Computer Science and Engg.- Faculty

• PhD in Parallel Computing from VNIT Nagpur (2017)
• M.E. in CSE from MGMCoE Nanded (2011)
• B. E. in Computer Technology form KITS Ramtek Nagpur (2003)

• 2018 to till date – Assistant Professor IIIT Nagpur
• 2016 – 2018 – Assistant Professor SVPCET Nagpur
• 2007 – 2011 – Assistant Professor KITS Ramtek Nagpur
• 2005 – 2006 – Lecturer KITS Ramtek Nagpur

• 5th Sem CSE - Database Management Systems (2018-19, 2019-20)
• 4th Sem CSE - Design and Analysis of Algorithms (2018-19, 2019-20)
• 1st Sem CSE/ECE - Computer Programming (Summer Term: 2019, 2020)

• Area of Research

• Parallel Computing
• Deep Learning, Machine Learning, Data Mining
• IoT, Cryptography and Information Security

• Research Project

• Breast Cancer Detection: The cancer in human body is increasing day-by-day and various kinds of cancers are identified that are need to be detected and proper treatment to be provided to cure. To help the medical doctor by detecting the cancer is the major objective of this research work. To do so, we adapted the various Deep Learning models such as CNN, RNN, LSTM to predict the presence of cancer in breast rather than applying traditional Machine Learning approach to bypass the hand engineered feature extraction process. Moreover, the breast cancer is also increasing in women’s and causing the deaths. So, the early or timely detection of breast cancer will help the doctor to diagnose the patient easily and efficiently.
• Fake News Detection: The objective of this research is to identify the Fake News contents over the internet to know the genuineness of the news. Now a days, so many fake news are posted in various social platforms to divert the peoples and society in large. So, we try to identify the fake news by using Deep learning models such as CNN, RNN and LSTM in combination. Moreover, we try to achieve more accurate result as compared to state-of-art methods.
• Skin Cancer Detection: Skin Cancer is caused due to uncontrolled growth of skin cells. The skin cancer is majorly classified as Melanoma and Non-Melanoma. Melanomaare usually brown or black as most melanoma cells make melanin and they are most dangerous among all types of skin cancer. Whereas, Non-Melanoma are most common skin cancers which mainly constitutes of Basal Cell Carcinoma, Squamous Cell Carcinoma, Benign Keratosis, Melanocytic Nevi, Vascular Lesions, Dermatofibroma. About 8 out of 10 skin cancers are Basal CellCarcinomas. A study estimates more than 3 million non-melanoma and 132,000 melanoma skin cancer cases occur each year. It's estimated that the number of new melanoma cases diagnosed in 2019 will increase by 7.7 percent. The vast majority of melanomas are caused by the sun. In fact, one UK study found that about 86 percent of melanomas can be attributed to exposure to ultraviolet (UV) radiation from the sun and about 90 percent of nonmelanoma skin cancers are associated with exposure to ultraviolet (UV) radiation from the sun. The motivation for the worklies in the fact "Skin Cancers are highly curable if they detected at early stages". Basal cell and squamous cell carcinomas, the two most common forms of skin cancer, are highly curable if detected early and treated properly. The five-year survival rate for people whose melanoma is detected and treated before it spreads to the lymph nodes is 99 percent. The objective of this project will be to develop a Deep Leaning based model to accurately classify the skin lesion image among seven skin cancer types: Melanoma, Basal Cell Carcinoma, Squamous Cell Carcinoma, Benign Keratosis, Melanocytic Nevi, Vascular Lesions, Dermatofibroma. The work will employ the support of Transfer Learning, Data Augmentation, Automated Feature Extraction techniques to maximise the skin cancer classification accuracy.
• Textual Sentiment Analysis: We introduce a new approach to textual sentiment analysis. Till date the combination of Long Short Term Memory (LSTM) and Bidirectional Long Short Term Memory (Bi-LSTM) was not used to train the deep learning model for sentiment analysis. I chose to proceed with the same. This work mainly focuses on the use of LSTM and Bi-LSTM jointly to increase the accuracy of prediction. In this model, losses are minimised and accuracy is increased. Though the state-of-art accuracy is not reached, this model gives much more accuracy as compared to pure SVM model. This work also incorporates comparison between the performance metrics in new model with performance metrics of SVM model at the end. This model is trained on the IMDB movie review dataset which contain positive and negative reviews.

