Department of Artificial Intelligence & Machine Learning| (FOE) at MUJ

FACULTY OF ENGINEERING

OVERVIEW

The Department of Artificial Intelligence and Machine Learning (AI/ML) in the School of Computer Science and Engineering offers B.Tech & M.Tech programs in Computer Science and Engineering (Artificial Intelligence and Machine Learning). This program aims to provide students with a strong foundation in the principles and techniques of AI and ML, as well as hands-on experience in applying these technologies to real-world problems.

Throughout the program, students will learn about the various subfields of AI and ML, including computer vision, natural language processing, robotics, deep learning, and others. In addition to the core coursework, students will have the opportunity to participate in research projects, both within the department and with other departments and institutions. Students will have a deep understanding of the principles and practices of AI and ML and will be prepared to work in various industries and roles, including data analysis, software development, and research. They will be well-equipped to tackle challenging problems and contribute to advancing AI and ML.

VISION

To achieve Excellence in Computer Science and Engineering (Artificial Intelligence and Machine Learning) Education for Global Competency with Human Values.

MISSION

Provide innovative Academic & Research Environment to develop competitive Engineers in the field of Artificial Intelligence and Machine Learning.
Develop Problem-solving & Project Management Skills by Student Centric Activities & Industry Collaboration.
Nurture the Students with Social & Ethical Value.

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Faculty MembersHolding PhD

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Scholarships

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IncubationStartups

Programs

TEACHING FACULTY View all faculties

Dr. Puneet Mittal

Associate Professor & HoD

Department of Artificial Intelligence & Machine Learning

Mr. Abhishek Kesarwani

Assistant Professor

Department of Artificial Intelligence & Machine Learning

Dr. Amit Kumar Bairwa

Assistant Professor (Selection Grade)

Department of Artificial Intelligence & Machine Learning

Dr. Deepak Panwar

Associate professor

Department of Artificial Intelligence & Machine Learning

Mr. Deepjyoti Choudhury

Assistant Professor (Senior Scale)

Department of Artificial Intelligence & Machine Learning

Dr. Gautam Kumar

Associate Professor

Department of Artificial Intelligence & Machine Learning

Dr. Harish Kumar Shakya

Associate Professor

Department of Artificial Intelligence & Machine Learning

Mr. Harish Sharma

Assistant Professor (Senior Scale)

Department of Artificial Intelligence & Machine Learning

Mr. Harshit Sharma

Department of Artificial Intelligence & Machine Learning

Dr. Hemlata Parmar

Assistant Professor

Department of Artificial Intelligence & Machine Learning

Dr. Jaydeep Kishore

Assistant Professor (Selection Grade)

Department of Artificial Intelligence & Machine Learning

Dr. Jayesh Gangrade

Associate Professor

Department of Artificial Intelligence & Machine Learning

Dr. Kanwalpreet Kour

Assistant Professor

Department of Artificial Intelligence & Machine Learning

Dr. Manish Rai

Assistant Professor (Senior Scale)

Department of Artificial Intelligence & Machine Learning

Mr. Niraj Kumar Yadav

Department of Artificial Intelligence & Machine Learning

Mr. Prashant Hemrajani

Assistant Professor (Selection Grade)

Department of Artificial Intelligence & Machine Learning

Dr. Preeti Narooka

Assistant professor (Selection Grade)

Department of Artificial Intelligence & Machine Learning

Dr. Priya Goyal

Assistant Professor (Selection Grade)

Department of Artificial Intelligence & Machine Learning

Mr. Ravindra Kumar Soni

Assistant Professor

Department of Artificial Intelligence & Machine Learning

Ms. Rishika Singh

Assistant Professor (Adhoc)

Department of Artificial Intelligence & Machine Learning

Mr. Sanjay Kumar Tehariya

Assistant Professor (Senior Scale)

Department of Artificial Intelligence & Machine Learning

Dr. Sarla More

Assistant Professor- Senior Scale

Department of Artificial Intelligence & Machine Learning

Ms. Shubh Lakshmi Agrwal

Assistant Professor (Selection Grade)

Department of Artificial Intelligence & Machine Learning

Mr. Siddharth Kumar

Assistant Professor

Department of Artificial Intelligence & Machine Learning

Ms. Simran

Assistant Professor (Adhoc)

Department of Artificial Intelligence & Machine Learning

Ms. Sri Geetha M

Assistant Professor (Selection Grade)

Department of Artificial Intelligence & Machine Learning

Ms. Stuti Pandey

Assistant Professor

Department of Artificial Intelligence & Machine Learning

Mrs. Surabhi Agrawal

Department of Artificial Intelligence & Machine Learning

Mr. Surendra Solanki

Assistant Professor

Department of Artificial Intelligence & Machine Learning

Dr. Uddalak Chatterjee

Department of Artificial Intelligence & Machine Learning

Dr. Upendra Singh

Assistant Professor

Department of Artificial Intelligence & Machine Learning

Dr. Varun Tiwari

Assistant professor (Selection Grade)

Department of Artificial Intelligence & Machine Learning

Dr. Vivek Bhardwaj

Assistant professor (Selection Grade)

Department of Artificial Intelligence & Machine Learning

Dr. Yadvendra Pratap Singh

Assistant Professor (Senior Scale)

Department of Artificial Intelligence & Machine Learning

PLACEMENTS & INTERNSHIPS

Anirudh Singh

Indian Institute of Technology Kanpur

Anoushka Goyal

Defence and Research Development Organisation

Ayush Tripathi

Defence and Research Development Organisation

Ridhi Makharia

HP Inc.

Ayush Gaidhani

Siemens Technology and Services Pvt Ltd

Garvit Ahuja

Indian Statistical Institute, Kolkata

Anushka Telang

B.Tech (AI)

Hindustan Petroleum Corporation Limited

Arul Bhal

boAt

Amith Antony John

CamCom

Aneerban Saha

Grameen Shakti Mohan Finance Services Pvt. Ltd.

FACILITIES @MUJ

Computing Lab
Computational Intelligence Lab
Artificial Intelligence and Data Science Lab
Big Data and Machine learning LAB
Intelligent Computing Lab
High Performance Computing Lab

Computing Lab

Welcome to the Computing Lab (Room AB1 103), a dynamic space designed to support students' exploration and experimentation in various computing disciplines. Equipped with essential resources including modern computers, software tools, and internet connectivity, our lab provides a versatile environment for students to engage in hands-on learning and project-based activities. Our ensemble comprises a diverse range of high-performance computing systems, showcasing the capabilities of HP and Dell workstations powered by the formidable Intel Core i5-4590 processors. Included in our lineup are the HP 280 G1 MT Business PC, HP PRO 330MT Business PC, HP Z2 10 CMT WorkStation, and the Dell Precision 3430, meticulously crafted to enhance your computational experience.

In this vibrant setting, students can delve into a wide range of computing topics, from programming and software development to database management and networking. Whether it's designing interactive websites, developing mobile applications, or implementing algorithms for data analysis, students are encouraged to unleash their creativity and problem-solving skills.

Computational Intelligence Lab

Welcome to the 009 Lab, a cutting-edge facility equipped with 57 HP 200 Pro G4 22 All-in-One PCs. Powered by Intel Core i5-10210U processors, 8GB RAM, and 1TB HDDs, our lab is tailored to support a wide range of computing needs. From fostering collaborative learning to enabling advanced research in natural language processing, software development, and data-intensive tasks, our space promotes innovation and hands-on experience in the field of computing. With state-of-the-art infrastructure and a dedicated team of experts, we provide a stimulating environment where creativity thrives, and breakthroughs happen. Join us in pushing the boundaries of NLP and shaping the future of technology.

