Computing and Vision Lab (Lab In-charge: Prof. Rajeev Srivastava)

This is one of the UG and PG labs of the department which caters to the needs of UG as well as PG students. The practical classes of various UG (BTech./IDD) Courses such as Computer Graphics, Operating Systems, and Data Structures are held in this lab. Apart from normal UG/ PG labs this lab also supports to the B.Tech./IDD students for carrying out their work related to their Exploratory Projects, UG Projects, and M.Tech. Thesis. Associated PhD Research Scholars conduct their research in this lab in the area of Image Processing, Computer Vision, and Machine Learning.

Facilities Available

  • Server-01 No. (Dell Poweredge Tower Server: Intel Xeon E3-1225V2 (3.2 GHz/8 MB Cache), 16 GB RAM DDR3 1600 MHz UDIMM (32 GB, Support), 1 TB SATA HDD 7200 RPM (4 HDD Support)+Accessories).
  • Workstataions-02 No. Specifications for Workstation 1: Dell Precision T 7810 Tower Workstation: Dual Intel Xeon Processor E5-2630 V3, (8 Core , 20 MB Cache, 2.4 GHz Turbo), 32GB (4X8GB) 2133 MHz DDR4 ECC RDIMM, 1X2 TB 3.5 inch Serial ATA (7200 RPM) Hard Drive, 8x Slim line DVD+/-RW Drive, P2414 H 23.8” Wide Screen Monitor with LED back light, Nvidia Quadpro K420 1 GB Graphic Adaptor+ Accessories. Specifications for Workstation 2: Intel Xeon Silver 4114 CPU@2.2 GHz (2 processors), 64 GB RAM, 2 TB HDD, dedicated Video Memory: Nvidia 8GB GDDR5.
  • Desktop PCs (Intel Core i7 and others) with internet connectivity to all-30 Nos.
  • Accessories: Printers, scanners, UPS (5KVA).
  • Machine Vision Equipment: Benchmark High Speed Imaging System: Vision Processor, Industrial Cameras, Imaging Computer, Imaging Library and Analysis software, Lens Kit, Zoom Lens, Copy/Camera Stand, Lighting.
  • Software Available: MATLAB 2014, OriginLab, Visual Basic 2010,  Statistica, Image Pro Software, C/C++ Compilers, Java, Acrobat Professional , MS Office, EndNote and other open source software packages such as OpenCV, OpenGL etc.

Network Security lab (Lab In-charge: Dr. Kaushal Kumar Shukla)

The Network Security lab caters to the mini projects associated with the Information Security and Network Security theory courses. It has iSecurit attack generator for studying defense techniques, LAN trainers and real time packet analyzer. The lab relies heavily on open source software for vulnerability scanning, penetration testing, OS fingerprinting, SSL etc . The lab also caters to the lab component of the UG course on Computer Networks.

Facilities/ Equipment Available:

  • Equipped with around 35 PCs with necessary software, Real-Time Packet Analyser, and LAN/WAN Trainer

Undergraduate Lab-1

General purpose undergraduate lab equipped with hardware, microprocessor kits and PCs with required software.

Undergraduate Lab-2

General purpose undergraduate lab equipped with hardware, microprocessor kits and PCs with required software. Microprocessors Lab The Microprocessors Lab is primarily for practical courses on Microprocessors and Advanced Microprocessors. The lab is equipped with trainer kits of 8085, 8088, 8086 and related Hardware and Software.

Intelligent Computing and Robotics

Equipped with modern intelligent computing Hardware and Software.

Databases and Information Management Lab

The main focus of this lab is in the following areas: Information Extraction, Web Mining, Recommender Systems, Learning Paradigms, Intelligent Systems and sub-areas releted to these five areas. In general, our focus is mainly on the topics related to AI and Databases.

Available Infrastructure: • 3 PCs with Core i7 processor, 3.4 GHz, 4 GB RAM and 1 TB HDD.

Faculty in-charge: R N Chowdary

Research scholars:

  • Shivang Agarwal
  • Chintoo Kumar

Information Retrieval Lab

Information Retrieval lab is equipped with 5 PCs (Intel® CoreTM i7-7700 CPU @ 3.60GHz × 8 processor) with internet connectivity and a Server ( 2 Nos of Intel® Xeon® processor E5- 2660v3 (25M Cache, 2.60 GHz), Intel C610 series chipset, 64 GB memory 2133MT/s Registered ECC DIMMs, HDD 3 X 600GB SAS 10K RPM, with support for 12, 3.5'' Hard Drives or Chassis with up to 24, 2.5'' Hard Drives, Graphics min. 16 MB Memory, at least GBE NIC with IPv6 support in CentOS) along with necessary computing facilities. Also lab is equipped with two laptops, printers, scanner, projector, UPS (5KVA) and other related accessories.