• Reviewed Papers for Journals / Conferences

• Security and Privacy
• CIT. Journal of Computing and Information Technology
• Transactions on Computational Science – Springer
• International Virtual Conference on “Artificial Intelligence for Internet of Things” (AIIOT 2019), SENSE, VIT, Vellor, 6th December, 2019
• International Conference on Ubiquitous Computing (ICUC-2017), 25^th & 26^th July, 2017
• International Conference on Micro-Electronics & Telecommunication Engineering (ICMETE-2016), SRM University, NCR Campus, Modinagar, India.

• C. S. Meshram and J. V. Tembhurne et. al "A Subtree-based Transformation Model for Cryptosystem using Chaotic Maps under Cloud Computing Environment for Fuzzy User Data Sharing" International Journal of Communication Systems 33 (7) e4307 2020. Indexed in SCI.
• Tausif Diwan J. V. Tembhurne "A Parallelization of Non-Serial Polyadic Dynamic Programming on GPU" CIT. Journal of Computing and Information Technology Vol. 18 No. 1 April 2019 pp. 75-81. Indexed in SCOPUS.
• Kailash W Kalare J. V. Tembhurne "A Work Distribution Strategy for Global Sequence Alignment" International Journal of Computing Vol. 18 No. 1 April 2019 pp. 75-81. Indexed in SCOPUS.
• J. V. Tembhurne S. R. Sathe "Multi-Precision Integer Multiplication for Cryptosystems" Advanced Science Letters Vol. 24 No. 7 July 2018 pp. 5187-5193(7). Indexed in SCOPUS
• J. V. Tembhurne "Parallel Multiplication of Big Integer on GPU" Communication in Computer and Information Science Springer Vol. 827 June 2018 pp. 276-285. Indexed in SCOPUS DBLP.
• Pathak Abhishek D. and Tembhurne Jitendra V. "Internet of Things: A Survey on IoT Protocols" In Proc. of 3rd International Conference on Internet of Things and Connected Technologies (ICIoTCT) 2018 held at Malaviya National Institute of Technology Jaipur (India) on March 26-27 2018. Available at SSRN: https://ssrn.com/abstract=3168575 or http://dx.doi.org/10.2139/ssrn.3168575. Indexed in SCOPUS
• J. V. Tembhurne S. R. Sathe "New Modified Euclidean and Binary Greatest Common Divisor Algorithm" IETE Journal of Research Vol. 62 2016 pp. 852-858. Indexed in SCIE.
• J. V. Tembhurne and S. R. Sathe "RSA public-key Acceleration on CUDA GPU" Advances in Intelligent S

• PhD.
  •  Mr. Vishesh Gaikwad under Visvesvaraya Scheme (On going)
• M. Tech.
• B.E. / B. Tech.
  • More than 10 groups

• Head of the Department CSE IIIT Nagpur
• Network Centre & IT Infrastructure In-charge at IIIT Nagpur
• Website design and management In-charge at IIIT Nagpur
• Chairman SC/ST Cell at IIIT Nagpur
• Stock and Purchase Committee member at IIIT Nagpur
• Tender Processing Committee member at IIIT Nagpur
• Admission Committee member at IIIT Nagpur

