Computer Science and Engineering

CSED
CSED
CSED
CSED

Department of Computer Science & Engineering (CSED) at Institute of Engineering & Technology Lucknow (IET-L) was started since its establishment in 1984 and became the place of top-ranking students of state entrance examination (UPSEE) over past decades. The [email protected] is a premier and dynamic center for imparting quality education and known for excellence in teaching in the field of computer science in the state of Uttar Pradesh. 

The department offers B. Tech. programme in Computer Science & Engineering and PhD programme in Computer Science & Engineering. The department is a center for advanced studies, keeping pace with the latest in the rapidly changing environment of information technology. It has been a consistent endeavour of the department to adapt itself and its programmers to mirror the requirements of the constantly evolving IT environment in India and abroad.

The curriculum of B. Tech. programme in Computer Science & Engineering comprehensively covers the topics related to computing and information technology with an emphasis on practical learning. The educational ecosystem and up-to-date course structure prepare our students adaptive with the latest developments in computer science & engineering.   

The faculty members of the [email protected] hold strong academic credentials and delivers expert classroom lectures supported from their strong research experience. The department has state-of-the-art infrastructure and computing laboratories. All laboratories are facilitated by high-speed ethernet and wireless networks.

For more information regarding research activities at [email protected]please visit the faculty and research pages.

Vision of Department

To contribute at national and international scenario through excellence in science and technology by providing a transformative education and research in the field of computer science and engineering and to cultivate the attitude and skills of employability, entrepreneurship, start-up among students so that they can become a valuable resource not only for the industry but also for the society.

Mission of Department

M1. To achieve high academic standards and values to prepare computer science professionals who can augment the industrial, educational, research, innovations and social needs of the nation and the world at large.

M2. To provide the education to the students by rigorous course work etc. in such a way that they should be an excellent technocrat.

M3. To develop human technical potential to its fullest extent so that intellectually capable and imaginatively gifted leaders can emerge in a range of professions to achieve the needs of society and industry.

M4. To preserve the core values as an enduring principle adopted by the department are integrity, excellence, transparency, and empathy.

 

The Program Educational Objectives (PEOs) of B. Tech. programme in Computer Science & Engineering are given below:

PEO1. The students will be able to formulate and analyze engineering problems of various domains that may require sound foundation of mathematics, scientific reasoning and computer engineering fundamentals.

PEO2. The students will be able to use techniques, tools and skills in areas aspiring for innovative solutions to challenging problems of Industry and day-to-day life.

PEO3. The students will be able to contribute effectively and efficiently in varying roles of teamwork along with the practice of ethical and moral values.

The Program Specific Objectives (PSOs) of B. Tech. programme in Computer Science & Engineering are given below:

PSO1: Possess strong mathematical & algorithmic skills and background in core subjects of computer science to appreciate the problems of various diverse domains along with standard tools and technologies in practice to make perfect suitability for industry, academia and research organizations.

PSO2: Use techniques of mathematical abstractions and modelling for formulating real-world problems of various domains and design solutions.

PSO3: Possess knowledge and skills to understand, analyze and develop the strategy in the upcoming areas like data science and some specialized area of computer science intending to emulate human intelligence such as machine learning, computer vision, pattern recognition, Natural language processing.

LABORATORIES IN COMPUTER SCIENCE & ENGINEERING DEPARTMENT

The department of [email protected] has a number of course-specific laboratories with state-of-the-art systems. Each laboratory has 30-60 numbers of core i7 Intel 3.4 GHz with 8GB RAM and 1TB HDD desktops connected to 24x7 high-speed Internet connections. The laboratories are supported using Windows10 and Linux operating systems. 

 

DEPARTMENTAL COMMITTEES

Department UG Programme Committee (DUGC)

Department PG Programme Committee (DPGC)

Programme Assessment and Quality Improvement Committee (PAQIC)

Departmental Budget Committee

Laboratory Management Committee

Departmental Procurement Committee

Departmental Ethics & Disciplinary Committee

Student Grievance Redressal Committee

 

OTHER ACTIVITIES

FACULTY SUPERVISORS

PROJECT COORDINATOR

INTERNSHIP COORDINATOR

STUDENT GRIEVANCE REDRESSAL SYSTEM (SGRS)

DR SARVEPALLI RADHAKRISHNAN LECTURE SERIES

DEPARTMENTAL SOCIETIES

DEPARTMENTAL LIBRARY

DIGITAL LIBRARY

 

Courses Offered

Under Graduate
Dept Programme Specialization Intake Started In
Under Graduate CSE Bachelor of Technology Computer Science and Engineering 60 1984

Regular Faculty

Note: The following list is sorted alphabetically

Contractual Faculty

Name Sort descending Designation E-Mail
Er. Deepali Avasthi Assistant Professor (Contract) [email protected]
Er. Pratibha Pandey Assistant Professor (Contract) [email protected]

FDP/Seminar/Lectures Organized

Title Duration Status Type
Deep Learning - National Expert Lecture
Pervasive use of Artificial Intelligence in Industry - National Expert Lecture
Green Computing through Adaptive Multi-core Architectures - National Expert Lecture
UI Designing and Programming - National Short Term Course
Large Scale Least Squares Non-parallel SVM - National Expert Lecture
Support Vector Machines for Classification and Regression Problems - National Expert Lecture
Python Programming & Django Framework - National Workshop
Machine Learning using Python - National Workshop
Python and its Applications with IOT - National Workshop
Soft Computing Approaches and its Applications - National FDP