Pattern Recognition Laboratory (Lab-in-charge Dr. Pratik Chattopadhyay)

We focus on research related to Applications of Machine Learning in Different Domains such as Image Processing, Cyber-Security, Material Property Prediction, etc. Presently, we have a research team consisting of three PhD students, two IDD students, and six B.Tech students.
We regularly hire bright intern students from other institutes during summer to carry out our research work. Interested candidates are requested to email the lab-in-charge at with a detailed bio-data and research plan. .

Computing resources available in the lab: Workstation with 64 GB RAM, GPUs, i9-Processor

Publications from the Laboratory (since 2018)

  • Pratik Chattopadhyay, Lipo Wang, Yap-Peng Tan, Scenario-Based Insider Threat Detection From Cyber Activities, IEEE Transactions on Computational Social Systems, 5(3), 1-16, 2018.
  • Nirbhay Kumar Tagore, Ayushman Singh, and Pratik Chattopadhyay, Person Re-identification from Appearance Cues and Deep Siamese Features, Journal of Visual Communication and Image Representation (under revision).
  • Shailesh Shrivastava, Alakh Aggarwal, Pratik Chattopadhyay, Broad Neural Network for Change Detection in Aerial Images, 1st International Conference on Emerging Technology in Modelling and Graphics, Springer Singapore, 327-339, 2019.
  • Sanjay Kumar Gupta, Gaurav Mahesh Sultaniya, Pratik Chattopadhyay, An Efficient Descriptor for Gait Recognition using Spatio-Temporal Cues, International Conference on Emerging Technology in Modelling and Graphics, Springer Singapore, 85-97, 2019.
  • Utsav Krishnan, Akshal Sharma, Pratik Chattopadhyay, Feature Fusion from Multiple Paintings for Generalized Artistic Style Transfer, International Conference on Advances in Engineering Science Management & Technology, SSRN 3387817, 2019.

Multimedia Lab (Faculty Name: Tanima Dutta)

Facilities/ Equipment Available:

  • 3 PCs
  • Digital Cameras (still and video)
  • Mics
  • Audio recoder

Research activities going on:

  • Project 1: On Wireless Sensor Networks (2017-2020), Agency: SERB, Govt. of India ( Amount: 34,47,130 INR)
  • Project 2: On Multimodal Reversible Watermarking (2018-2020), Agency: SERB, Govt. of India ( Amount: 14,0181 INR)
  • Project 3: On Ganga River Monitoring (2018-2019), Agency: TATA Chingo, USA ( Amount: 10,00,000 INR)

UG/ PG Lab being conducted:

  • Distributed Computing (Open Elective)
  • Multimedia Systems and Application (Departmental Elective)

Publications and other:


Natural Language Processing Lab   (Lab In-Charge: Anil Kumar Singh)

Natural Language Processing (NLP) aims to enable computers to process human languages. It can be used to solve independent problems like Machine Translation, but it is also an essential part any ambition system based on Artificial Intelligence. NLP Research Lab was started in 2015. Projects on a variety of NLP topics have been carried out at this lab, and there are sometimes projects on related areas, such recommendation systems. However, the main focus area of research in the lab is NLP for Low Resource Languages. In particular, we have been carrying out work on Machine Translation for languages of the Purvanchal area (Bhojpuri, Maithili and Magahi). The prototype systems from Hindi to these three languages have already been prepared, along with language resources and tools for these systems, since these system are based on the transfer-based approach due to lack of sentence aligned parallel data in sufficient quantity.

Other than this, some of the topics on which projects have been done in the lab include:

  • Named Entity Recognition
  • Language Identification (standard, non-standard and code-switched data)
  • Question Answering
  • Metaphor Detection
  • Transliteration and Word Transduction
  • Morphological Analysis, Generation and Disambiguation
  • Embeddings and representation
  • Emotion Analysis
  • Opinion Summarization and Diversification
  • Reference Scope Identification for Citances
  • Shallow Discourse Parsing
  • Information Retrieval
  • Linguistic Analysis of Song Lyrics and Poems
  • Music Recommendation Systems
  • Computer Aided Second Language Learning


  • CSE-443: Natural Language Processing
  • CSE-7026: Selected Topics in Natural Language Processing

Ubiquitous Computing Lab   (Faculty Name: Hari Prabhat Gupta)

Facilities/ Equipment Available:

  • 5 PC
  • Sensors (active and passive)
  • Communication radio (WiFi, BLE, RFID)
  • Active devices

Research activities going on:

  • Project 1: On Wireless Sensor Networks (2017-2020), Agency: SERB, Govt. of India ( Amount: 34,47,130 INR)
  • Project 2: On Ganga River Monitoring (2018-2019), Agency: TATA Chingo, USA ( Amount: 10,00,000 INR)

UG/ PG Lab being conducted:

  • Ubiquitous Computing (Open Elective, 95 students) subject

Publications and other:

Data Engineering and High Performance Computing Lab   (Lab In-charge: Dr. Ravi Shankar Singh)

A low cost research lab(with proper connectivity to Param Shivay Super Computer of the Institute and High end systems available at Centre for Computing and Information Services in the Institute) where students are exposed to OpenMP, MPI, CUDA and hybrid programming. Apart from this, researchers are engaged in the applications of High-Performance Computing in various fields, which includes Cloud Computing, Image Processing, Parallel, Computing.

