Computer Science and Engineering (NBA Accredited)

The Computer Science and Engineering Department was established in the year 2001 with the vision to offer Bachelor of Engineering degree in Computer Science & Engineering and impart world class education to the students. A group of well qualified, experienced and highly motivated faculty is engaged in providing quality education to the future computer engineer and keeping them abreast of the fast technological development.

The well equipped laboratories help students to meet ever increasing technological and social challenges with its traditions of self discipline, hard work and a creative approach to solve exigent issues. In addition the Department regularly organizes a series of lectures by academicians and professionals of the highest repute, which lay stress on the latest innovative technologies in the field of Computer Science and Engineering and Information Technology.

VISION

To maintain academic excellence aiming to produce competent technocrats imbibed with ethical values to serve the national emerging technological needs.

 

MISSION

M1: To impart quality engineering education to the students by providing effective teaching learning, research and application based innovative environment.

M2: To inculcate creativity team-spirit, leadership and ethical competence through continuous collective curricular, co-curricular and extracurricular activities.

 

PROGRAM EDUCATIONAL OBJECTIVES (PEOs)

PEO1: To acquire a deep insight in mathematical, scientific & analytical skills and adopt self-motivating lifelong learning to explore cutting edge technologies.

PEO2: To prepare graduate to meet the evolving technological needs of the country by promoting innovation, ethical practice and a commitment to serving society.

PEO3: To acquire necessary technical knowledge to pursue successful professional career posing leadership and team spirit.

 

PROGRAM OUTCOMES (POs)

Engineering Graduates will be able to:

  1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  1. Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
  1. Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
  1. Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
  1. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
  1. The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
  1. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and the need for sustainable development.
  1. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  1. Individual and teamwork: Function effectively as an individual, and as a member or leader diverse teams, and in multidisciplinary settings.
  1. Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
  1. Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
  1. Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change

 

PROGRAM SPECIFIC OUTCOMES (PSOs)

  1. Ability to demonstrate the comprehended fundamentals of computer engineering to resolve mathematical and computational problems.
  2. Ability to explore evolutionary changes in computing by skills acquired through computer engineering principles and provide solution through innovative ideas.
  3. Ability to imbibe knowledge in modern computer environment and languages to gain additional skills for successful career and higher studies.

 

CSE Facebook Page 

     https://www.facebook.com/Csemsit-2004225629667348/?modal=admin_todo_tour

 

CSE MSIT ALUMINI

   https://www.facebook.com/groups/557388331376102/

Department of Computer Science & Engineering

 

The computer labs in the CSE department are equipped with high-quality computers and software with good configurations. Students, faculty, and staff all have access to these labs, which offer various tools and technologies for a wide range of tasks such as creating websites, editing documents, completing class assignments, sending emails, conducting data analyses, and accessing library resources. Microsoft Windows software is available for word processing, statistics, spreadsheet work, and database management. Furthermore, a wide selection of other software programs are also available for use. The department consists of multiple labs, and the specifics of each lab are outlined below:

 

Lab (#105)-CN LAB / PYTHON LAB
 

System Configuration: 

● DELL Desktop Intel Core™ 10700 CPU @2.90 GHz, i7 10th Generation, 8GB DDR4 RAM,
1TB HDD, keyboard, Optical USB Mouse, TFT Monitor.
● Server Dell Poweredge T430, Intel Xeon CPU ES-2604 V4 @1070 GHZ Processor, 16 GB
RAM, 3TB HDD SATA, Optical Mouse, Keyboard, TFT.

Computer Networking(CN) Lab:

During the odd semester, the department conducts practical sessions on computer networks, which refer to the interconnection of computing devices capable of sharing resources and exchanging data. To transmit information over physical or wireless technologies, these networked devices employ a set of rules known as communication protocols. For the implementation of various programs based on computer networking, students use Cisco Packet Tracer and Network Simulator NS 3 in conjunction with the Ubuntu Operating system.

Python Lab:

The Python lab is designed to enhance student's programming skills by providing a hands-on environment for coding, debugging, and implementing object-oriented concepts using Python. This lab serves as a foundation for students to develop coding proficiency and gain practical exposure to real-world programming scenarios.

Subjects taught:
● Programming in Python (CIC-332)
● Computer Network (CIC- 355)

Software installed: Cisco Packet Tracer, VS code

CN/ Python Lab View

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Lab (#05)-OS LAB / SSM & DA LAB
 

System Configuration:

● DELL OptiPlex 5080 Desktop PC (Intel Core i7-10700 / 8 GB DDR4 RAM / 1TB 7200 RPM
Hard Disk / Integrated Graphics Card (2 GB) / Wi-Fi enabled / DVD RW/ USB- Keyboard
& Mouse / 19.5 LED TFT)   
                                                         
Operating Systems(OS) Lab:

The lab focuses on hands-on experiments in CPU scheduling (FCFS, SJF, Priority, Round Robin), page replacement policies (LRU, FIFO, Optimal), memory management algorithms (First Fit, Best Fit, Worst Fit), semaphore-based synchronization (Reader/Writer, Producer-Consumer problems), deadlock avoidance (Banker's algorithm), and various file organization techniques.