Artificial Intelligence and Data Science Lab

Welcome to the Artificial Intelligence and Data Science Lab, where innovation meets excellence. With 35 high-performance HP Z2 Tower G5 Workstations boasting Intel Core i7-10700 CPUs and NVIDIA Quadro P2200 graphics cards, our facility is at the forefront of technological advancement. Here, we empower researchers and innovators to explore the realms of AI and data science, driving groundbreaking solutions and shaping the future of technology through data-driven excellence. Join us on the journey towards pioneering discoveries and transformative advancements. With state-of-the-art equipment and a collaborative environment, we cultivate creativity and foster interdisciplinary collaborations to tackle the most pressing challenges in AI and data science.

Big Data and Machine learning LAB

Welcome to the Big Data and Machine Learning Lab (AB1 122), an advanced facility dedicated to empowering students in the realms of big data analytics and machine learning. Our lab serves as a cutting-edge environment tailored to support students' projects, from minor to major, focusing on harnessing the power of big data and machine learning technologies. Equipped with state-of-the-art resources including robust servers, high-capacity storage systems, and specialized software tools, our lab offers students the opportunity to delve into complex datasets and develop innovative machine learning models.

In this dynamic space, students embark on a journey of exploration, employing advanced strategies to tackle real-world challenges through their projects. Whether it's developing predictive analytics models for business forecasting, implementing recommendation systems for personalized content delivery, or optimizing data processing pipelines for enhanced efficiency, students are encouraged to devise effective problem-solving strategies and leverage cutting-edge techniques in big data analytics and machine learning.

Intelligent Computing Lab

Welcome to the Intelligent Computing Lab (AB1 Lab 305), a premier facility dedicated to fostering innovation and research in the field of intelligent computing. Our lab provides a cutting-edge environment tailored to support students' endeavours in both minor and major projects cantered around intelligent computing technologies. Equipped with state-of-the-art resources including powerful processors, specialized software tools, and access to high-performance computing clusters, our lab offers students the opportunity to explore advanced algorithms, machine learning techniques, and artificial intelligence applications.

In this dynamic space, students embark on a journey of exploration, delving into the realms of intelligent computing concepts and applications. Projects span a wide spectrum of domains, from developing intelligent systems for data analysis and pattern recognition to creating innovative solutions for robotics and automation. Whether it's designing predictive models for financial forecasting or implementing deep learning algorithms for image processing, students are encouraged to unleash their creativity and problem-solving skills.

High Performance Computing Lab

Welcome to the High Performance Computing Lab, a premier facility dedicated to postgraduate students pursuing advanced studies in technology. Our lab features 15 high-performance workstations equipped with Intel Core-i7 12th Gen processors, 32GB RAM, and RTX 3060 graphics cards, ensuring unparalleled computational power for research and project development. With rapid SSDs and capacious HDDs at their disposal, students have the resources needed to delve deep into their studies and push the boundaries of innovation.

In addition to providing a robust infrastructure for technology studies, the High Performance Computing Lab offers a platform for high-impact projects in artificial intelligence. From developing cutting-edge machine learning algorithms to designing AI-driven solutions for complex real-world problems, students have the opportunity to engage in transformative research that shapes the future of AI technology. Join us as we embark on a journey of exploration and discovery, where creativity meets excellence in the pursuit of technological advancement.

FROM THE

STUDENT THOUGHTS

Arpit Singh Gautam
Department of Artificial Intelligence & Machine Learning

My time at MUJ has been incredible. My departments faculty has always pushed us to do better, to go the extra mile, whether its by participating in more hackathons, learning new skills, or attending more seminars and workshops. Thanks to my reliable professors ongoing assistance and the tools they make available, I was able to gain a lot of knowledge about the machine learning field, which intrigues me. I also learned how to develop end-to-end projects. How to create a projects SRS, among other things.

Ishaan Khullar
Department of Artificial Intelligence & Machine Learning

My college life till now has been on a different track. My learning graph has increase exponentially. We won the T-HUNT hackathon organised by our department. Our HOD sir helped us through the problem statements, helped us to think out of the box. So, I would like to thank my department for their constant support, and I really appreciate their way of pushing us to do more research in our field and grow.

Manik Tyagi
Department of Artificial Intelligence & Machine Learning

My journey till now at MUJ has been amazing , starting from hosting a major event to winning T-HUNT Hackathon which was conducted by our department. Under the mentorship of our highly skilled professors we completed a facial recognition attendance system.I would like to thank my department for their constant support and faith they showed in me.

Shikhar Tyagi
Department of Artificial Intelligence & Machine Learning

My experience at MUJ has been fantastic so far. I have had the opportunity to attend various seminars and workshops during my first and second semesters, which has helped me gain insights into the field of AI and ML. In my fourth semester, I was privileged to become a Mentee at IBM and participate in hackathons, where my team and I won the first prize in the T-Hunt hackathon organized by our department. I sincerely appreciate my AI & ML department for their constant support and belief in me.

Rishi Sharma
Department of Artificial Intelligence & Machine Learning

Studying AI and ML at Manipal University Jaipur is a transformative experience. The departments expert faculty and cutting-edge resources prepared me for success. Practical learning through hands-on projects set me on a path to excel in these fields. I highly recommend Manipal University for AI and ML education.

G SRILASYA VARMA
Department of Artificial Intelligence & Machine Learning

Being part of MUJs AI and ML department has enriched my learning journey. The collaborative atmosphere and diverse student body have nurtured my passion for AI. The support and opportunities here are exciting, and I am confident about my future in this field.

Ansh Srivastava
Department of Artificial Intelligence & Machine Learning

MUJs AI and ML department is a hub of knowledge and innovation. Faculty approachability, an updated curriculum, and industry connections have opened doors to incredible opportunities. My learning journey has been enriched by the collaborative atmosphere and a diverse student body.

Manu Gupta
Department of Artificial Intelligence & Machine Learning

My experience at Manipal University Jaipur has been nothing short of extraordinary. The AI and ML departments unwavering commitment to research and practical learning has equipped me with a distinct advantage in this ever-evolving field. The invaluable guidance from faculty and collaborative efforts with peers have truly set me on the path to success.

Vaidik Mandloi
Department of Artificial Intelligence & Machine Learning

Studying at Manipal University Jaipur, especially within the AI and ML Department, has been transformative. Faculty expertise and innovation are inspiring. I have gained a deep AI and ML understanding. Hands-on projects prepared me for a successful career. The supportive environment and cutting-edge facilities made my journey incredible

Shivansh Srivastava
Department of Artificial Intelligence & Machine Learning

Manipal University Jaipurs AI and ML department is exceptional. Updated courses and hands-on opportunities create a hub for AI enthusiasts. The mentorship and collaboration are invaluable. MUJ is a springboard to exciting opportunities.

Achievements

Student Achievements
Faculty Achievements

Dean's list "Award of Excellence" Program

Student Academics Awards 2023

Hackathon prize

Mr. Arpit Singh Gautam awarded the certificate for the Best Contributor in DSA Domain to the PANACEA MUJ Repository.

Hackathon prize

Mr. Pratham Singhal received a cash prize for winning the world’s biggest Ethereum Hackathon ETHIndia 2022 held in Bengaluru..

T-Hunt Hackathon

Mr. Arpit Singh Gautam secure the title of MUJ Wizard Programmer by winning the T-Hunt Hackathon organized in MUJ.

National Engineering Olympiad

Mr. Nikhil Anand (2019-2023) perform outstanding in National Engineering Olympiad 6.0 with AIR 7.

Institute of Scholars

Researcher Excellence Award - Dr.Manish Rai

ICACCS-2023

Best Paper Award - Dr. Yadvendra Pratap Singh

RESEARCH

Exploring the unexplored

The areas of research include:
• Intercultural Philosophy • Eco-Philosophy • Technology and Human Values • Cross-cultural Philosophy of Religion • Peace Studies • Physical Education and Sports • Exercise Physiology • Sports Psychology • Sports Biomechanics • Health Education • Sports Management

Read more

HAPPENINGS @ FOEView all

News

Manipal University Jaipur spearheads Rajasthan's semiconductor journey with IESA.

