Editing the recommendation Letter draft to make it more praise for the studet
To the Review Committee, I am writing to you in support of Guang Zeng and his desire to your graduate program. Every year, I receive countless requests to write these types of letters, but it is only on behalf of a handful of remarkable students that I take the trouble. I believe whole-heartedly that only those student’s who are most deserving should have a place in any given program, and Mr. Zeng is a very promising data science and quantitive researcher. I first met Guang when he came to apply for a quantitative researcher intern role, along with several other Master of Financial Engineering graduate student. He was the top student in all his classes and his resume included many impressive quantitative research projects and machine learning designs. But what impressed me the most was his chirpy enthusiasm and the importance that he placed on his career path. Where most undergraduate students are content to have a straight-forward schedule of courses, Guang strived to find an internship opportunities and gain qualitative research experience in the real industry. Touched by his motivation and skills, I offered Guang to work on the intern project that Research NLP applications on financial/equity reports to find signals and enhance factor investing. And it was the first time that our company accepted an undergraduate student as an intern. Though Guang has consistently shown his machine learning skills, ingenuity, and willingness to work, the best example of his intelligence shone through when I asked him to build a deep learning model that is capable of classifying the sentiment of stock comment data. For the project, we have around 40k comment data with various noise and categories. Instead of simply train the model by packaged library, he would first feature-engineered filter and process textual data with the TF-IDF framework. Much to my amazement, Guang was able to pro-processed the entire dataset much a head of the due day, leaving the rest of time exploring the innovative machine learning algorithms. The project mentor, Haibo, told me that Guang spent day and night meeting with him to tackle the bugs and issues. This demonstrates the way in which Guang is always prepared to exceed expectations, to work quickly and efficiently, and to take the initiative when necessary. While Guang is perfectly capable of working independently, his interpersonal skills are exemplary and allow him to thrive in a group atmosphere or when speaking publicly. Guang has excellent communication skills. His written work is both clear and concise, as well as interesting to read. He demonstrated his oral articulateness in the every weekly meeting that were a summary of the past work. Jane was highly proficient in extracting information from other colleagues and smoothly point out the issues. He always explained his views very concisely and gave supporting arguments that were both clear and persuasive. I was also impressed by Guang’s innovative ideas and critical thinking ability. During the implementation of the models, Guang propose a novel way of incorporating two neural network into one model to deal with two different types of input—text and features. We accepted his idea and the prediction accuracy improved 5 percentages from the pervious model design. I believe such ideas of innovation will help Guang success in the future academic career of any research field. Guang is unquestionably an exceptional candidate for graduate study in both data science and quantitative finance. Guang’s work in stock sentiment classification suggests that she would greatly benefit from the opportunities for intellectual development provided by a sustained period of graduate study. He has proven himself to have the perseverance, initiative, and intellectual creativity necessary to complete an advanced graduate degree. I would therefore highly recommend Guang Zeng. If his performance in my company is a good indication of how he would perform as a graduate student, he would be an extremely positive asset to your program. If I can be of any further assistance, or provide you with any further information, please do not hesitate to contact me. School list: Harvard Data Science master program 12/01 Harvard Health Data Science master program 12/01 MIT Master of Finance 01/05 MIT MBa 01/05 Yale Asset Management 01/05 Princeton Master of Finance 01/05 Columbia Financial Engineering —rolling Columbia Financial Math —rolling Stanford Data Science 01/05 Upenn Data Science 01/03 Cambridge Master of Finance —rolling Oxford Master of Finance —rolling