Statistics, Statistical Modelling & Data Analytics (SSM & DA) Lab:

In this lab, students perform hands-on exercises involving matrix operations, eigenvalues, and eigenvectors, and solve equations using various methods. They explore matrix properties, reduced row echelon form, and function plotting. Additionally, they present data as frequency tables, identify outliers, and assess project risks. The lab also includes exercises on scatter diagrams, residual plots, correlation, time series analysis, linear regression, and concepts of probability and distributions. This comprehensive approach enhances their understanding of mathematical and statistical techniques.

Subjects taught:
● SSM & DA(DA-304P)
● Operating system (CIC-353)

Software installed: Scilab, VS code

OS/ SSM & DA Lab View

 

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Lab#106-A- PROGRAMMING LAB

System Configuration: 

● DELL 3268 Vostro Desktop PC Configuration Core i5 7th Gen/ 4GBDDR4 RAM/ 1TB
SATA/ DVD RW/USB Keyboard USB Mouse/ 18.5 LED TFT.

Programming Lab:

The Programming Lab is a hands-on learning space where participants develop coding skills, test software, and apply theoretical concepts. It includes exercises, debugging, and project-based learning, fostering critical thinking and innovation. Equipped with essential tools, it plays a key role in computer science and engineering education.

Subjects taught: -
● Programming in C(ES-153/154)

Software installed: - VS Code

Programming Lab View

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Lab#106-B- PSLP LAB /COMPILER DESIGN LAB

System Configuration: 

● DELL 3268 Vostro Desktop PC Configuration Core i5 7th Gen/ 4GBDDR4 RAM/ 1TB
SATA/ DVD RW/USB Keyboard USB Mouse/ 18.5 LED TFT.


Probability, Statistics & Linear Programming Lab (PSLP LAB):


This lab provides hands-on exercises to implement and demonstrate various programming and statistical concepts. Students learn matrix multiplication, loops, and conditional statements. They explore probability limits, plot normal and exponential distributions, fit binomial, Poisson, and normal distributions, and implement linear and multiple regression models. Additionally, they solve linear programming, transportation, and assignment problems using different methods. These experiments enhance students' understanding of programming, statistical analysis, and optimization techniques, preparing them for real-world applications.

Compiler Design Lab:

This lab provides hands-on practice in compiler writing with LEX/YACC. Students write programs to check grammar rules, remove left recursion, and perform left factoring. They also implement stack operations, determine leading non-terminals, and perform shift-reduce parsing. Additionally, they find FIRST of non-terminals and check operator precedence. These exercises enhance understanding of compiler design and parsing techniques, preparing students for advanced topics in language processing and software development.

Subjects taught : -
● Compiler Design(CIC-351)
● Probability, Statistics and Linear Programming Lab(BS-252)

Software installed: - VS code

PSLP/ CD Lab View

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LAB#102- DESIGN & ANALYSIS OF ALGORITHM LAB / DBMS LAB

System Configuration:

ACER P-V Core i5 processor, 2nd generation, CPU @3.0 GHz, 4GB DDR3 RAM,500 GB HDD,
DVD R/W, Keyboard, Optical Mouse, TFT 18.5. colour monitor

Design & Analysis of Algorithm Lab:
During odd semesters, the lab on Design of Algorithms is conducted. This lab serves as an introduction to the fundamentals of computational complexity analysis and various algorithm design techniques. The lab aims to impart knowledge on both the underlying mathematical theory and practical considerations of efficiency. To implement the algorithms, the lab requires the use of Turbo C7, which is a widely used programming environment that enables students to practice coding and apply the concepts learned in the lectures.

DBMS Lab:

During the semester, the lab on Database Management Systems (DBMS) is conducted. The primary objective of this lab is to provide students with an opportunity to apply the concepts learned in the DBMS subject. In this lab, students develop a database using Oracle 11g, which is a widely used database management system, to implement various SQL-based queries. By practicing database design and implementation, students gain hands-on experience and develop practical skills in database
management.

Subjects taught : -
● Design & Analysis of Algorithm(CIC-359),
● Database Management System (CIC-256)

Software Installed: - Turbo C/C++, ORACLE

Design & Analysis of Algorithm Lab / DBMS Lab View

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 LAB#402- JAVA LAB/ OBJECT ORIENTED PROGRAMMING LAB 

System Configuration:

● Acer System:- Acer I-5, 2320 CPU, 3GHZ, 4 GB DDR# RAM, 500GB HDD(SATA),
Optical Mouse, Keyboard, LCD Screen with APC UPS
● HP – Intel Core 2 Duo 2.93 GHz, 4 GB RAM, 500 GB SATA HDD, DVD Writer, on board
LAN, Keyboard, Optical Mouse, 18.5” TFT Color Monitor

Java Lab:

This lab provides an overview of the Java programming language, covering its basics such as inheritance, virtual function calls, and the underlying mechanisms that support them. All the experiments in this lab are conducted using JDK (Java Development Kit) software, which provides an integrated development environment for writing, debugging, and executing Java programs. Through this lab, students gain a solid understanding of Java's fundamentals and develop practical skills in programming with Java.