Read more 07 Jun 2024

Dr Dinesh Yadav bags MTTS Outstanding Chapter Officer/Volunteer Award 2023 (R-10 India and Sri Lanka)

Read more 13 Dec 2023

Events

Conference on Flexible Electronics for Electric Vehicles (FlexEV-2024)

Read more 19 Dec 2024

5-days Professional Development Program on Verification and Testing

Read more 22 Jul 2024

CLUBS & CHAPTER

Abhigya Club

ACM

Nexus (Satellite Club MUJ)

Aperture

ASME

Autonomous Initiative

CARS

Coreografia

Design & Simulation Buro

Developer Student Clubs Manipal University Jaipur

Electronics Society

Glitch!

Hercampus

Humans of MJ

IE(I) MUJ Civil Engineering

IE(I) MUJ Mechatronics

IEEE APS Student Chapter

IEEE MTTS Student Chapter

IMechE

Innovader

INSTITUTE OF ENGINEERS (INDIA)

LearnIT

MarkSoc

MUJ OSA Student Chapter

OMPHALOS

PANACEA

PHI Phenomenon

Randomize

ROTARACT CLUB

RPM-SAE MUJ

SPIE Student Chapter Manipal University Jaipur

Techno Electricia

Turing Sapiens

Wings - The - Aeromodelling Club

BLOCKCHAIN@MANIPAL

ACM SIGAI

GlobalGrad

ECO-TECH EMPIRE

CYBER SPACE

MOTO MAVERICK

IEEE SENSORS COUNCIL

TYWI MUJ CHAPTER

VRsatile Club

AIML COMMUNITY

INDGenus MUJ Chapter

INDUSTRIAL COLLABORATIONS

EXPANDING Horizons

Dr. Puneet Mittal

Associate Professor & HoD Department of Artificial Intelligence & Machine Learning

puneet.mittal@jaipur.manipal.edu
9914114147

PHD, PUNJABI UNIVERSITY, PATIALA, 2020
M.TECH., PUNJABI TECHNICAL UNIVERSITY, 2012
B.TECH. ,PUNJABI TECHNICAL UNIVERSITY, 2005 \r\n

Speech Recognition & AI&ML\r\n

Gold Medal of the University for Academic Excellence in B.Tech, GATE 2011\r\n

M.Tech Coordinator\r\n
Class Coordinator III D\r\n
Discipline/ Grievance\'s Redressal Committee \r\n

CSI
ISTE
IEI
IAENG\r\n

P. Mittal and N. Singh, \"Subword analysis of small vocabulary and large vocabulary ASR for Punjabi language,\" International Journal of Speech Technology, vol. 23, no. 1, pp. 71-78, Jan. 2020, doi: https://doi.org/10.1007/s10772-020-09673-3.
P. Mittal and N. Singh, \"Development and analysis of Punjabi ASR system for mobile phones under different acoustic models,\" International Journal of Speech Technology, vol. 22, no. 1, pp. 219-230, Jan. 2019, doi: https://doi.org/10.1007/s10772-019-09593-x.
P. Mittal and N. Singh, \"Speaker-Independent Automatic Speech Recognition System for Mobile Phone Applications in Punjabi,\" Advances in Intelligent Systems and Computing, pp. 369-382, Sep. 2017, doi: https://doi.org/10.1007/978-3-319-67934-1_33
P. Mittal and S. Sharma, \"Automatic Speech Recognition Models, Tools, and Techniques,\" pp. 18-40, Dec. 2022, doi: https://doi.org/10.4018/978-1-6684-6001-6.ch002.
P. Sachin, N. Correa, A. H. Shenoy, A. C. Ballal and P. Mittal, \"Gender and Emotion Classification By Hierarchical Modelling Using Convolutional Neural Network,\" 2022 2nd Asian Conference on Innovation in Technology (ASIANCON), Ravet, India, 2022, pp. 1-6, doi: 10.1109/ASIANCON55314.2022.9908796.\r\n

Mr. Abhishek Kesarwani

Assistant Professor Department of Artificial Intelligence & Machine Learning

abhishek.kesarwani@jaipur.manipal.edu
8987490027

PHD, NIT, DURGAPUR, PURSUING
M.TECH., NIT, ROURKELA, 2018
B.E., CHHATTISGARH SWAMI VIVEKANAND TECHNICAL UNIVERSITY ,2016

Image Processing
Deep Learning

GATE 2016
GATE 2017
UGC-NET 2019

Section Coordinator

KPI 40

IEEE

A. Kesarwani, S. Das, M. Dalui, D.R. Kisku, B. Sen, S. Roy, and A. Basu, "Non-invasive anaemia detection by examining palm pallor: A smartphone-based approach," Biomedical Signal Processing and Control, vol. 79, p. 104045, 2023, doi: https://doi.org/10.1016/j.bspc.2022.104045
A. Kesarwani and P.M. Khilar, "Development of trust-based access control models using fuzzy logic in cloud computing," Journal of King Saud University-Computer and Information Sciences, vol. 34, no. 5, pp. 1958-1967, May 2022, doi: https://doi.org/10.1016/j.jksuci.2019.11.001
A. Kesarwani, S. Das, M. Dalui, and D.R. Kisku, "Non-invasive Haemoglobin Estimation Using Different Colour and Texture Features of Palm," International Conference on Computer Vision and Image Processing, pp. 176-189, November 2022, Cham: Springer Nature Switzerland, doi: https://doi.org/10.1007/978-3-031-31417-9_14
A. Kesarwani, K. Purohit, M. Dalui, and D.R. Kisku, "Measuring the degree of suitability of edge detection operators prior to an application," 2020 IEEE Applied Signal Processing Conference (ASPCON), pp. 128-133, October 2020, IEEE, doi: https://doi.org/10.1109/ASPCON49795.2020.9276678
S. Das, A. Kesarwani, M. Dalui, D.R. Kisku, B. Sen, S. Roy, and A. Basu, "Smartphone-based non-invasive haemoglobin level estimation by analyzing nail pallor," Biomedical Signal Processing and Control, vol. 85, pp. 104959, March 2023, doi: https://doi.org/10.1016/j.bspc.2023.104959

Dr. Amit Kumar Bairwa

Assistant Professor (Selection Grade) Department of Artificial Intelligence & Machine Learning

amitkumar.bairwa@jaipur.manipal.edu
9799606918

PHD, MANIPAL UNIVERSITY JAIPUR, 2021
MTECH, RAJASTHAN TECHNICAL UNIVERSITY KOTA, 2014
BE, UNIVERSITY OF RAJASTHAN ,2004

Computer Networking
Security Linux

Young Researcher 2023
Dr. Ram das Pai Award for Professional Excellence 2023
Young Researcher 2022
Honorary Rosalind Member of London Journals Press 2021

M. Tech. Coordinator
ODL Course content development
Faculty Club Coordinator

M.Tech Coordinator

Membership of IEEE with membership no. 92082913
Membership of Association for Computing Machinery (ACM) with membership no. 6190848
Membership of The Indian Society for Technical Education (ISTE) with membership no. LM 109716.