• Invited talk on "Introduction to Artificial Neural Networks" in One Week Online Workshop on "Artificial Intelligence" Sponsored by AICTE - ATAL Workshop Scheme from 16th May to 20th May, 2020 at IIIT Nagpur
• Invited talk on "Introduction to RNN and LSTM" in One Week Online Workshop on "Artificial Intelligence" Sponsored by AICTE - ATAL Workshop Scheme from 24th April to 28th April, 2020 at IIIT Nagpur
• Invited talk on "Applications of RNN and LSTM in Data Science" in One Week Online Workshop on "Data Science" Sponsored by AICTE - ATAL Workshop Scheme from 18th April to 22nd April, 2020 at IIIT Nagpur
• Invited talk on "Sequence Modeling using RNN and LSTM" in 2nd One Week Online Workshop on "Artificial Intelligence" Sponsored by AICTE - ATAL Workshop Scheme from 13th April to 17th April, 2020 at IIIT Nagpur
• Visiting Faculty for 6th Sem IT course (M. Tech.) from Jan-2020 to May-2020 at ABV-IIITM Gwalior, India
• Invited talk on "Application of RNN, LSTM for Sequence Modeling" in DST-ICPS Division Sponsored, Three Day National Level Seminar on Deep Learning for Engineering Applications from 6th to 8th January, 2020 at KITS, Warangal, TS, India
• Invited talk on "RNN, LSTM for Sequence Modeling" in One Week Workshop on "Artificial Intelligence and Machine Learning" from 9th to 13th December, 2019 - Sponsored by AICTE - ATAL Workshop Scheme at IIIT Nagpur
• Session Chair in SPANDAN - 2019 at YCCE, Nagpur
• CSE BoS member, Raisoni University

• PhD in Knowledge Management Systems from JUIT Solan (2013)
• M. Tech. in CSE from IIIT Allahabad (2005)
• B. E. in Computer Technology form RGPV Bhopal(2003)

• 2018 to till date – Assistant Professor IIIT Nagpur
• 2015 - 2018 - Assistant Professor IIIT Kota
• 2009 - 2015 - Assistant Professor JUIT Solan
• 2007 - 2009 - Software Engineer CSC India Pvt Ltd.
• 2005 - 2007 - Software Engineer IBM India Pvt Ltd.

• 4th Sem CSE - Software Engineering
• 3rd Sem CSE/ECE - Object Oriented Programming
• 1st Sem CSE/ECE - Computer Programming

• Area of Research

• Machine Learning
• Multi Agent Systems
• Knowledge Management Systems

• Research Project

• Weed removal using CNN

• Reviewer for Journal / Conference

• Joey Pinto Pooja Jain Tapan Kumar Jain Fault Prediction for Distributed Computing Hadoop Clusters Using Real-Time Higher Order Differential Inputs to SVM : Zedacross International Journal of Information and Computer Security (IJICS) October 2017
• Yash Sharma Gaurav Agrawal Pooja Jain Tapan Kumar Vector Representation of Words for Sentiment Analysis Using Glove International Conference on Intelligent Communication and Computational Techniques December 2017.
• Pinto Joey Pooja Jain and Tapan Kumar. "Hadoop cluster monitoring and fault analysis in real time." In International Conference on Recent Advances and Innovations in Engineering (ICRAIE) 2016 pp. 1-6. IEEE 2016
• Pinto Joey Pooja Jain and Tapan Kumar. "Hadoop distributed computing clusters for fault prediction." In Computer Science and Engineering Conference (ICSEC) 2016 International pp. 1-6. IEEE 2016.
•  

• PhD.

• Head of the Department CSE at IIIT Nagpur (July - 2018 to June - 2020)
• Faculty In-charge T&P IIIT Nagpur

• PhD in CSE (Wireless Sensor Networks) from VNIT, Nagpur (2018)
• M. Tech. in CSE from VNIT, Nagpur (2009)
• B. E. in CSE from Govt. College of Engineering, Amravati (2002)

• July 2019 - till date - Assistant Professor, IIIT, Nagpur
• 2009 - June 2019 - Assistant Professor, RCOEM, Nagpur
• 2005 - 2007 - Lecturer, PCE, Nagpur
• 2003 - 2005 - Teaching Assistant, VNIT Nagpur

5th Sem CSE - Computer Networks

• Area of Research

• Wireless Sensor Networks

• Nishat A. Ansari, Umesh A. Deshpande, and S. P. Mohammad. "An asynchronous algorithm for providing energy efficient coverage and connectivity in wireless sensor networks." In 2016 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), pp. 1-6. IEEE, 2016, IISc Bangalore, indexed in dblp database.
• Nishat A. Ansari, Umesh A. Deshpande, Amit M. Tapas, and Anushka A. Jejani. "A distributed algorithm for object tracking in wireless sensor networks using data mining based prediction." In 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT), pp. 1-6. IEEE, 2017, IIT Delhi, Scopus indexed.