Object Oriented Programming Lab:

During the odd semester, practical sessions on OOPS (Object-Oriented Programming) are conducted in the lab. The purpose of this lab is to solidify students' comprehension of fundamental object- oriented programming concepts, such as objects, classes, subclasses, and methods, and their implementation in C/C++. Additionally, it offers an opportunity to practice non-object aspects of C++ (such as loops and conditionals) using Turbo C++.

Subjects taught : -
 Java (CIC-258),
 OOPS( CIC-257)
 

Software Installed :- JDK , VS code

Java Lab/ Object Oriented Programming Lab View

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LAB#101- DATA STRUCTURE LAB / WEB TECHNOLOGY LAB

 System Configuration:

 Dell Precision Workstation M/N. 3460 SFF CTO, 13th Gen Core i7 @ 13700 Processor/ 16
GB DDR-5 RAM @5600 MHZ/ 512 GB PCLe NVMe SSD/No-ODD/Nvidia Quadro T400
Graphic with 4 Gb Integrated HD Audio, Gigabit LAN, Dual Band Wifi with Bluetooth
(External Antenna)/ Linux/USB Keyboard & Mouse/ Dell 19.5" HD Display Monitor/ 260W
Power Supply  

Data Structures Lab:

The laboratory is currently being utilized for conducting different subjects in a way that maximizes the use of resources. During the odd semester, the Data Structure (DS) lab is carried out in this space. The DS lab necessitates the use of Turbo C7 for the implementation of various data structure algorithms.

WEB Technology Lab:

During the even semester, the Web Technology lab is conducted in this laboratory. In this lab, students learn to analyze the elements and attributes of a web page, create web pages using XHTML and Cascading Style Sheets, build dynamic web pages using JavaScript for client-side programming, and generate XML documents and Schemas.

Subjects taught:-
 Data Structure (CIC-255)
 Web Technology (CIE-356P)

Software installed:- VS Code

Data Structure Lab / Web Technology Lab View

=======================================================================
 
 

 

LAB#104- SOFTWARE ENGINEERING LAB / ARTIFICIAL INTELLIGENCE LAB &

PROJECT LAB

 System Configuration:

 Dell Precision Workstation M/N. 3460 SFF CTO, 13th Gen Core i7 @ 13700 Processor/ 16
GB DDR-5 RAM @5600 MHZ/ 512 GB PCLe NVMe SSD/No-ODD/Nvidia Quadro T400
Graphic with 4 Gb Integrated HD Audio, Gigabit LAN, Dual Band Wifi with Bluetooth
(External Antenna)/ Linux/USB Keyboard & Mouse/ Dell 19.5" HD Display Monitor/ 260W
Power Supply

 Software Engineering Lab:

During the odd semester, the SE lab is conducted with the objective of providing students with practical experience in various areas of software engineering and UML. These areas include identifying requirements, creating DFDs, designing behaviour and structure using UML diagrams, implementation, testing, and more. Throughout the semester, students will work on an assigned project to gain a better understanding of the software development process in real-life scenarios. Practical sessions are conducted using Star UML.

Artificial Intelligence Lab:

In this lab, students engage in practical experiments with PROLOG, implementing various logical statements and predicates. They also develop programs for CPU scheduling, memory management, and classic synchronization problems. Python is used for implementing games and natural language processing tasks with NLTK, including stemming, lemmatization, and POS tagging. Students gain hands-on experience with algorithms like BFS and the Water Jug Problem, enhancing their programming and problem-solving skills across multiple domains.

Project Lab:

The Department of Computer Science and Engineering houses a dedicated lab that is exclusively reserved for project work. This lab is specifically intended for use by final year students. It comprises computer systems with high-end configurations and licensed software that are relevant to the students' project requirements. All computers in the lab are equipped with internet connectivity, and UPS power backups and antivirus and other software are also installed based on the final year project group's demands. In addition, any necessary networking hardware and software are provided as needed.

Subjects taught:-
 Software Engineering(CIC-357)
 Artificial Intelligence (AI- 302 P)

Software installed:- SWI PROLOG, STAR UML

Software Engineering Lab / Artificial Intelligence Lab & Project Lab View


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                                            LAB-224- MOBILE COMPUTING LAB / COMPUTATIONAL METHODS LAB

 System Configuration:

 HP – Intel Core 2 Duo 2.93 GHz, 4 GB RAM, 500 GB SATA HDD, DVD Writer, on board
LAN, Keyboard, Optical Mouse, 18.5” TFT Color Monitor
 ACER P-V Core i5 processor, 2nd generation,3.0 GHz, 4GB DDR3 RAM,500 GB HDD,
mouse, keyboard and TFT color monitor          
          
Computational Methods Lab:

The Computational Methods Lab introduces numerical techniques for solving engineering and scientific problems. It covers topics like root finding, linear algebraic equations, interpolation, numerical differentiation, and optimization. The lab emphasizes practical implementation using programming languages such as Python and C. Students develop algorithms and apply numerical methods to real-world problems, gaining hands-on experience in computational problem-solving.