Akshit Kamboj, Priyanshu Kumar, Amit Kumar Bairwa, Sandeep Joshi, Detection of malware in downloaded files using various machine learning models, Egyptian Informatics Journal, 2022, ISSN 1110-8665, https://doi.org/10.1016/j.eij.2022.12.002.
Jeril Kuriakose, Sandeep Joshi, Amit Kumar Bairwa, EMBN-MANET: A method to Eliminating Malicious Beacon Nodes in Ultra-Wideband (UWB) based Mobile Ad-Hoc Network, Ad Hoc Networks, Volume 140, 2023, 103063, ISSN 1570-8705, https://doi.org/10.1016/j.adhoc.2022.103063.
Amit Kumar Bairwa, Sandeep Joshi, Dilbag Singh, "Dingo Optimizer: A Nature-Inspired Metaheuristic Approach for Engineering Problems", Mathematical Problems in Engineering, vol.2021, Article ID 2571863, 12 pages, 2021. https://doi.org/10.1155/2021/2571863
Amit Kumar Bairwa, Sandeep Joshi, "Mutual authentication of nodes using session token with fingerprint and MAC address validation", Egyptian Informatics Journal, 2021, ISSN 1110-8665.https://doi.org/10.1016/j.eij.2021.03.003
Amit Kumar Bairwa, and Sandeep Joshi,"An agent-based routing search methodology for improving QoS in MANET", Ingeniare. Revista chilena de ingenier ́ıais, Volume 28 N 4,December 2020 http://dx.doi.org/10.4067/S0718-33052020000400558

Dr. Deepak Panwar

Associate professor Department of Artificial Intelligence & Machine Learning

deepak.panwar@jaipur.manipal.edu
7725928669

PHD, GAUTAM BUDDHA UNIVERSITY, GAUTAM BUDH NAGAR, UTTAR PRADESH ,2018
M.TECH., GAUTAM BUDDHA UNIVERSITY, GAUTAM BUDH NAGAR, UTTAR PRADESH ,2011
B.TECH., UTTAR PRADESH TECHNICAL UNIVERSITY, 2009

Computational Intelligence
Software Engineering

Academic Audit Coordinator
Semester Coordinator
Exam Cell Member

ACM
CSI
IEEE

ISSN: 2367- 3370, Series: https://www.springer.com/series/15179.
2022. DOI: - 10.46338/ijetae0522.15.
D. Panwar and P. Tomar, 'New mathematical model for software quality prediction of component-based software using shuffled frog-leaping algorithm', International Journal of Computer Applications in Technology, vol. 55, no. 4. Inderscience Publishers, p. 266, 2017. doi: 10.1504/ijcat.2017.086014.
D. Panwar, G. L. Saini, and P. Agarwal, 'Human Eye Vision Algorithm (HEVA): A Novel Approach for the Optimization of Combinatorial Problems', Artificial Intelligence in Healthcare. Springer Singapore, pp. 61-71, Oct. 30, 2021. doi: 10.1007/978-981-16-6265-2_5.
G. L. Saini, D. Panwar, S. Kumar, V. Singh, and R. C. Poonia, 'Predicting of Open Source Software Component Reusability Level Using Object-Oriented Metrics by Taguchi Approach', International Journal of Software Engineering and Knowledge Engineering, vol. 31, no. 02. World Scientific Pub Co Pte Lt, pp. 147-166, Feb. 2021. doi: 10.1142/s0218194021500030.

Mr. Deepjyoti Choudhury

Assistant Professor (Senior Scale) Department of Artificial Intelligence & Machine Learning

deepjyoti.choudhury@jaipur.manipal.edu
9508756084

PHD ,ASSAM UNIVERSITY, SILCHAR, PURSUING
M.TECH., ASSAM UNIVERSITY, SILCHAR, 2013
B.TECH., NAGALAND UNIVERSITY ,2011

Social Networks Analysis
Machine Learning
Cloud Computing

GATE 2011
Earned global certifications,namely "Microsoft Azure Fundamentals" on 6th May 2021, "Microsoft Azure Data Fundamentals" on 29th May 2021 and "Microsoft Azure AI Fundamentals" on 26th June 2021.

Class Coordinator
KPI 13 and 29
PAC 3.5,Dept. BoS member

D. Choudhury, T. Acharjee, "A Novel Approach to Fake News Detection in Social Networks using Genetic Algorithm Applying Machine Learning Classifiers", Multimedia Tools And Applications, Springer Nature, Article: 12788, 2022
D. Choudhury, T. Acharjee, "A Scalable Approach for Strengthening Social Media Ties Using Multi-Dimensional Analysis", Revue d'Intelligence Artificielle, Vol. 37, No. 4, 2023
D. Choudhury, T. Acharjee, "An Empirical Analysis of Naïve Bayes, SVM, Logistic Regression and Random Forest to Spot False Information in Real-World Networks", International Conference on Intelligent Controller and Computing for Smart Power, Hyderabad, 21st-24th July 2022
D. Choudhury, T. Acharjee, "A Swarm Intelligence Based Community Detection Algorithm in Social Networks", 4th International Conference on Artificial Intelligence and Speech Technology, IGDTUW Delhi, 9th-10th December 2022
D. Choudhury, T. Acharjee, "Effective Estimation of Relationship Strength among Facebook Users Applying Pearson Correlation and Jaccard's Coefficient", Doctoral Symposium on Human Centered Computing (HUMAN 2023), Kolkata, 25th February 2023.

Dr. Gautam Kumar

Associate Professor Department of Artificial Intelligence & Machine Learning

gautam.kumar@jaipur.manipal.edu
+91-8262001726

PHD, JAYPEE UNIVERSITY OF INFORMATION TECHNOLOGY, 2017
M.TECH., RAJASTHAN TECHNICAL UNIVERSITY, 2012
B.E., RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL, 2005

Cryptography
Information Security
Algorithms Designs

3 Published Books with International Repute(Taylor and Francis and Springer)
Best Teacher and Best Researcher Award

KPI 2 and KPI-11,In Conference Organization

Lab Incharge

IAENG

Lakshmanna, F. Shaik, V. K. Gunjan, N. Singh, Gautam Kumar, R. Mahammad Shafi, "Perimeter Degree Technique for the Reduction of Routing Congestion during Placement in Physical Design of VLSI Circuits", Complexity, vol. 2022, Article ID 8658770, 11 pages, 2022. https://doi.org/10.1155/2022/8658770
Gautam Kumar and Hemraj Saini, "Novel Noncommutative Cryptography Scheme using Extra Special Group," Security and Communication Networks, John Wiley & Sons, Vol. 2017, Issue 5, pp. 1-21, January 2017. DOI: 10.1155/2017/9036382.
Gautam Kumar and Hemraj Saini "Secure and Robust Telemedicine using ECC on Radix-8 with Formal Verification," International Journal of Information Security and Privacy, IGI Global Publishing, Vol. 12, Issue 1, pp. 13-28, 2018.
Gautam Kumar and Hemraj Saini "Effective Signcryption Approach for Secure Convention for Multilayer Consensus using ECC," International Journal of Security and its Applications, Science & Engineering Research Support Society, Vol. 10, No. 7, pp. 287-306, 2016.
Nguyen Ha Huy Cuong, GautamKumar, and Vijender Kumar Solanki, "Blockchain based Digital Right Management Techniques", Large-Scale Data Streaming, Processing, and Blockchain Security, IGI Global, pp. 168-180, 2020. DOI: 10.4018/978-1-7998-3444-1.ch008

Dr. Harish Kumar Shakya

Associate Professor Department of Artificial Intelligence & Machine Learning

harish.shakya@jaipur.manipal.edu
8979093747

PHD, IIT (BHU) ,2018
M.E., SHRI G.S. INSTITUTE OF TECHNOLOGY & SCIENCE, INDORE ,2009
B.E., RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALA, BHOPAL, 2005

Social Networks Analysis
Soft Computing

Qualified GATE-2006
UGC JRF RGNF Fellowship Award (2012-2014)
UGC SRF RGNF Fellowship Award (2014-2017)

Departmental Exam Coordinator

ACM Membership ID # 1718955
IEEE Membership ID # 93946210
IEICE Membership ID # 1783700
IEI (India) Membership ID # AM1757078
IETE Membership ID # AM500866
FELLOW IETE,AMIEI
IAENG Membership ID # 195822
ICSES Membership ID # 1910
CSTA Membership ID # 50227342
SAISE Membership ID # 20180607001
IACSIT Membership ID # 80347113
MIR Labs Membership ID #1621