Facilities/Equipment Present:

  • PCs: 7
  • All in one Printer: 1
  • UPS: 7
  • White Board: 1
  • Software: Mostly Open-source software like Linux, CloudSim, WorkflowSim etc.

Courses Being Conducted: Projects of following Subjects

  • CSE372 (Introduction to High Performance Computing)
  • CS-7011 (High Performance Computing)
  • CS-7020 (Cloud Computing)

Research Scholars/M. Tech. students working in the lab:

Swati Gupta
Topic: Workflow Scheduling in Cloud
Navin M Upadhyay
Topic: High Performance Computing using Multi-Core Clustering
Medara Rambabu
Energy Aware Workflow Scheduling in Cloud
Vinod Kumar
Topic: Hyper Spectral Image Classification
Yaman Dua
Topic: Hyper Spectral Image Compression
Karan Siwach
Topic: Air Pollution Estimation using Image Processing

Smart Softwares and Systems Lab   (Lab In-charge: Dr. Amrita Chaturvedi)

We focus on application of machine learning and artificial intelligence in the following areas: software engineering, software architecture, semantic web and ontologies, brain computer interaction and cyber security.

Facilities/Equipment Present:

  • 3 PCs with Core i7 processor, 3.4 GHz, 8 GB RAM and 1 TB HDD.


Visual Computing and Analytics Lab   (Lab In-charge: Dr. Sanjay Kumar Singh)

Visual Computing and Analytics Lab (VCA Lab) is a multidisciplinary research lab led by Professor Sanjay Kumar Singh performing basic & applied research in the area of Computer Vision, Data Science and related areas of Machine learning / Deep learning . In both fields, we are intrigued by visual functionalities that give rise to semantically meaningful interpretations of the visual world.


We work on developing artificially intelligent systems that are able to reason about the visual world. From a computer vision perspective, we aspire to develop novel and efficient intelligent algorithms using machine learning and deep learning that can perform important visual perception tasks such as object recognition, scene categorization, integrative scene understanding, human motion recognition, material recognition, video analysis etc. In data science, our curiosity leads us to study the underlying neural mechanisms that enable the human to take decision and perform analysis of various industrial real time data. A key characteristic of the VCA lab is its high level of engagement with other disciplines. We have collaborated with industrial and academic partners in the area of Biosciences, Medicine and Engineering such as Imagenous Engineering Private Limited (IEPL) , IVRI etc.



  • 03 B Tech BTP, CSE Students Machine learning/ Deep Learning.
  • 05 B.Tech Students of different branches in the area of Machine learning/ Deep Learning
  • 01 IDD MTP in the area of Quantum Computing.

Research Scholars :

  • Anshul
  • Abhinav
  • Anviti Pandey
  • Aneesh G Nath
  • Aneesh G Nath

Facilities Available:

  • Several machine-learning / deep- learning and data science tools.
  • High-End Digital and Video Camers.
  • High End PCs with i7 Processor.

Ongoing Research Topics in the Lab:

  • Analysis of Industrial Vibration Data using Artificial Intelligent Techniques

The fourth revolution of industry (Industry 4.0) has improved the industrial organization for increasing the efficiency, connectivity, productivity, scalability, transparency, safety, along with saving of valuable time and money. Industry 4.0 introduces the Industrial Internet of Things through the utilization of cyber-physical systems for information exchange and intelligent as well as autonomous decisions. As an effect, the industrial system has modernized by the integration of the latest technologies into mechanical equipment for achieving a higher degree of precision and efficiency. As a consequence, the overall industrial system becomes more complicated. Thus, the digital data collected from the machinery through multiple heterogeneous sensors need to be analyzed for extracting information. This information helps to perform the digital health monitoring of equipment through artificial intelligent methods to improve the availability of the system, and reduce the financial and human losses.


Medical Imaging using machine / deep learning methods

Artificial intelligence transforms healthcare. Medical images contain rich information that can only be partially observed with the naked eye. Computer algorithms may extract additional information, but large amounts of data are required to train complex models. At the same time, Big Medical Image repositories have appeared in recent years as a consequence of large-scale research studies and decades of clinical imaging. Analyzing such enormous data sets opens up many interesting research questions from both a clinical and a technical perspective. At VCA Lab, We aspire to come up with real innovations in this area that are clinically relevant and perceive this is a challenge that can only be addressed through multidisciplinary collaborations.

Evaluating the time series data using machine learning algorithms :Time series analytics

The time series data most of us are exposed to deals primarily with generating forecasts. Whether that’s predicting the demand or sales of a product, the count of passengers in an airline or the closing price of a particular stock, we are used to leveraging tried and tested time series techniques for forecasting requirements. But as the amount of data being generated increases exponentially, so does the opportunity to experiment with new ideas and algorithms. Working with complex time series datasets is still a niche field, and it’s always helpful to expand your repertoire to include new ideas.