Mobile Computing Lab:

The Mobile Computing Lab (M-Lab) explores the potential of using mobile and wireless computers mand sensors to tackle various pressing issues in fields such as healthcare, conservation, transportation, education, and beyond.

Subjects taught: -

 Mobile Computing Lab (CIE-368P)
 Computational Methods (ES-251)

Software installed: - Turbo C, HTML - One Compiler

Mobile Computing Lab / Computational Methods Lab View

=======================================================================

 

 

LAB-216- DLCD LAB

 System Configuration:

 DELL 3268 Vostro Desktop PC Configuration Core i5 7th Gen/ 4GBDDR4 RAM/ 1TB
SATA/ DVD RW/USB Keyboard USB Mouse/ 18.5 LED TFT
HP – Intel Core2duo 2.93 GHz, 4 GB RAM, 500 GB SATA HDD, DVD Writer, on board
LAN, Keyboard, Optical Mouse, 18.5” TFT Color Monitor
HCL- Intel Core 2 duo 2.2 GHz, 1 GB RAM, 80 GB SATA HDD, 52X CD ROM, HCL
Keyboard, Microsoft USB optical Mouse, TFT

DLCD Lab:

The DLCD Lab provides hands-on experience in digital logic design, combinational & sequential circuits, and computer architecture. Students work on adders, multiplexers, counters, and memory components, along with 8085 assembly programming using GNUsim8085. The lab strengthens theoretical concepts through practical applications.


Subjects taught: -
 Digital Logic and Computer Design (ECC-207)

DLCD Lab View

 

Dr. Geetika Dhand
Associate Professor | HOD | Ph. D., M.Tech. (IT), B.Tech.

[email protected]

Dr.Geetika Dhand has an experience of 20+ years in teaching.. She has published more than 40 research papers in SCI, Scopus ,Elsevier indexed journals etc. She has chaired several sessions of IEEE and Springer International Conferences. She has nine published and granted patents in the technology transfer domain. She is a Life Member of the Indian Society for Technical Education (ISTE). She has also published two international books in the field of artificial intelligence.

Vidwan Id-  240999

Detailed Profile

Dr. Naveen Dahiya
Professor | Ph. D., M.Tech., B.E.

[email protected]

Dr. Naveen Dahiya is currently working as Professor in CSE department and is handling the additional charge of Dean Academics. He has done his Ph.D and M.Tech. from J.C. Bose Y.M.C.A. University of Science and Technology, Faridabad, Haryana. To his credit, he has a granted patent and publications in reputed journals with high impact factors. He has hosted special issues of various reputed journals in his role as a guest editor. He is Editorial Review Board member of various journals of repute. His areas of interest are Data Analytics and Data Warehouse Design.

Vidwan ID: 241950

Detailed Profile

Dr. Koyel Datta Gupta
Professor | Ph.D., M.Tech., B.Tech.

[email protected]

Dr. Koyel Datta Gupta is a professional with an experience of 19+ years in academics. Her areas of research include Network Security, IoT, Blockchain and Machine Learning. Dr. Koyel Datta Gupta is currently working as Professor in Maharaja Surajmal Institute of Technology (MSIT) (under the GGSIP University), New Delhi. She has published more than 30 research papers in reputed Journals like IEEE Transactions on Green Communications and Networking, Expert Systems, Computers and Electrical Engineering, ETT Wiley, Neural Processing Letters, Springer etc. She has also published in conferences proceedings and has also edited and authored books.

Vidwan Id- 240950

Detailed profile

Dr. Rinky Dwivedi
Professor | Ph. D, M.E., .B. Tech.

[email protected]

Dr. Rinky Dwivedi has an experience of 17+ years in teaching. She is extremely passionate about teaching and research. She has many scientific publications, book chapter and patents to her credit. Her research interest includes software engineering, Internet of Things and soft computing. She is the reviewer of many international conferences and journals.

Vidwan Id- 241399

Detailed profile

Dr. Naresh Kumar
Professor | Ph. D., M. Tech., B. Tech., UGC-NET, GATE Qualified

[email protected]

Dr. Naresh Kumar works on Information Retrieval using Web Crawlers, Search Engines and Meta search Engines. He uses algorithmic approach for retrieval of information. His main focus is on minimization of unwanted information from the retrieved data.