Shakya, H.K., Singh, K., More, Y.S. et al. Opposition-Based Genetic Algorithm for Community Detection in Social Networks. Proc. Natl. Acad. Sci., India, Sect. A Phys. Sci.92, 251-263(2022). https://doi.org/10.1007/s40010-020-00716-7
Shakya H K et al. ,"Internet of Things-Based Intelligent Ontology Model for Safety Purpose Using Wireless Networks", Wireless Communications and Mobile Computing, Hindawi journal, ISSN:1530-8669 May 2022. https://doi.org/10.1155/2022/1342966
Kuldeep Singh, Ajay Kumar, Shashank Sheshar Singh, Harish Kumar Shakya, and Bhaskar Biswas, "EHNL: An efficient algorithm for mining high utility itemsets with negative utility value and length constraints", in Information Sciences, Elsevier, 2019, ISSN: 0020-0255.https://doi.org/10.1016/j.ins.2019.01.056
Kuldeep Singh, Harish Kumar Shakya, Abhimanyu Singh, Bhaskar Biswas," Mining of high‐utility itemsets with negative utility", Expert Systems, wiley, ISSN: 1468-0394.https://doi.org/10.1111/exsy.12296
Suruchi Karnani & Harish Kumar Shakya (2022) Mitigation strategies for distributed denial of service (DDoS) in SDN: A survey and taxonomy, Information Security Journal: A Global Perspective,DOI: 10.1080/19393555.2022.2111004

Mr. Harish Sharma

Assistant Professor (Senior Scale) Department of Artificial Intelligence & Machine Learning

harish.sharma@jaipur.manipal.edu
88529 04048

MTECH ,DHIRUBHAI AMBANI INSTITUTE OF INFORMATION & COMMUNICATON TECHNOLOGY, 2011
BE, UNIVERSITY OF RAJASTHAN, 2008

Machine Learning
Information Retrieval
Image Processing
Data Science

GATE (2007)
GATE(2009)
Young Researcher award(2022)

Nucleus Member (Corporate Relation & Placement)

Section Coordinator

ACM
IEEE
IEEE-CIS

Development, in conference proceedings by Springer LNNS.
2459, Scopus Indexed, ISO 9001:2008 Certified Journal, Volume 12, Issue 05, May
2019 E-ISSN: 2347-2693
2520(2021)

Dr. Hemlata Parmar

Assistant Professor Department of Artificial Intelligence & Machine Learning

hemlata.parmar@jaipur.manipal.edu
7988867668

PHD, KALINGA UNIVERSITY, 2021
M.TECH., MAHARSHI DAYANAND UNIVERSITY ROHTAK, 2016
B.TECH., MAHARSHI DAYANAND UNIVERSITY ROHTAK, 2014

Network Security & Cryptography

Section coordinator

KPI-(28,30,40)
Mentor-Mentee Coordinator

IAEG

Hemlata "Enhancement Of Security By Infrared Arrays Sensor-Based IoT System" Innovative Practices In Technology And Management (ICIPTM) IEEE Conference at Amity University.
Hemlata ".Modern Technique Of Encryption And Decryption Based On Image" Innovative Practices in Technology And Management (ICIPTM) IEEE Conference at Amity University.
Hemlata "Role of Neural Network, Fuzzy, and IoT in Integrating Artificial Intelligence as A Cyber Security System" Second International Conference on Electronic and renewable systems, St. Mother Theresa Engineering College, Tuticorin, India.
Hemlata "Revolutionizing Hand Gesture Recognition: A transfer Learning Approach using Surface Electromyography and Convolution Neural Networks. "Second International conference on Augmented Intelligence and sustainable system", Trichy, India.

Dr. Jaydeep Kishore

Assistant Professor (Selection Grade) Department of Artificial Intelligence & Machine Learning

jaydeep.kishore@jaipur.manipal.edu
9410104408

PHD, SHIV NADAR UNIVERSITY, NCR, COMPLETED 2024
M.TECH., UTTARAKHAND TECHNICAL UNIVERSITY, DEHRADUN, 2010
B.TECH., UTTAR PRADESH TECHNICAL UNIVERSITY, 2005

Deep Learning
Computer Vision
NAS, SSL

GATE (2020)
Research Fellowship

Departmental webpage
school webpage

Section Coordinator
KPI 8 and 9

ISOC
IAENG

Jaydeep Kishore, Snehasis Mukherjee, "Minimizing Parameter Overhead in Self Supervised Models for Target Task" IEEE transaction on artificial Intelligence, https://doi.org/10.1109/TAI.2023.3322394
Jaydeep Kishore, Snehasis Mukherjee, "Auto CNN classifier based on knowledge transferred from self-supervised model", Applied Intellegence, Springer (2023): 1--19, https://doi.org/10.1007/s10489-023-04598-1
Jaydeep Kishore, Snehasis Mukherjee, "Impact of Autotuned Fully Connected Layers on Performance of Self-supervised Models for Image Classification.", Machine Intellegence Research, Springer, https://doi.org/10.1007/s11633-023-1435-7
Mohd Mursleen, Ankur Singh Bisht,Jaydeep Kishore ``A Support Vector Machine Water Wave Optimization Algorithm Based Prediction Model for Metamorphic Malware Detection.International Journal of Recent Technology and Engineering (IJRTE) IJRTE ISSN: 2277-3878. Volume-7, Issue-5 (2019)
Diva Pant, Vishal Kumar, Jaydeep Kishore, Ritu Pal. ``Healthcare Data Modeling in R", IEEE 1st International Conference on Intelligent Systems and Information Management (ICISIM-2017), Orangabad, India

Dr. Jayesh Gangrade

Associate Professor Department of Artificial Intelligence & Machine Learning

jayesh.gangrade@jaipur.manipal.edu
8435717932

PHD, MAULANA AZAD NATIONAL INSTITUTE OF TECHNOLOGY, BHOPAL (NIT), 2020
M.TECH., MAULANA AZAD NATIONAL INSTITUTE OF TEHNOLOGY, BHOPAL (NIT) ,2008
B.E., RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALA, BHOPAL ,2003

Machine Learning
Computer Vision

5 Time GATE Qualified

Directoaret of Academics
Registrar Office

BoS Coordintor
Value Added Courses Coordinator
Patent Drafting and Submission
Course Coordinator
Class Coordinator
SFR & Faculty Requirement

G. Jayesh and J. Bharti, "Vision-based hand gesture recognition for Indian sign language using convolution neural network," IETE Journal of Research, vol. 69, no. 2, pp. 723-732, Feb. 2023.
J. Gangrade, J. Bharti, and A. Mulye, "Recognition of Indian sign language using ORB with bag of visual words by Kinect sensor," IETE Journal of Research, vol. 68, no. 4, pp. 2953-2967, Apr. 2022.
Shrivastava, Hemang, et al. "Network analysis of infant brain functional connectivity using spectral EEG." International Journal of Electronic Healthcare 12.2 (2022): 139-150.
P. Upadhyay, J. Gangrade, and S. Gangrade, "Comparative Analysis of Optimized Twin Support Vector Machine and Twin Bounded Support Vector Machine."
D. Desai, et al., "Deep transfer learning for Multiple Sclerosis Detection and classification using pre-trained model," 2023.

Dr. Manish Rai

Assistant Professor (Senior Scale) Department of Artificial Intelligence & Machine Learning

manish.rai@jaipur.manial.edu
9755482055

PHD, RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL, COMPLETED 2024
M.TECH., RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL, 2013
B.E., RAJIV GANDHI PROUDYOGIKI VISHWAVIDYALAYA, BHOPAL, 2009

Machine Learning
Networki Security
Image Processing

Research excellence award 2023 frm insc institue of scholar

Class coordinator
OBE Coordinator
Course File Coordinator
KPI 1,13

Rai, M., Goyal, S. & Pawar, M. An Optimized Deep Fusion Convolutional Neural Network-Based Digital Color Image Watermarking Scheme for Copyright Protection. Circuits Syst Signal Process (2023). https://doi.org/10.1007/s00034-023-02299-1
Rai, M., Goyal, S. A hybrid digital image watermarking technique based on fuzzy-BPNN and shark smell optimization. Multimed Tools Appl 81, 39471-39489 (2022). https://doi.org/10.1007/s11042-022-12712-7
Rai, M., Goyal, S., Pawar, M ."An enhanced digital image watermarking technique using DWT-HDSVD and deep convolutional neural network" Int. J. Critical Computer-Based Systems, 2022 https://www.inderscience.com/info/ingeneral/forthcoming.php?jcode=ijccbs
Rai, M., Goyal, S., Pawar, M. (2021). Feature Optimization of Digital Image Watermarking Using Machine Learning Algorithms. In: Bajpai, M.K., Kumar Singh, K., Giakos, G. (eds) Machine Vision and Augmented Intelligence-Theory and Applications. Lecture Notes in Electrical Engineering, vol 796. Springer, Singapore. https://doi.org/10.1007/978-981-16-5078-9_39
S. B, L. Ganu, M. Rai, S. Kaliappan, R. Maranan and J. V, "Convolution Neural Network and EVO Based Efficient Method for Detecting Nerve Disorders," 2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS), Trichy, India, 2023, pp. 303-308, doi: 10.1109/ICAISS58487.2023.10250521.

