在业界的科研也很活跃,很多大公司都有研究岗位、实验室,博士毕业后不仅可以去高校学术界、还可以去业界的研究岗位就业(接触实际问题和数据,更好用所学推动人工智能发展!)。直博省时间,但是没有很好背景的话现在申请AI方向的博士真的很难!想要去top校的话,要么本科履历拉满(推荐信很重要),要么就靠gap/硕士刷科研吧(谁知道自己的进步速度赶不赶得上top校门槛提升的速度呢)! +> +> **本科做科研** +> +> 我本科没有完整的项目经历,我一直属于一个“游走”的状态,看过很多领域的东西,一直没有坚定的做哪个。以前我总觉得要做有深刻价值、自己最感兴趣的工作(与未来想做的方向match的工作)。对于潜在的导师来说,这个学生看起来很灵光知道很多,但是他没有一个完整的项目经历的背书,没有办法确定这个学生能从头handle一个科研项目,大部分年轻老师不愿承担这个风险。因此 +> +> 1. 还是要“有点东西”的,有一个自己主导的从头到尾的科研项目来证明自己有这样一个完整的经历及其相应的耐心与基础能力 +> 2. 质量要走在数量前面,宁愿项目不完整、也要能详细说出来自己的工作亮点体现在哪里 +> +> 其他一些建议: +> +> 1. 在读论文的时候可以写notes(xx论文读后笔记)、blogs然后放在个人主页上/drive/github/知乎上,联系老师/申请的时候附上连接,这样哪怕没有一个很好的研究项目经历,也能展示到你确实学到了一些advanced的东西 +> +> **GAP -> 顶尖学校PhD?** +> +> 这是个可行、已经有很多人走过的方法。Bolei Zhou在香港的时候host了很多华五本科的gap的学生,后来那些人都去了很好的学校读PhD(https://boleizhou.github.io/lab/)。但这个需要早早规划,尽量在大三春季就能找到要跟的导师、早早开始做科研出成果。(大四毕业之后去做RA,==只想空1年==,那就是大四毕业后的12月就开始申请了/ 大三春季就找老师、作准备,这个时候就有大四一年+大四毕业之后半年持续的做科研时间 +> +> **机遇?** +> +> 很多好学校投入很多来建设人工智能领域的学科(USC的计算机系收到了10亿美元的资助、UIUC计算机系去年新招了十个AP,如果一个人招3学生,多招30个phd);留美H1B工签难抽、有人为了留美选择去普通的学校做AP(很多人背景回国能去很好的985的,但还是选择了美国国内可能100名守门员的学校),里面还是有背景和科研很厉害的老师的。 +> +> **收过南科大学生的老师、院系、学校会更倾向收南科大学生** +> +> 一些AI/ML领域和南科大有关的学长学姐老师学校: +> +> 16级Yuancheng Xu@Maryland Furong Huang|15级数学系 Yansong Li@UIC Shuo Han |17级统计系 Mingshuo Liu@UC Davis|18级统计系Chongyang Shi、19级统计系Xinyi Wei@UF Jie FU|19级Shengjie Niu@PolyU Jian Huang|18级数学系Junze Deng@OSU Yingbin Liang|17级Peiyao Xiao、17级数学系Yujie Zhu@Buffalo Kaiyi Ji|15级计算机系Xiangyi Yan@UCI Xiaohui Xie|16级计算机系Yutong Wang@UC Davis|16级统计系Yun Zhang@HKUSTGZ Wenjia Wang|15级数学系Yushun Zhang@CUHKSZ Zhiquan Luo|16级计算机系Songlin Yang@MIT Yoon Kim +> +> **跨专业申请** +> +> 理论上统计/数据科学->计算机/ECE是跨专业,在没有和目标导师沟通的前提下,可能会因为==课程背景匹配度==等的问题在很早就被刷掉。 +> +> Contact: maw6@rpi.edu + + + +**请作者吃点小零食**: + +![snacks](/yua/snacks.png) diff --git a/docs/grad-application/math/statistics/yua/me b/docs/grad-application/math/statistics/yua/me new file mode 100644 index 0000000..8b13789 --- 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