• B.E. / B. Tech.
• Various B. Tech. level projects

Faculty Advisor 3rd year section A, CSE

• Life member of ISTE
• Top rank holder in M. Tech

• PhD in Energy Efficient Real Time Scheduling Algorithms from BITS, Pilani (2017)
• M. E. in Computer Science from BITS, Pilani (2009)
• B. E. in Computer Technology form RCERT, Chandrapur, Nagpur University (2001)

• 2019 to till date - Assistant Professor, IIIT, Nagpur
• 2017 - 2019, Assistant Professor (Visiting), Department of CSIS, BITS, Pilani
• 2010 - 2016, Lecturer, Department of CSIS, BITS, Pilani
• 2005 - 2009, Teaching Assistant, Department of CSIS, BITS, Pilani
• 2002, Lecturer, Computer Science Department, Bajaj Polytechnic College, Chandrapur

• Mobile App Development using Android Programming
• Python Programming
• Advanced Computer Architecture
• 1st Semester CSE - Computer Programming (2019-2020)
• 5th Semester CSE - Real Time Systems (2019-2020)

• Area of Research

• Operating Systems
  • Real Time Scheduling
  • Energy Efficient and Temperature Aware Scheduling
  • Multiprocessor/Multi-core Scheduling
  • Mixed Criticality Systems
• Homogeneous/Heterogeneous Computer Architecture
• Energy Optimization issues in Internet of Things

• Research Project

• Reviewer for Journal / Conference

• Journal of Computer Standards and Interface, Elsevier Publication

• Digalwar, M., Raveendran, B. K. & Mohan, S. (2017). LAMCS: A Leakage Aware DVFS based Mixed Task Set Scheduler for Multi-Core Processors. Journal of Sustainable Computing, Volume 15, September 2017, page no. 63-81. (Elsevier Publication, SCI Expanded).
• Digalwar, M., Gahukar, P., Raveendran, B. K. & Mohan, S. (2017). Energy efficient real-time scheduling algorithm for mixed task set on multi-core processors. International Journal of Embedded Systems, Vol. 9, No 6. (Inderscience Publications, SCOPUS Indexed)
• Vinita Tahiliani, Digalwar, M., (2018). Green IoT Systems: An Energy Efficient Perspective. Proc. of 11th IEEE Int. Conf. on Contemporary Computing (IC3 2018), (SCOPUS Indexed).
• Digalwar, M., Gahukar, P., & Mohan, S. (2018). Energy Efficient Real Time Scheduling on Multi-core Processor with Voltage Islands. 7th IEEE Int. Conf. on Advances in Computing, Communications and Informatics (ICACCI-2018). (SCOPUS Indexed).
• Deshpande, P, .Digalwar, A. & Digalwar, M. (2018). Application of Industrial IoT in Manufacturing Industry for Predictive Maintenance: A Survey. In Proc. of 12th ISDSI 2018 Int. Conf., Mumbai, India. Dec 2018.
• Digalwar, M., Gahukar, P., Mohan, S. & Raveendran, B. K. (2015). STREAM: A Simulation Tool for Energy Efficient Real Time Scheduling and Analysis. Proc. of Int. Workshop on Analysis Tools and Methodologies for Embedded and Real-time Systems (WATERS) in conjunction with 27th Euromicro Conf. on Real Time Systems (ECRTS), Lund, Sweden. July 2015 (Indexed in Web of Science).
• Digalwar, M., Gahukar, P., & Mohan, S. (2014). Design and development of a real time scheduling algorithm for mixed task set on multi-core processors. Proc. of 7th IEEE Int. Conf. on Contemporary Computing (IC3 2014), pp. 265-269. (SCOPUS Indexed).
• Digalwar, M., Mohan, S., & Raveendran, B. (2013). Dynamic voltage and frequency scaling scheduling algorithm for mixed t