Vidwan Id- 241001

Detiled Profile

Dr. Priyanka Nandal
Associate Professor | Ph. D., M. Tech., B. E

[email protected]

Dr. Priyanka work is devoted to explore the importance of several nonlinear processes in order to understand the mechanism behind the observed phenomena in the regions of solar wind, magnetopause and radiation belts. Using numerical methods, the results are found consistent with the observations of THEMIS or CLUSTER spacecrafts. She has done efforts to speed up the simulation process using the techniques of parallel processing. Simulation was performed on a high performance computing hardware exploiting graphics processing unit (GPU) using NVIDIA's compute unified device architecture (CUDA) frameworks. She is also interested in the field of machine learning and deep learning.

Vidwan Id- 241004

Detailed Profile

Dr. Sandeep Kumar
Associate Professor | Ph. D.,M. Tech., B. Tech., PGDBM

[email protected]

Dr. Sandeep Kumar is a seasoned academic with a rich background in teaching and research. With over 19 years of experience in various institutions, he currently serves as an Associate Professor in the Department of Computer Science and Engineering at Maharaja Surajmal Institute of Technology, Delhi. His research interests primarily lie in Data Mining, Image Processing, and related fields, where he leverages open-source technologies to tackle complex challenges. His work is distinguished by its focus on bridging the gap between theoretical computer engineering concepts and their practical applications. Dr. Kumar's contributions have been recognized with prestigious awards. He was honored with the National-Level Top Mentor award for IBM TGMC 2013 and has received Best Research Paper Awards at IRCET-2021 and ICCSM 2024. A dedicated scholar, he actively participates in and presents his research at renowned conferences worldwide. His commitment to continuous learning is evident in his extensive participation in faculty development programs (FDPs) and workshops. Recently, he represented MSIT at ICCAD-24 in Paris, France, where he presented his latest research. Currently, he is mentoring Ph.D. scholars and has a strong publication record in Scopus, SCI, and SCIE journals. He also holds several national and international patents.

Vidwan Id- 241013

Detailed Profile

Dr. Kavita Sheoran
Associate Professor | Ph.D., M.Tech.(IT), B.Tech.

[email protected]

Dr.Kavita Sheoran has an experience of 20+ years in teaching. . She is currently an Associate Professor in the Department of Computer Science and Engineering. Her current research interests are Soft Computing, Wireless Networking and Machine Learning. She has published several papers in SCI, Scopus and Elsevier indexed journals. She has chaired several sessions of International Conferences. She has published several patents also. She has also published three books. She has committed her life to impart good quality education to the students.

Vidwan Id-  241003

Detailed Profile

Dr. Amita Yadav
Associate Professor | Ph. D., M.Sc., M.Tech.

[email protected]

Dr. Amita works on Green Computing through energy efficiency in Wireless sensor networks. She is particularly interested in routing protocols, power administration, and information dissemination protocols. Her research interest mainly in the area of Wireless Sensor networks, Data Mining and Network Security.

Vidwan Id- 241017

Detailed Profile

Dr. Savita Ahlawat
Associate Professor | Ph.D., M.Tech.(IT), B.E.

[email protected]

Dr. Savita Ahlawat is an Associate Professor in the Department of Computer Science and Engineering at Maharaja Surajmal Institute of Technology, Delhi. With 19 years of academic experience, she has published numerous peer-reviewed research articles in international journals and conferences. In addition to her teaching and research responsibilities, she actively guides PhD students, hosted special sessions at various conferences, and serves as a reviewer for several well-reputed international journals contributing to the broader academic and research community. Her research interests include Pattern Recognition, Image Processing, Artificial Intelligence, Deep Learning and Computer Vision.

Vidwan Id- 241471

Detailed Profile

Dr. Nishtha Jatana
Associate Professor | Ph.D,M.Tech. (CTA), B.Tech.

[email protected]

Dr. Nishtha Jatana, currently, HoD of CSE 2nd Shift has worked on Software Testing using metaheuristic techniques during her doctoral degree. She has recently started working in the area of Assistive Technologies for visually disabled people. She has also worked in the area of Machine Learning algorithms and Blockchain Technology. She has several publications in SCIE and Scopus indexed journals and international conferences and Patents. She remains enthusiastic about managing, organizing and handling responsibilities and works diligently for betterment of the Institute. She has over 15 years of teaching experience.

Vidwan ID: 241879

Detailed Profile

Dr. Vimal Gaur
Associate Professor | Ph.D, M.Tech.(IT), B.Tech.

[email protected]

Name of the Faculty Dr. Vimal Gaur
Designation Associate Professor
Qualification Ph.D (Maharishi Markandeshwar (Deemed
to be University), Ambala
M.Tech (GGSIPU, New Delhi)
B.Tech (N.C.College of Engineering, Israna,
Affiliated to Kurukshetra University, Kurukshetra
Area of Expertise: Artificial Intelligence, Machine Learning
Phone: 9999620069
Email id: [email protected]

Vidwan Id- 241010

Detailed Profile

Dr. Sangeeta
Associate Professor | Ph. D., M.Tech.(CSE), B.Tech. (IT), UGC NET-JRF Qualified

[email protected]

Name of the Faculty: Dr. Sangeeta
Designation: Associate Professor
Qualification: PhD (DTU, Delhi), ME (MDU, Rohtak) and BE (MDU, Rohtak)
Area of Expertise: AI, ML, Soft Computing, Software Reliability Modeling, Optimization and Machine Translation.
Email id: [email protected]

Vidwan Id- 241009

Detailed Profile

Dr. Sapna Malik
Associate Professor | Ph. D., M.Tech, B.E.