Mr. Prashant Hemrajani

Assistant Professor (Selection Grade) Department of Artificial Intelligence & Machine Learning

Dr. Preeti Narooka

Assistant professor (Selection Grade) Department of Artificial Intelligence & Machine Learning

preeti.narooka@jaipur.manipal.edu
9022297778

PHD, BANASTHALI VIDYAPITH, 2018
M.TECH., BANASTHALI VIDYAPITH, 2012
B.TECH., RAJASTHAN TECHNICAL UNIVERSITY, KOTA, 2010

Big Data
High Performance Computing

SPONSORED PROJECT - 4.72 L

KPI Co-Coordinator
Timetable Co-Coordinator
Course Coordinator Class Coordinator

IAENG
ISTE
IFERP
CSTA

M. Diwakar, P. Singh, G. R. Karetla, P. Narooka,(2022). Low-Dose COVID-19 CT Image Denoising Using Batch Normalization and Convolution Neural Network. Electronics, 11(20), 3375.
P. Narooka, & S. Choudhary (2017, January). Optimization of the search graph using Hadoop and Linux Operating System. In 2017 International Conference on Nascent Technologies in Engineering (ICNTE) (pp. 1-6). IEEE.
P. Narooka, & S. Choudhary (2017, January). Optimization of the search graph using Hadoop and Linux Operating System. In 2017 International Conference on Nascent Technologies in Engineering (ICNTE) (pp. 1-6). IEEE.
S. Choudhary & P. Narooka, (2016, December). Hugepage & Swappiness functions for optimization of the search graph algorithm using Hadoop framework. In 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) (pp. 1-5). IEEE.
P., Narooka, & S. Choudhary, (2016). Performance Evaluation of BigData Analysis with Hadoop in Various Processing Systems. International Journal of Scientific and Engineering Research (IJSER)-(ISSN 2229-5518), IJSER, 7(10).

Dr. Priya Goyal

Assistant Professor (Selection Grade) Department of Artificial Intelligence & Machine Learning

priya.goyal@jaipur.manipal.edu
09999093376

PHD, MVN UNIVERSITY, FARIDABAD, 2022
M.TECH., MAHARSHI DAYANAND UNIVERSITY ROHTAK, 2012
B.E., MAHARSHI DAYANAND UNIVERSITY ROHTAK, 2007

AIML
Big Data Analytics
NLP
Deep Learning

Exam Cell Member

section coordinator

Identification of Political Hate Speech Using Machine Learning Based TextToxicity
Hate Speech Detection using OpenAI and GPT3 in International Journal of Emerging
Review Paper on Big Data with Comparative Analysis of Hadoop"
Priya, Dr. Sachin Gupta, presented paper "A Contemporary Analysis of Hate Speech
Trust-Based Multi-Attribute Decision Making System for Social Networks

Ms. Shubh Lakshmi Agrwal

Assistant Professor (Selection Grade) Department of Artificial Intelligence & Machine Learning

shubh.agrwal@jaipur.manipal.edu
9414481213

PHD, THE LNM INSTITUTE OF INFORMATION TECHNOLOGY, JAIPUR, PURSUING
M.TECH., MNIT, JAIPUR, 2011
B.E., UNIVERSITY OF RAJASTHAN, 2006

Machine Learning
Deep Learning
Image processing
NLP
Data Science

Mentor
Course coordinator
Registration Coordinator

Section Coordinator
KPI 1

Shubh Lakshmi Agrwal et al. "Facial gender recognition using Gabor-DCT feature extraction." Journal of Statistics and Management Systems 22, no. 4 (2019): 719-728.
Shubh Lakshmi Agrwal et al.,"Facial Gender Analysis Using Gabor-DWT Feature Extraction Method", International Journal of Engineering and Advanced Technology (IJEAT), Volume-9 Issue-2, December 2019.
Shubh Lakshmi Agrwal et al."An improved average Gabor wavelet filter feature extraction technique for facial expression recognition." International Journal on Innovations in Engineering and Technology 2 (2013): 1058-2319.
Shubh Lakshmi Agrwal et al., "New improved feature extraction approach of IRIS recognition." International Journal of Computer Systems 3, no. 1 (2016): 1-3.
Shubh Lakshmi Agrwal et al., "An efficient hybrid technique of feature extraction for facial expression recognition using AdaBoost Classifier." International Journal of Engineering Research & Technology 8, no. 1 (2012).

Mr. Siddharth Kumar

Assistant Professor Department of Artificial Intelligence & Machine Learning

Siddharth.kumar@jaipur.manipal.edu
9570641992

PHD, INDIAN INSTITUTE OF INFORMATION TECHNOLOGY, RANCHI, THESIS SUBMITTED
M.TECH., CENTRAL UNIVERSITY OF PUNJAB, 2015
B.TECH., BIJU PATNAIK UNIVERSITY OF TECHNOLOGY, ROURKELA, ODISSA, 2012

Data Science
Machine Learning
Deep Learning
GIS and Remote Sensing

GATE 2014
UGC NET JRF 2018

Associated with Academic Audit

Kumar, S., Pati, J. Machine learning approach for assessment of arsenic levels using physicochemical properties of water, soil, elevation, and land cover. Environ Monit Assess 195, 641 (2023). https://doi.org/10.1007/s10661-023-11231-8
Kumar, S., & Pati, J. (2022). Assessment of groundwater arsenic contamination level in Jharkhand, India using machine learning. Journal of Computational Science, 63, 101779. https://doi.org/10.1016/j.jocs.2022.101779
Kumar, S., & Pati, J. (2022). Assessment of groundwater arsenic contamination using machine learning in Varanasi, Uttar Pradesh, India. Journal of Water and Health, 20(5), 829-848. https://doi.org/10.2166/wh.2022.015
Arghya Chattopadhyay, Anand Prakash Singh, Siddharth Kumar, Jayadeep Pati, Amitava Rakshit; The machine learning and geostatistical approach for assessment of arsenic contamination levels using physicochemical properties of water. Water Sci Technol 1 August 2023; 88 (3): 595-614. doi: https://doi.org/10.2166/wst.2023.231
Kumar, A., Kumar, S., Rautela, K. S., Shekhar, S., Ray, T., & Thangavel, M. (2023). Assessing seasonal variation and trends in rainfall patterns of Madhya Pradesh, Central India. Journal of Water and Climate Change, jwc2023280. https://doi.org/10.2166/wcc.2023.280

Ms. Simran

Assistant Professor (Adhoc) Department of Artificial Intelligence & Machine Learning

Network Security
blockchain

Best Anchor in IEEE event at Chandigarh University
Faculty Representative in IEEE Photonics Society.

Event Coordinator

IEEE Faculty Membership

S. Kaur and J. Singh, "Enhancing Medical Image Analysis and Disease Surveillance in Healthcare: A Study on PSO- ACO Optimization using Swarm Intelligence," 2023 2nd International Conference on Computational Modelling, Simulation and Optimization (ICCMSO), Bali, Indonesia, 2023, pp. 269-276, doi: 10.1109/ICCMSO59960.2023.00058
Simran and J. Singh, "A Comprehensive Survey of PSO-ACO Optimization and Swarm Intelligence in Healthcare: Implications for Medical Image Analysis and Disease Surveillance," 2023 3rd Asian Conference on Innovation in Technology (ASIANCON), Ravet IN, India, 2023, pp. 1-6, doi: 10.1109/ASIANCON58793.2023.10270025.