• PhD.
•  
• M. Tech.
• Design and Development of an IoT based Mobile app for Cab Scheduling and Booking Systems (Year 2018-19)
• Study and analysis of energy optimization issue in the embedded devices in IoT based Systems.
• Design and development of a Simulation Tool called "STREAM" for implementing energy efficient real time scheduling algorithms. (Year 2014-15)
• B.E. / B. Tech.
• Study and Implementation (in Verilog) of ARM Processor
• Study of Energy Aware Real Time Scheduling Algorithms for Multiprocessor Systems
• Study and analysis of memory organization of series of Intel Architecture
• Study of ISA and micro architecture of Pentium II processor

Faculty Advisor 1st year section A, CSE

• PhD in CSE from VNIT, Nagpur (2018)
• M. Tech. in Computer Engineering from College of Engineering, Pune (2007)
• B. E. in CSE form SGGS Institute of Engineering and Technology, Nanded (2001)
•  

• July 2019 - till date - Assistant Professor, IIIT Nagpur
• 2017 - 2019 - Associate Professor, MIT School of Engineering, MIT ADT University, Pune
• 2012 - 2017 - Associate Professor, MIT College of Engineering, Pune
• 2007 - 2012 - Assistant Professor, MIT College of Engineering, Pune
• 2003 - 2007 - Lecturer, MIT College of Engineering, Pune
• 2003 - Lecturer, AISSMS's College of Engineering, Shri Savitribai Phule Pune University, Pune
• 2001 - 2003 -Lecturer, MGM's College of Engineering, Nanded
•  

• 3rd Semester CSE - Microprocessor and Interfacing (2019-2020)

• Area of Research

• Delay Tolerant Networks/ Vehicular Delay Tolerant Networks
• Mobile Social Networks
• Internet of Things

• Research Project

• Reviewer for Journal / Conference

• IEEE Transactions on Vehicular Technology Journal
• International Journal of Communication Systems, Wiley
• IEEE 4th International Conference On Computing, Communication, Control and Automation 16th to 18th Aug, 2018

• Milind R. Penurkar and Umesh A. Deshpande, "Priority-based scheduling policy for a Hybrid Routing algorithm in a Vehicular Delay Tolerant Network", Proc. of Int. Conf. on Computing, Analytics and Security Trends (CAST), Pune, India, pp. 578-583, 2016.
• Milind R. Penurkar and Umesh A. Deshpande, "OPPRES: OPPortunistic Routing algorithm for routing messages in Emergency Situations using Vehicular Delay Tolerant Network", Proc. of IEEE Int. Conf. on Advanced Networks and Telecommunications Systems (ANTS), IISC, Bangalore, India, pp. 1-6, 2016.
• Milind R. Penurkar and Umesh A. Deshpande,"Max-Util: A Utility-Based Routing Algorithm for a Vehicular Delay Tolerant Network Using Historical Information", Proc. of 3rd Int. Conf. on Advanced Computing, Networking and Informatics in Smart Innovation, Systems and Technologies, Springer, India, Vol. 44, pp. 587-598, 2015.
• Milind R. Penurkar and Umesh A. Deshpande, "Conhis: Contact history-based routing algorithm for a vehicular delay tolerant network", Proc. of Annual IEEE India Conference (INDICON), Pune, India, pp. 1-6, 2014.
•  

• PhD.
•  
• M. Tech.
• Various Projects supervised
• B.E. / B. Tech.
• Various Projects supervised

Faculty Advisor 2nd year section A, CSE

• PhD in Parallel Computing from VNIT, Nagpur (2017)
• M. Tech. in CSE from VNIT, Nagpur (2011)
• B. E. in Computer Science form ACET, Nagpur (2008)

• July 2019 to till date - Assistant Professor, IIIT Nagpur
• August 2011 to July 2019 - Assistant Professor, RCOEM, Nagpur

• 3rd Semester CSE - Data Structures with Applications (2019-2020)
• 6th Semester CSE – Neural Network and Deep Learning (2019-2020)
• 2nd Semester CSE - Data Structures (2019-2020)