[email protected]

Dr. Sapna Malik is having an experince of 15 years in teaching and Research. She  pursed Bachelor of Engineering  from M.D.University,Rohtak in 2004, Master of Technology from   GGSIPU University,Delhi in 2009 and Ph.D. from Ansal University,Gurgaon, in 2018. She is working as Assistant Professor in Department of Computer Science & Engineering ,MSIT,Delhi,India since 2006. She is life time member of ISTE. She has published more than 30 research papers in reputed international journals including Thomson Reuters (ESCI & Scopus) and conferences including IEEE,Springer,Elsevier.Her main research work focuses on Mobile Security, Cryptography Algorithms, Network Security, Cloud Security and Privacy, Data Mining, IoT and Computational Intelligence based education.

Vidwan Id- 241007

Detailed Profile

Dr. Sonia Rathee
Associate Professor | Ph. D., M.Tech., B.E.

[email protected]

Dr. Sonia Rathee is in the department of CSE at MSIT since 2007. She obtained her Ph.D. degree in Computer Science from U.I.E.T, M.D.U, Rohtak in 2019. She has about 17 years of teaching and research experience. Her interests are in the fields of Database management system, spatial database, temporal database, Artificial Intelligence, Data Analytics. She has published more than 40 research articles in various International Journals/Conferences and published a Book of international repute and 3 book chapters. She has also reviewed papers in various Journals and Conferences. She has attended more than 25 Faculty development programs and seminars to keep her updated with the latest technology. She has successfully supervised many 4th Year Students projects. She has excellent time management skills, can amicably coordinate with co-professors to develop new programs to enhance the abilities of the students in the computer courses.

Vidwan Id-  241006

Detailed Profile

Dr. Vinita Rohilla
Assistant Professor | Ph.D,M.Tech., B.E.

[email protected]

Ms. Vinita Rohilla
Assistant Professor
Ph.D,M.Tech(CSE),B.E(CSE)
Area of Expertise: Machine Learning, Data Science, Computer Vision, Web development
Email id: [email protected]

Vidwan Id- 241014

Detailed Profile

Dr. Shaily Malik
Assistant Professor | Ph.D,M.Tech., B.E.,

[email protected]

Dr. Shaily Malik is a professional with an experience of 17+ years in academics. Her areas of research include information retrieval using semantic similarity Measures, Cross Modal Retrieval and Machine Learning. She is currently working as Assistant Professor in Maharaja Surajmal Institute of Technology (MSIT) (under the GGSIP University), New Delhi in Computer Science and engineering department. She has published 3 Patents (1 granted and 2 published), 4 papers in SCI Journals, 5 papers in scopus indexed journal, 1 in ESCI Indexed journals, 3 papers in UGC listed journals and more than 10 research papers in reputed conferences.

Vidwan Id- 240998

Detailed Profile

Dr. Shalu
Assistant Professor | Ph.D,M.Tech.(IT), B.E.

[email protected]

Her research area includes the use of Swarm Optimization techniques for improving the quality of service in Wireless Sensor Networks (WSN). She focuses on design and simulation of Swarm based coverage holes detection and recovery protocols for WSN. She also has an exposure to realization of test bed (iSense).    

Vidwan Id- 241002

Detailed Profile

Dr. Pooja Kherwa
Assistant Professor | Ph.D, M.Tech., B.E.

[email protected]

/media/2024/10/09/poojakherwa.pdfPooja Kherwa is an assistant professor in Maharaja Surajmal Institute of Technology, New Delhi. She received her M. Tech in information Technology from Guru Govind Singh Indraprastha University; Dwarka, New Delhi in 2010.Currently she is pursuing her PhD from Guru Govind Singh Indraprastha University, Dwarka- New Delhi. Her research interest includes Topic Modeling, Sentiment Analysis, Machine Learning.A talented professional who has superb teaching skills developed as a result of over 15 years of extensive experience in teaching computer science-related subjects and concepts to engineering graduate students. She has extensive research experience in topic modeling and published more than 15 research article in various international journals/conferences and in book of international repute as book chapters. She is the most read researcher of the department as per research gate, and was most read researcher of the institution for more than 6 consecutive months in 2020.She has also reviewed papers in various SCIE/ESCI/Web of science journals. She has got certification of Appreciation for supervising graduate students in Inter College B. Tech. Project competition and winning Best Project of Computer Science in GGSIPU 2014. She has excellent communication and rapport with students which makes learning easier for them and much more fun.

