Department of Mathematics

"Without mathematics, there's nothing you can do. Everything around you is mathematics. Everything around you is numbers"- Shakuntala Devi Mathematics has always played a crucial role in our endeavor to understand the nature of the physical universe and in the continuing development of our technological society. There has also been a time-honored practice that distinguishes the importance of pure mathematics for its aesthetic appeal to the human spirit. Many students decide to study mathematics for one or both of these reasons. Students also study mathematics in order to develop and improve their critical and analytical skills that can significantly contribute to many personal goals. Most certainly the study of mathematics can lead directly to interesting employment opportunities in the field of mathematical sciences and to higher studies. Over the last few decades the rapid pace of research and development in, computers and modern technology has led to new requirement for more mathematical expertise, and the need to nurture a new generation of mathematically competent men and women has never been more crucial. Mathematics is utilized around the world as an indispensable tool in numerous fields, including natural science, engineering, medicine, finance and the social sciences.

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After Class 12

3 Years B.Sc in Mathematics


After Graduation

2 Years M.Sc


After Post Graduation

Ph.D (Full time)

Ph.D (Part time)

Step 1: Make online Application at http://www.technoindiauniversity.ac.in

Step 2: Complete application form with every detail. Submit your Registered mail- id and mobile number to receive our confirmation

Step 3: Acknowledgement of application through sms and email.

Step 4: Confirmation of appearing in examination will be sent via email or sms after filling up form. A unique application id will be generated. Candidate is required to appear for entrance examination with the id.

Step 5: Final Admission and Registration with payment of requisite fees.

After Class 12

3 Years B.Sc in Mathematics


After Graduation

2 Years M.Sc in Mathematics




Our Current Application Areas Include:

Mathematical Modeling for Real-World Systems

Our current application areas include the formulation and analysis of mathematical models to represent complex real-world phenomena in engineering, physics, biology, and economics. Students learn how differential equations, linear algebra, and optimization techniques can be applied to model systems such as population dynamics, fluid flow, and economic behavior. This approach enables learners to connect abstract theory with practical problem-solving and decision-making

Data Science, Statistics, and Predictive Analytics

Our department emphasizes the use of probability theory and statistical methods to analyze and interpret real-world data. Students are trained in regression, hypothesis testing, and stochastic processes to extract meaningful insights and support data-driven decisions. This area prepares learners for applications in finance, healthcare, and emerging data-centric industries

Graph Theory and Network Analysis

Our current application areas include the study of networks through graph theory, with applications in communication systems, transportation, and social network analysis. Students explore concepts such as connectivity, shortest paths, and network optimization, enabling them to understand and design efficient and scalable systems in modern technological environments

Optimization Techniques and Operations Research

We focus on mathematical optimization methods used to achieve the best possible outcomes under given constraints. Students learn linear programming, nonlinear optimization, and decision-making strategies applied in logistics, supply chain management, resource allocation, and industrial planning. This area highlights the role of mathematics in improving efficiency and performance in real-world systems

Mathematical Foundations of Artificial Intelligence

Our current application areas include the study of core mathematical principles underlying artificial intelligence, such as linear algebra, probability, and multivariable calculus. Students understand how these concepts drive machine learning models and intelligent systems, enabling accurate predictions, pattern recognition, and automated decision-making