• Area of Research

• Parallel Computing
• Deep Learning

• Research Project

• Title: A Deep learning approach for wind profiling over ocean surface, Guided by: Dr. Amit Kesarkar, Group Head, Weather and Climate Research Group, National Atmospheric Research Laboratory, India. Duration: May-June 2018

• Reviewer for Journal / Conference

• Tausif Diwan, J. V. Tembhurne, "A Parallelization of Non-Serial Polyadic Dynamic Programming on GPU", CIT. Journal of Computing and Information Technology. Indexed in SCOPUS. In Press.
• Tausif Diwan and S. R. Sathe, "A Generalized Strategy for Parallelization of Non-Serial Polyadic Dynamic Programming on Multicore and Manycore," Advanced Science Letters, vol. 23, no. 04, pp. 3802-3807, April 2017. Indexed in SCOPUS.
• Tausif Diwan and S. R. Sathe, "Efficient scheduling of dynamic programming algorithms on multicore architectures," Journal of Engineering Science and Technology, vol. 12, no. 05, pp. 1253-1264, 2017. Indexed in SCOPUS, ESCI.
• Tausif Diwan and S. R. Sathe, "Dynamic Programming Parallelization of Matrix Chain Multiplication on GPU: A Comparative Study," in Advances in Intelligent Systems and Computing, vol. 394, pp. 333-343, Feb. 2016, Springer. Indexed in Web of Science (ISI Procedings), SCOPUS.

• PhD.

• M. Tech.

• 2 projects

• B.E. / B. Tech.

• 8 groups

• Faculty Advisor 2nd year section B, CSE
• Internship In charge at Departmental Level
• Students Activity Committee Member

Visiting Faculty at ABV-IIITM, Gwalior for Parallel and Distributed Computing course of IPG-VI Semester M. Tech.

• PhD in CSE from NIT Allahabad (2018)
• M. Tech. in IT from IIIT Allahabad (2015)
• B. Tech. in IT form GBTU (2012)

• July 2019 to till date - Assistant Professor, IIIT, Nagpur
• June 2018 - June 2019 - Visiting Assistant Professor, Thapar University, Punjab

• 1st Semester CSE/ ECE - IT Workshop - I (2019-2020)
• 6th Sem CSE – Cryptography and Network Security
• 6th Sem CSE – Mobile Computing
• 3rd Sem CSE – IT Workshop

• Area of Research

• Machine Learning
• Internet of Things
• Wireless Sensor Network
• Information-centric Network
• Data Mining
• Data Science

• Research Project

• Modified Trial Division Algorithm Using KNJ-Factorization Method To Factorize RSA Public Key Encryption

• Reviewer for Journal / Conference

• Journal of Supercomputing, springer
• IEEE Journal of Communications and Networks
• Transactions on Emerging Telecommunications Technologies, Wiley
• IEEE System Journal

• Lal, Nidhi, Shishupal Kumar, and Vijay Kumar Chaurasiya. “A Road Monitoring Approach with Real-time Capturing of Events for Efficient Vehicles Safety in Smart City” Wireless Personal Communication, Springer, 2020.
• Nidhi Lal & Shishupal Kumar (2019) An Efficient Uplink Scheduler for WiMAX Communication System with Prevention from Security Attacks, New Review of Information Networking, 24:2, 133-152, DOI: 10.1080/13614576.2019.1608580.
• Varun Shirbhayye, Deepesh Kurmi, Siddharth Dyavanapalli, Agraharam Sai Hari Prasad, and Nidhi Lal. "An Accurate Prediction of MPG (Miles Per Gallon) using Linear Regression Model of Machine Learning." In 2020 International Conference on Computer Communication and Informatics (ICCCI), pp. 1-5. IEEE, 2020.
• Saw, Montu, Tarun Saxena, Sanjana Kaithwas, Rahul Yadav, and Nidhi Lal. "Estimation of Prediction for Getting Heart Disease Using Logistic Regression Model of Machine Learning." In 2020 International Conference on Computer Communication and Informatics (ICCCI), pp. 1-6. IEEE, 2020.
• Kumar, Akash, Aniket Verma, Gandhali Shinde, Yash Sukhdeve, and Nidhi Lal. "Crime Prediction Using K-Nearest Neighboring Algorithm." In 2020 International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE), pp. 1-4. IEEE, 2020.
• Keerthana, P. S. M., Nimish Phalinkar, Riya Mehere, Koppula Bhanu Prakash Reddy, and Nidhi Lal. "A Prediction Model of Detecting Liver Diseases in Patients using Logistic Regression of Machine Learning." Available at SSRN 3562951 (2020).
• S Arvind, Anshika Jain, Nidhi Lal and Mayuri Digalwar, "Insurance Claim Prediction Approach Using Machine Learning based Logistic Regression ", IEEE International Conference on Measurement, Instrumentation, Control and Automation (#48462) (ICMICA 2020) April 2, 2020 to April 4,2020 , N