Ms. Sri Geetha M

Assistant Professor (Selection Grade) Department of Artificial Intelligence & Machine Learning

Machine Learning
Deep Learning
NLP

SIH WINNER 2 teams
Institutional Best Faculty award
Best project for product development by TITAN & 1.5 Lac Tata motors hackathon winner and best mentor

Served as KSI LEAD- Curriculum Design and Development for computing cluster comprising CSE, AI&DS, IT, ISE, MBA-IEV, B.Sc DS

NBA CRITERIA III Coordinator
Hackathon coordinator
FOSS& GDSC CLUB faculty coordinator
DQAC member
magazine editor
Dept Student grievences cell incharge

CSI
IAENG

M. Sri Geetha, M. Sujay Sudharshan, S. Sunderesh, P. Aruna & M. Sanjana Sri " Enhanced Video Articulation (EVA)-A Lip-Reading Tool" Advances in Computational Intelligence and Communication Technology pp 147-156, doi:10.1007/978-981-16-9756-2_14
Sri Geetha, M. and Grace Selvarani, A. 'Breast Cancer Classification Using Hybrid Deep Neural Networks: Staging and Grading of Cancer'.Journal of intelligent and fuzzy systems,DOI: 10.3233/JIFS-231345, 1 Jan. 2023 :vol. 45, no. 6, pp. 10281 - 10294.. M. Sri Geetha, R. Yashwanthika, M. Sanjana Sri, M. Sudiksa,"GenSQL-NLP-Based SQL Generation", SustainableCommunication Networks and Application, LNDECT, DOI:10.1007/978-981- 16-6605-6_20, ISSN: 2367- 4512, Vol.93, pp.279-288
P. S, K. S. M.S, S. S, R. Kingsy Grace and M. Sri Geetha, "Abstractive Summarizer using Bi-LSTM," 2022 International Conference on Edge Computing and Applications (ICECAA), Tamilnadu, India, 2022, pp. 1605-1609, doi: 10.1109/ICECAA55415.2022.9936215.
Sri Geetha M, Dr. A. Grace Selvarani, Dr. Ravi Kumar, Dr.Sheshang Degadwala, Ravi Kishore Veluri, "Automatic Detectionand Classification Of Melanoma Skin Cancer through DeepLearning Techniques", NVEO- Natural Volatiles and Essential Oils,E-ISSN:2148-9637,Vol.8,no.5,pp.7584-7594

Ms. Stuti Pandey

Assistant Professor Department of Artificial Intelligence & Machine Learning

Multimedia
Blockchain
Software Engineering

Semi-Finalist of Eureka (International Business Plan Competition) at IIT BOMBAY
Third Winner of National Entrepreneurship Challenge (NEC) at IIT BOMBAY

Life Member of CRSI
Membership ID: L/0586

Stuti Pandey, Nihar Ranjan Pradhan, Akhilendra Pratap Singh, Dharmender Singh Kushwaha, "Perceptual Hash Computation of Multimedia Objects using Improved K-L Transform", 2nd International Symposium on Sustainable Energy and Technological Advancements (ISSETA 2023), February 24-25, 2023.
Stuti Pandey, Ashish Pandey, Nihar Ranjan Pradhan, Akhilendra Pratap Singh, Vinay Kumar, "Addressing Scheme for Three-Dimensional Central Triangular Matrices in Linear Arrays", IEEE IAS Global Conference on Emerging Technologies (GlobConET-2022), May 20-22, 2022. DOI: 10.1109/GlobConET53749.2022.9872468
Stuti Pandey, Nihar Ranjan Pradhan, Akhilendra Pratap Singh, Dharmender Singh Kushwaha, "Copyright Infringement Detection of Multimedia Objects using K-L Transform", 4th International Conference on Energy, Power and Environment (ICEPE-2022), April 29-May 01, 2022. DOI: 10.1109/ICEPE55035.2022.9798179
Stuti Pandey and Abhay Kumar Agarwal, "Machine Learning Approaches for Cardiovascular Disease Prediction: A Survey", Computational Methodologies for Electrical and Electronics Engineers, IGI Global, March 2021, Chapter 6, Pp. 75-84. ISBN: 9781799833277" DOI: 10.4018/978-1-7998-3327-7
Stuti Pandey and Abhay Kumar Agarwal, "Comparison of machine learning algorithms for cardiovascular disease prediction", Computational Methodologies for Electrical and Electronics Engineers, IGI Global, March 2021, Chapter 9, Pp. 111-126. ISBN: 9781799833277" DOI: 10.4018/978-1-7998-3327-7

Mr. Surendra Solanki

Assistant Professor Department of Artificial Intelligence & Machine Learning

PHD, MAULANA AZAD NIT, BHOPAL, SUBMITTED
M.TECH., MAULANA AZAD NIT, BHOPAL, 2017
B.E., DEVI AHILYA VISHVAVIDHYALAYA, INDORE, 2012

Cognitive Radio Network
Deep Learning

GATE 2014
GATE 2016
UGC-NET 2017

SAS FDP Nov 2023
KPI 1

S. Solanki, et al., "Spectrum Sensing in Cognitive Radio Using CNN-RNN and Transfer Learning," IEEE Access, vol. 10, no. -, pp. 113482-113492, 2022, DOI: 10.1109/ACCESS.2022.3216877
S. Solanki, V. Dehalwar, and J. Choudhary, "Deep learning for spectrum sensing in cognitive radio," Symmetry, vol. 13, no. 1, pp. 147, Jan. 2021, DOI: 10.3390/sym13010147.
S. Solanki, V. Dehalwar, and J. Choudhary, "Cooperative spectrum sensing for PU detection in cognitive radio using SVM," in Data Engineering and Communication Technology: Proceedings of ICDECT 2020, Springer Singapore, 2021.
V. Dehalwar, S. Solanki et al., "Blockchain based Device identification and authentication in a Smart Grid," in 2020 5th International Conference on Smart and Sustainable Technologies (SpliTech), IEEE, 2020.
J. Bharti, S. Solanki, and A. Beliya, "Comparison of LSB methods and pattern," in 2017 International Conference on Recent Innovations in Signal processing and Embedded Systems (RISE), IEEE, 2017.

Dr. Uddalak Chatterjee

Information security

Best paper award received from CSI kolkata chapter and NITTTR, chandigrah.

Chatterjee, U., Ray, S., Khan, M. K., Dasgupta, M., & Chen, C. M. (2022). An ECC-based lightweight remote user authentication and key management scheme for IoT communication in context of fog computing. Computing, Springer,104(6), 1359-1395.
Chatterjee, U., Ray, S., Adhikari, S., Khan, M. K., & Dasgupta, M. (2023). An improved authentication and key management scheme in context of IoT-based wireless sensor network using ECC. Computer Communications, Elsevier, 209, 47-62.
Chatterjee, U., Ray, S., Sadhukhan, D., & Dasgupta, M. (2023). An improved authentication and key management scheme for hierarchical IoT network using elliptic curve cryptography. Innovations in Systems and Software Engineering, 19(3), 231-246.
Chatterjee, U., Ray, S., Adhikari, S., Khan, M. K., & Dasgupta, M. (2023). Efficient and secure e‐voting scheme using elliptic curve cryptography. Security and Privacy, 6(3), e283.
Chatterjee, U., Sadhukhan, D., & Ray, S. (2020). An improved authentication and key agreement protocol for smart healthcare system in the context of internet of things using elliptic curve cryptography. In Proceedings of international conference on IoT inclusive life (ICIIL 2019), NITTTR Chandigarh, India (pp. 11-22). Springer Singapore.

