B.Tech in Mathematics & Computing

Indian Institute of Petroleum and Energy

IIPE Campus

B.Tech in Mathematics & Computing

Mathematics Driving Intelligence: Developing the Next Generation of AI, Machine Learning and Data Science Innovators.

B.Tech in Mathematics & Computing

4-Year ProgramIntake: 22 StudentsJEE Advanced

Vision

To produce future leaders at the forefront of research, development, and innovation in futuristic disciplines that require deep use of Mathematics, Computer Science, and Data Science. The program emphasizes AI and ML, attracting the nation's brightest minds through the JEE Advanced examination.

Core Focus

The curriculum concentrates on areas where Mathematics and Computing are most relevant and inter-laced. It provides a perfect platform for those seeking strong Mathematical and Analytical components with specialization in topics like AI/ML/DS/Energy.

Background

Recent ground-breaking mathematical developments have far reaching implications on daily life, from mathematical modelling and large scale optimization to data-driven strategies for solving PDEs and mimicking neural processing. These advancements underpin emerging fields like Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, and Data Science (DS).

With vast potential for applications, these fundamental topics, not surprisingly, have become cynosure for researchers from several scientific fields while resulting in products like Chat GPT, high precision imaging in medical domain, physics-aware neural processing etc.

At the heart of these developments lie some deep rooted advanced mathematical, computational, and data analytic tools, which form the foundational pillars of emerging fields like Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, and Data Science (DS). Recognizing the need for trained manpower, IIPE Visakhapatnam proposes this 4-year B.Tech. programme.

Admissions

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Selection Process

Admission is based on JEE Advanced ranking. Qualified candidates apply for IIPE BTech Admissions.

Important Dates

JEE Advanced: May 2025
IIPE Admissions: June-July 2025
Classes Begin: August 2025

Co-ordinator

Ramunaidu Randhi

Ramunaidu Randhi

Associate Professor, Mathematics

Sparse Representation Theory (Compressed Sensing), Deep Learning and Model-based AI, Machine Learning, Finite Frame Theory

Program Highlights

  • Strong foundation in Mathematics and Computer Science
  • Specialization in AI, ML, and Data Science
  • Industry-relevant curriculum
  • Hands-on practical training

Career Opportunities

  • Data Scientist
  • Machine Learning Engineer
  • AI Researcher
  • Computational Scientist
  • Software Developer

Program Structure

The program consists of 165 credits distributed across 8 semesters with a balanced mix of core courses and electives.

Institute Core66 credits
Departmental Core70 credits
Departmental Elective12 credits
Open Elective17 credits
View Program Structure

Faculty

Veerabhadra Rao C

Veerabhadra Rao C

Associate Professor, Computer Science and Engineering

Distributed Systems, Algorithms, AI & ML

Ramunaidu Randhi

Ramunaidu Randhi

Associate Professor, Mathematics

Sparse Representation Theory (Compressed Sensing), Deep Learning and Model-based AI, Machine Learning, Finite Frame Theory

S. Rathan

Rathan Samala

Assistant Professor, Mathematics

Computational Methods for (Partial) Differential Equations, Hyperbolic conservation laws, Nonlocal conservation laws: applications to traffic flows, Shock capturing schemes: ENO and WENO

Seshagiri Rao Ambati

Seshagiri Rao Ambati

Professor, Department of Chemical Engineering

Process Control, Wastewater Treatment, Process Dynamics, Hybrid Energy Systems, Flow Batteries

Venkata Reddy P

Venkata Reddy P

Associate Professor, Department of Chemical Engineering

Process Systems Engineering, Water Distribution Networks, Cyber Physical Systems, Security of Critical Infrastructures, Machine Learning applications in Process Design, Fault detection and isolation

Hemanth Kumar Tanneru

Hemanth Kumar Tanneru

Associate Professor, Department of Chemical Engineering

Systems Engineering, Data Analytics and Machine Learning, Waste to Value

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