CMI is one of the India’s finest research Universities, with programs in Mathematics, Data Science, Computer Science and Physics. The institute benefits from a small student-to-faculty ratio. The diverse community, focus on strong student-faculty ties and commitment to education outside the classroom combine to create a unique learning environment.
To complement its long and distinguished history of academic collaborations, CMI has taken active steps to engage with industry on areas related to the mathematical sciences.
CMI currently has an active R&D collaboration in the area of large-scale formal verification with the Tata Research Development and Design Centre (TRDDC), Pune, a research lab under TataConsultancy Services. Another collaboration is with Honeywell Technologies in the field of verification of avionics software.
In 2015, CMI set up a separate society called Algolabs to foster interaction with industry, notably in the area of analytics, and optimization. Algolabs has conducted numerous short-term training programmes in machine learning, including in-house training for organizations such as Cognizant, Global Analytics, MRF and Tech Mahindra. In addition, Algolabs has undertaken projects in several areas related to analytics and machine learning. The goal is to make Algolabs the first choice solution provider for any industrial problem requiring computational and analytical insight.
Some CMI graduates have created startups. Indraneel Mukherjee (BSc 2006) has a startup in San Francisco dealing with web analytics. Sourasis Roy (BSc 2005, MSc 2007) is co-founder of a Mumbai startup in the area of insurance. Recently, Pratish Gandhi (BSc 2010, MSc 2013) has founded a startup in Bangalore in the area of financial services.
The programs offered in CMI are listed below.
Depending on their interests, students from any of the above programs may take up corporate jobs. The largest number of students participating in campus interviews are from M.Sc. in Data Science, M.Sc. in Computer Science and B.Sc. (Hons.) in Mathematics & Computer Science.
M.Sc. Data Science students take up three month summer internships during May-July after their first year.
M.Sc. Computer Science students write an M.Sc. thesis during January-June in their second year. Some students write the thesis in CMI, while others opt for writing it during a six month industry internship.
Mathematics: Calculus, matrix computations and linear algebra routines, topological data analysis, numerical optimization, discrete mathematics.
Machine Learning: Supervised and unsupervised learning, reinforcement learning, deep learning, neural network, natual language processing, Bayesian networks.
Statistics: Probability theory, sampling distributions, estimation, hypothesis testing, statistical inference, advanced regression, logistic regression, time series and Bayesian data analysis - with R
Computer Science: Design and analysis of algorithms, data mining, graph theory, databases, data structes with Python, distributed computing for big data .
Master of science in computer science is a four semester program. The last semester involves writing an M.Sc. thesis. If a student has completed all other course requirements in the first three semesters, that student is allowed to complete the thesis as part of a six month internship carried out in companies working in relevant areas. Apart from this, students also take up internships during the summer break in May-July. Admission to this program is through a highly competitive national level entrance test. A portion of the students are also admitted from CMI undergraduate batch based on their performance.
While some basic courses are compulsory for all students, there is a lot of flexibility in the form of elective courses. As students realize their interests and goals, they typically specialize in core computer science or in one of the application areas such as machine learning or statistical computation. The courses offered are based on discrete mathematics, algorithms, theory of computation, linear algebra, logic and automata theory, probability and statistics.
Campus interviews are being conducted in CMI for several years now. Some of the major recruiters are Credit-Suisse, Ernst & Young, TRDDC, Adobe, Zen Drive, Teradata, Fresh Works. CMI admits around 50 B.Sc. students and 70 M.Sc. students every year. Following are the statistics for the past few years.
|Year||Maximum Offer||Mean Offer||Median Offer|
|2021-2022||62 lpa||17.6 lpa||16 lpa|
|2020-2021||18.4 lpa||12.99 lpa||13.5 lpa|
|2019-2020||20 lpa||14 lpa||13.35 lpa|
|2018-19||16.54 lpa||12.88 lpa||14.8 lpa|
|2017-18||20 lpa||12.67 lpa||14.8 lpa|
|2016-17||13.5 lpa||9.75 lpa||9.5 lpa|
|2015-16||12.5 lpa||8.75 lpa||8.5 lpa|
|2014-15||9.25 lpa||7.75 lpa||7.5 lpa|
The M.Sc. Data Science program was started in 2018. The students admitted have now completed the first year and all of them found three month summer internships in the industry, for the duration of May-July 2019.
Companies interested is conducting campus
interviews at CMI for permanent jobs or
internships can write to
After the initial contact, the company can send a job description, which is circulated among the students. If a reasonable number of students show interest within a week, the company will be informed. If necessary, we can collect CVs of interested candidates and send them beforehand. We typically give around one week time for the students to give us their latest CV. A date is then fixed for conducting the campus interview.
On the day of the campus interview, company representatives can give a pre-placement talk and conduct written tests and interviews. After we receive the list of selected candidates, we give one week time to convey acceptance of the offers. Following is the timeline for the first round of placements.
A presentation hall will be provided for making pre-placement talks. Written tests can be conducted in the same hall. A computer lab with linux desktops is available for on-line tests. Office rooms for conducting personal interviews will be provided. CMI uses the Reculta platform for streamlining placements processes.