Dr. Upendra Singh

Assistant Professor Department of Artificial Intelligence & Machine Learning

upendra.singh@jaipur.manipal.edu
+91 8107 271701

PHD , BITS PILANI , 2023
M.TECH. , JAGANNATH UNIVERSITY, 2013
B.E., UNIVERSITY OF RAJASTHAN, 2009

Computer Network & Resource Allocation

Timetable Coordinator and Exam Cell Member

IEEE

Rajput, N.S., Singh, U., Dua, A., Kumar, N., Rodrigues, J.J., Sisodia, S., Elhoseny, M. and Lakys, Y., "Amalgamating Vehicular Networks With Vehicular Clouds, AI, and Big Data for Next-Generation ITS Services," in IEEE Transactions on Intelligent Transportation Systems, 2023, doi: 10.1109/TITS.2023.3234559.
U. Singh, A. Dua, N. Kumar and M. Guizani, "QoS Aware Uplink Scheduling for M2M Communication in LTE/LTE-A Network Game-Theoretic Approach," in IEEE Transactions on Vehicular Technology, vol. 71, no. 4, pp. 4156-4170, 2021, DOI: 10.1109/TVT.2021.3132535.
Singh, U., Dua, A., Kumar, N., Tanwar, S., Iqbal, R., Hijji, M., Amin, S. and Sharma, R., 2022. Scalable priority-based resource allocation scheme for M2M Communication in LTE/LTE-A network. Computers and Electrical Engineering, 103, p.108321.
U. Singh, A. Ramaswamy, A. Dua, N. Kumar, S. Tanwar, G. Sharma, I. E. Davidson, R. Sharma, "Coalition Games for Performance Evaluation in 5G and Beyond Networks: A Survey," in IEEE Access, DOI: 10.1109/ACCESS.2022. 3146158
U. Singh, A. Dua, S. Tanwar, N. Kumar, and M. Alazab, "A Survey on LTE/LTE-A Radio Resource Allocation Techniques for Machine-to-Machine Communication for B5G Networks," in IEEE Access, vol. 9, pp. 107976-107997, 2021, DOI: 10.1109/ACCESS.2021.3100541.

Dr. Varun Tiwari

Assistant professor (Selection Grade) Department of Artificial Intelligence & Machine Learning

varun.tiwari@jaipur.manipal.edu
9461111165

PHD, RAJASTHAN TECHNICAL UNIVERSITY, KOTA, 2020
M.TECH., RAJASTHAN TECHNICAL UNIVERSITY KOTA, 2015
B.TECH., RAJASTHAN TECHNICAL UNIVERSITY, KOTA ,2013

Machine Learrning
Image Processing

Nucleous Member of MUJ-TEC

KPI Coordinator
Registration Coordinator

IEEE
ACM
IAENG

Tiwari V, Jain SC. An optimal feature selection method for histopathology tissue image classification using adaptive jaya algorithm. Evolutionary Intelligence. 2021 Sep;14:1279-92, DOI: https://doi.org/10.1007/s12065-019-00205-w
Tiwari V, Jain SC. Efficient Bag-of-Features using Improved Whale Optimization Algorithm for Histopathological Image Classification. Recent Patents on Computer Science. 2019 Nov 1;12(4):269-79,DOI: 10.2174/2213275912666181127120030
Tiwari V, Jain SC. Histopathological cells segmentation using exponential grasshopper optimisation algorithm-based fuzzy clustering method. International Journal of Intelligent Information and Database Systems. 2020;13(2-4):118-38, DOI: https://doi.org/10.1504/IJIIDS.2020.109452
Rastogi D, Johri P, Tiwari V. Brain Tumor Detection and Localization: An Inception V3-Based Classification Followed By RESUNET-Based Segmentation Approach. International Journal of Mathematical, Engineering & Management Sciences. 2023 Apr 1;8(2).
Rastogi D, Johri P, Tiwari V. Augmentation based detection model for brain tumor using VGG 19,International Journal of Computing and Digital Systems, vol. 13, no. 1, pp. 1227-1237 Apr 1;8(2),DOI: http://dx.doi.org/10.12785/ijcds/1301100

Dr. Vivek Bhardwaj

Assistant professor (Selection Grade) Department of Artificial Intelligence & Machine Learning

vivek.bhardwaj@jaipur.manipal.edu
7814108877

PHD, CHITKARA UNIVERSITY, 2021
M.E., CHITKARA UNIVERSITY, 2017
B.TECH., HIMACHAL PRADESH UNIVERSITY, 2013

Natural Language Processing
Robotic Process Automation

Certified RPA Trainer
Merit Certificate for One Hundred Eighth position in Senior Secondary Examination
Published Two Books with International Repute

Nucleus Member (Corporate Relation & Placement)

KPI-21, 23, 39
Class Coordinator

V. Bhardwaj and V. Kukreja, "Effect of pitch enhancement in Punjabi children's speech recognition system under disparate acoustic conditions," Applied Acoustics, vol. 177, p. 107918, Jun. 2021, doi: 10.1016/j.apacoust.2021.107918.
V. Bhardwaj et al., "Automatic Speech Recognition (ASR) Systems for Children: A Systematic Literature review," Applied Sciences, vol. 12, no. 9, p. 4419, Apr. 2022, doi: 10.3390/app12094419.
V. Bhardwaj, V. Kukreja, and A. Singh, "Usage of prosody modification and acoustic adaptation for robust Automatic Speech Recognition (ASR) system," Revue D'intelligence Artificielle, vol. 35, no. 3, pp. 235-242, Jun. 2021, doi: 10.18280/ria.350307.
V. Bhardwaj, V. Kukreja, C. Sharma, I. Kansal and R. Popali, "Reverse Engineering-A Method for Analyzing Malicious Code Behavior," 2021 International Conference on Advances in Computing, Communication, and Control (ICAC3), Mumbai, India, 2021, pp. 1-5, doi: 10.1109/ICAC353642.2021.9697150.
V. Bhardwaj, "A Systematic Review of Robotic Process Automation in Business Operations: Contemporary Trends and Insights," Journal of Intelligent Systems and Control, vol. 2, no. 3, pp. 153-169, Sep. 2023, doi: 10.56578/jisc020304.

Dr. Yadvendra Pratap Singh

Assistant Professor (Senior Scale) Department of Artificial Intelligence & Machine Learning

yadvendra.singh@jaipur.manipal.edu
9654306320

PHD, MNNIT ALLAHABAD, 2019
M.TECH., MNNIT, ALLAHABAD, 2013
B.TECH., UTTAR PRADESH TECHNICAL UNIVERSITY, 2008

Machine Learning
Deep Learning
Image processing
Remote sensing and Web GIS

Reseach Project
GATE 2011,2012
Reseach Felloship

E-Cell Nucleus Member

Semester Coordinator
KPI 4 and 10

IEEE
ACM

Singh, Y.P., et.al. (2022) "A Deep Neural Network for Classification of Land Use Satellite Datasets in Mining Environments" Journal of Mining and Environment. DOI: 10.22044/jme.2022.12262.2224
Singh, Y. P., Singh, A. K., & Singh, R. P. (2016). Web-GIS based Framework for Solid Waste Complaint Management for Sustainable and Smart City. International Journal of Advanced Remote Sensing and GIS, Vol 5, No 10 (2016), pp. 1930-1936
Singh, Y.P., Singh, R.P., Singh, A.K., Yadav, D.K. (2015), "Using GIS and Remote Sensing Technique for Zoning of Wastewater Drainage of Allahabad City", International Journal of Advanced Remote Sensing and GIS, Vol 4, No 1 (2015), pp. 1419-1434
Y. Rajanak, R. Patil and Y. P. Singh, "Language Detection Using Natural Language Processing," 2023 9th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 2023, pp. 673-678, doi: 10.1109/ICACCS57279.2023.10112773.
Y. P. Singh, et.al."Machine Learning for Sentiment Analysis and Classification of Restaurant Reviews," 2022 3rd International Conference on Computing, Analytics and Networks (ICAN), Rajpura, Punjab, India, 2022, pp. 1-5, doi: 10.1109/ICAN56228.2022.10007390.