Vidwan Id - 243726

Detailed Profile

Dr. Navdeep Bohra
Assistant Professor | Ph.D,M.Tech., B.Tech.

[email protected]

Dr. Navdeep Bohra is a professional with an experience of 15+ years in academics and industry. His areas of research include Popularity Prediction, Machine Learning. Navdeep Bohra is currently working as Assistant Professor in Maharaja Surajmal Institute of Technology (MSIT) (under the GGSIP University), New Delhi. He has granted 1 Patent and published 3 research papers in reputed Journals like Springer etc. He has also published in conferences proceedings.

Vidwan Id- 241019

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Mr. Ravi Choudhary
Assistant Professor | M.Tech (PC), B.Tech.

[email protected]

Mr. Ravi Choudhary is a professional with an experience of 16+ years in academics. He is currently working as an Assistant Professor in Maharaja Surajmal Institute of Technology, New Delhi. His area of research includes Artificial intelligence, Electric Power systems, Machine Learning. He has published various research papers in reputed journals and conference proceedings.

Vidwan ID: 243397

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Mr. Sushil Kumar
Assistant Professor | M.Tech., B.Tech.(IT)

[email protected]


Mr. Sushil kumar has an overall experience of 16 years in Academics. He received his B.Tech (IT) and M.Tech in Computer Science and Engineering from MMEC, Mullana, Amabala. His research interests are in the fields of Machine Learning, Image Processing and Computer Vision.

Vidwan Id- 241005

Detaile/media/2024/10/09/sushil-kumar.pdfd Profile

Dr. Poonam
Assistant Professor | Ph. D, M. Tech., B. Tech.

[email protected]

Dr. Poonam’s research areas include Machine Learning, IoT, Digital Image Processing, and Digital Communication. She has published several research papers in these domains. She has taught various subjects like Electronic devices, Microprocessors & microcontrollers, Digital Communication, Analog Electronics, Satellite Communication etc. during her teaching career. She is also actively involved in the various Institutional & Departmental activities.

Vidwan Id- 243295

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Dr. Anshul Pareek
Assistant Professor | M.Tech., B.Tech.

[email protected]

Dr. Anshul Pareek is an experienced academic professional with over 20 years of expertise in Artificial Intelligence, Machine Learning, and Electronics Engineering. Currently serving as an Assistant Professor at Maharaja Surajmal Institute of Technology, New Delhi, while supervising numerous student projects in AI and ML. Dr. Pareek holds a Ph.D. in Vision Based Human Robot Interfacing from and an M.Tech in Digital Communications. She has authored over 30 research papers in prominent journals and conferences, and has filed patents on IoT-based Healthcare Systems and Deep Learning applications. Additionally, she is an active member of IEEE, IEEE RAS and IIC, and is dedicated to fostering industry-academia collaboration through innovative research and teaching.

Vidwan Id- 243476

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Dr. Neeti Sangwan
Assistant Professor | Ph.D,M. Tech., B.Tech.

[email protected]

Dr. Neeti Sangwan is a professional with an experience of 12+ years in academics. She is currently working as an Assistant Professor in Maharaja Surajmal Institute of Technology, New Delhi. Her area of research includes Data Analytics, Machine Learning. She has published various research papers in reputed journals and conference proceedings. She has one patent granted to her.

Vidwan ID: 244219

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Dr. Parul Chaudhary
Assistant Professor | Ph.D, M.Tech., B. Tech., CSIR NET Qualified

[email protected]

Dr. Parul Chaudhary is a seasoned academic with over 13 years of experience in research and teaching within the field of Electronics & communication. Holding a Ph.D. from GGSIPU University, Dr. Chaudhary has made significant contributions through publications in high-impact journals, including SCI, SCIE, ESCI, SCOPUS, and UGC. Her expertise spans a range of subjects, including statistics, statistical modeling, Data Analytics, Machine Learning, and IoT. Notable achievements include pioneering research in energy harvesting systems and obtaining certifications from IIT Kharagpur and TCS IoN in AI. She has also completed internships in Machine Learning and Swayam courses on IoT. In addition to her research and teaching roles, Dr. Chaudhary has excelled in various administrative and leadership capacities. She has been a core member of accreditation committees for NAAC and NBA and played a pivotal role in establishing the Microsoft Learn Student Ambassador Student Chapter at Maharaja Surajmal Institute of Technology. Her contributions to academia are further highlighted by her involvement in curriculum development, faculty development programs, and successful coordination of the Placement Committee. Dr. Chaudhary is also recognized for her patents in smart energy management and agricultural systems, underscoring her commitment to innovative and practical applications of technology.

Vidwan Id- 243353

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Ms. Swati Malik
Assistant Professor | M.Tech., B.Tech.

[email protected]

Ms. Swati Malik is a professional with an experience of 11+ years in academics. She is currently working as an Assistant Professor in Maharaja Surajmal Institute of Technology, New Delhi. Her area of research includes digital communication, MATLAB. She has published various research papers in reputed journals and conference proceedings. She has one patent published by her.

