Meet the Incoming Master’s Class

The incoming master's class is filled with bright students from across the country and around the world. From 1,200 applicants, the institute admitted 143 new master's students - an acceptance rate of 11 percent. The class has 92 international students (64 percent) and 51 Americans (36 percent). Overall, the students say they were drawn to DSI due to its strong academic reputation, its rich curriculum, prominent professors and its location in New York City.

Most (63) earned their undergraduate degree more than two years ago; 25 earned their bachelor’s within two years of enrolling at DSI, while 55 of them got their degrees within a year of enrolling.

The academic profile of the class is also exceptional. The average undergraduate GPA score is a 3.7, and average GRE scores are 166 in quantitative and 157 in verbal. The average TOEFL score is 106.5.

The gender mix in the class is well balanced, with women making up 45 percent of the class and men 55 percent. Of the international students, 44 come from China, 24 from India and the remainder are from 19 countries. In terms of their academic backgrounds, more than half, or 59 percent, have technical degrees, whereas 22 percent studied math or statistics and 19 percent have non-technical degrees.

What follow are short profiles of three students. Read together, the stories personify the intellectual prowess of the incoming master’s class.   


Manksh Gupta
Manksh Gupta

Manksh Gupta earned a bachelor’s degree in statistics from the University of Delhi in just three years. Though he accelerated his studies, he still graduated third in his class. One summer, he also studied at the London School of Economics. There, he took an interest in econometrics, a subfield of economics that’s rife with data. His professors noticed his talent for analyzing data and encouraged him to study data science.

His interest in the field was further piqued when he worked as a data-science intern for AbsolutData, where he used machine learning, classification models and algorithms to analyze data. All of these techniques were new to him, so he signed up for an online Columbia Edx course in data science. He also started to read deeply in the field and discovered the works of David Blei and John Paisley, two prominent DSI professors. He decided to study data science at the graduate level and applied to DSI. To his delight, he was accepted.

Now, he’s studying with the same professors whose works he had read and loved. And though he’s been at DSI for just two months, he’s already assisting Professor Patricia Culligan with research relating to energy conservation in buildings in New York City. After he graduates, his intends to to work as a data scientist for a big tech company. He also recently interviewed for a summer internship at Apple, which he’s hopeful he’ll get. Meanwhile, he’s happy to be studying at DSI.

“The classes are all interesting,” he says, “and I can’t believe I’m studying with the best professors in the field whose work I read with great interest just a few months ago in New Delhi. It’s fantastic.”


Alexandra Hosa grew up in Poland, where she excelled in math, science and “all things geo,” as in geography and geology. During high school, she participated in Poland’s Geographical Olympiad, where for three competitions she was named a national laureate. When a senior in high school, while still living in Poland, she applied to MIT. She was admitted, and received a bachelor’s and a master’s in geoscience from MIT. She entered a doctoral program at the California Institute of Technology but switched after a year to the University of Edinburgh, from which she earned a Ph.D.

Alexandra Hosa
Alexandra Hosa

While studying at Edinburgh, she designed and coded a model for simulating the properties of synthetic rocks - a project that generated a great deal of data. Over time, she found that ‘the most fun part of the project wasworking with the data - all the way from cleaning it, to uncovering trends and figuring out how to best visualize my findings,” she says. And that’s what prompted her to decide to focus on data science. She eventually left Scotland for New York and enrolled in DSI. The master’s program here, she says, is the best way for her to learn the skills she needs to work as a data scientist.

“I’m very excited to be a part of the dynamically developing Data Science Institute,” adds Hosa. “After I graduate I’m open to working in different types of industries such media, tech, and finance but I hope to work for the industry that allows me to make the greatest impact on society.”


Mohamed Maskani Filali speaks six languages and knows six programming languages. He grew up in Morocco, studied in Paris and now lives in New York City. He loves to travel -- he’s visited 25 countries -- and discover the joys of foreign cultures, may it be their food, music, language or technology.

During high school in Morocco, Filali won a scholarship to study at Télécom ParisTech, one of the top research universities, or Grandes Écoles, in France. He majored in data science and specialized in advanced probabilities and statistics, machine learning and convex optimization.

He also has solid work experience.  Earlier this year, he worked as a machine-learning scientist/intern for Teads.TV, an online advertising companyin Paris. Using Scala and Spark, he implemented a machine model to predict the view-through rate of video-display ads.

Before that, he worked as a machine-learning and time-series R&D intern at Bio Serenity, a Paris-based company that does high-tech engineering, medical development and big data analytics. He used machine-learning algorithms to predict the presence of epileptic spikes in brain signals and contributed to a paper that has been accepted at the International Conference of the IEEE Engineering in Medicine and Biology Society. Using pandas and scikit-learn, he also implemented Bio Serenity's internal python library for detecting and visualizing epileptic brain patterns.  

Mohamed Maskani Filali
Mohamed Maskani Filali

While still in university, he participated in a Kaggle competition where he used machine learning and natural language processing to detect insults in social media. His project had an accuracy rate of 82 percent, ranking him second out of 100 participants.

A skilled researcher, Filali now helps DSI Professor Andreas Müller develop scikit-learn features.Müller co-manages scikit-learn, a machine-learning library for Python.

After he gets his masters, Filali says he’d like to work for a large technology firm and manage a data science team. He likes the technical side of data science, especially machine learning, but also enjoys communicate his findings to lay audiences, which he can do in six languages.  

“I left my home in Morocco to study in Paris and I’ve been independent ever since,” he says. “I love to discover new cultures and always wanted to come to the U.S.  Now I’m here and enjoying my studies and research at DSI while living in another major international city.”


--By Robert Florida

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