Vidwan ID: 243375

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Ms. Poonam Dhankhar
Assistant Professor | M. Tech. (SE), B. Tech.

[email protected]

Ms. Poonam Dhankhar works on image processing. She has great interest in the field of data analytics and deep learning. She believes teaching is not just about imparting knowledge through curriculum it is rather a two way process which makes you aware of  trending fields of research and technology.

Vidwan ID: 242473

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Ms. Gunjan Beniwal
Assistant Professor | M. Tech., B. Tech. (IT)

[email protected]

Ms. Gunjan is an active and dedicated professional with 9+ years of experience in academics. She is doing her research in the field of IoT, focusing on Quality of Service and fog computing. She has published various research papers in reputed journals and conference proceedings. She has one patent granted to her. With a strong foundation in algorithm design, she excels in her academic and research responsibilities and participates in technical and cultural activities within the institution. Her commitment to teaching and extracurricular involvement makes her a valuable department member.

Vidwan ID: 243313

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Dr. Vikrant Shokeen
Assistant Professor | Ph.D, M.Tech., B.Tech.

[email protected]

Dr. Vikrant Shokeen works on the segmentation ,feature extraction, classification of  images . He uses various techniques like PCA, SIFT and SURF for feature extraction and SVM, LDA, KNN for classification. He is particularly interested in hybrid approaches like SVM integrated with Feed Forward Back Propagation Neural Network to create a hybrid algorithm that further helps in reducing the computation complexity of the classification. His present research area is focused on the factual findings of the potential usage of the combinational Feed-Forward Back Propagation Neural Network as a judgement making for Lung Cancer.

Vidwan Id- 241187

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Ms. Sonica Upadhyay
Assistant Professor | M. Tech., B. Tech.

[email protected]

Ms Sonica Upadhyay is working as Assistant Professor in the department of Computer Science (MSIT). She has more than 5 years of experience in the field of academics. She has completed her Master's in Technology from Banasthali University and currently pursuing PhD. Her research interests lies in Big Data and Data analytics.

Vidwan Id-  241012

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Ms. Jyoti
Assistant Professor | M.Tech , B.Tech

[email protected]

Ms. Jyoti is working as Assistant Professor in the Department of Computer Science Engineering. She is pursuing her Ph.D. in Computer Science & Engineering from National Institute Of Technology, NIT Delhi. She has 3 years of experience in the field of academics. She has completed her B.Tech. and M.Tech. from Kurukshetra University, Kurukshetra. She has published two papers in Journal and Conference. She has attended many FDP, Workshops and Expert lectures on various topics like Machine Learning, Data Science, Python etc. Her research area includes Data Science, Computer Science & Machine Learning.

Vidwan Id - 260853

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Ms. Vaani Garg
Assistant Professor | M.Tech, B.Tech

[email protected]

Ms. Vaani Garg completed her M.Tech from NIT, Uttarakhand and is currently pursuing her PhD from DTU. Her research areas include image processing, computer vision, pattern recognition and machine learning. She is currently working in the field of automatic video summarization and video content analysis. She has also cleared the UGC-NET examination for Computer Science and Applications and GATE examination for Computer Science and Engineering.

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Ms. Kirti Dahiya
Assistant Professor | M.Tech , B. Tech

[email protected]

Ms. Kirti Dahiya is an assistant professor have more than two years of teaching experience, delivering engaging lectures and facilitating meaningful discussions to foster student learning and critical thinking, attended many faculty developed programs and also published research papers in two journals. Major research areas of interest are artificial intelligence and data science.

Vidwan Id : 281984

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Ms. Indu khatri (Ad-hoc)
Assistant Professor | M.Tech.,B.Tech

Indu
Assistant Professor
Ph.D Pursuing (DTU), M.Tech. (DCRUST), B.E.(MDU)
Area of Expertise: Machine Learning, Operating System, Data Structures
Phone: 91-9671544889
Email id: [email protected]

 

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Dr. Medhavi Malik (Ad-hoc)
Assistant Professor | Ph.D., M.Tech., B.Tech.

Name of Faculty: Dr. Medhavi Malik
Designation: Assistant Professor
Qualification: Ph.D (CS)
Area of Expertise: Computer Networks, Cloud Computing, Mobile Computing, Blockchain, Image Processing
Phone: 011-45037193
E-mail Id: [email protected]

 

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S.No. Name of the Staff Member Designation
1 Ms. Rashmi Tech. Assistant
2 Ms. Bhawna Kulshrestha Tech. Assistant
3 Mr. Sanjeev Tech. Assistant
4 Ms. Muskan Tech. Assistant
5 Ms. Neelima Tech. Assistant
6 Ms. Manju Tech. Assistant
7 Ms. Mamta Tech. Assistant
8 Mr. Rakesh Sharma Tech. Assistant
9 Ms. Seema Goel Tech. Assistant

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