• PhD.

• M. Tech.

• B.E. / B. Tech.

• Counselling Coordinator of CSE IIIT, Nagpur
• Member of International Collaboration and Revenue generation at IIIT, Nagpur
• Admission Committee member at IIIT Nagpur

• Invited/Delivered Lecture on “Protocols in IoT” organized by Department of Electronics and Telecommunication Engineering, Government college of Engineering, chandrapur DTE sponsored Faculty Development Program (FDP), 20 Dec 2019.
• Invited/Delivered Lecture on “Supervised Machine Learning Algorithms-Naïve Bayes and SVM” organized by CSE, IIIT Nagpur, ATAL sponsored Faculty Development Program (FDP), 17 May 2020.

• PhD in CSE from VNIT, Nagpur (2019), Specialization: Bioinformatics
• M. E. in CSE from GHRCE (2009)
• B. E. in Computer Engineering form SRPCE, Nagpur (2004)

• July 2019 to till date - Adjunct Assistant Professor on Practice, IIIT Nagpur
• July 2018 - May 2019 - Adjunct Assistant Professor on Practice, IIIT Nagpur
• 2009 - 2014 - Assistant Professor, SSGBCOET, Bhusawal
• 2006 - 2008 - Lecturer, PCE, Nagpur
• 2005 - 2006 - Trainee Software Engineer, Prism Software Ltd, Nagpur

• 6th/8th Sem CSE - Bioinformatics (2019-2020)
• 4th Sem CSE – Operating System (2019-2020, 2018-2019)
• 3rd Sem CSE - Computer System Organization (2018-2019)
• 3rd Sem CSE/ECE- IT Worksop (2019-2020, 2018-2019)

• Area of Research

• Bioinformatics
• Data Analysis

• Research Project

• Ongoing: Covid-19 research project on genomic analysis of Coronavirus and its correlation to immune system, approved by IIT Delhi Supercomputing facility.
• Complete:Computational characterization of genes in multiple cancers - This research focusses on detection of common genes in multiple cancer types using large scale data analysis

• Reviewer for Journal / Conference

• IEEE Transactions on Computational Biology and Bioinformatics - IEEE
• Methods - Elsevier

• Makhijani, R.K., Raut, S.A. and Purohit, H.J., 2018. Identification of common key genes in breast, lung and prostate cancer and exploration of their heterogeneous expression. Oncology Letters, 15(2), pp.1680-1690. (SCIE Indexed; Impact factor:1.5; https://doi.org/10.3892/ol.2017.7508))
• Makhijani, R.K., Raut, S.A. and Purohit, H.J., 2018. Fold change based approach for identification of significant network markers in breast, lung and prostate cancer. IET Systems Biology. (SCIE Indexed; Impact factor:1.01; DOI: 10.1049/ietsyb.2018.0012)
• •Conference: Richa Makhijani, Shital A Raut. Characterization of top hub genes in breast and lung cancer using functional association, in Proc. of Int. Conf. of Soft Computing for Problem Solving (SocProc 2018), at VIT Vellore, to be published in SCOPUS indexed AISC series of Springer. (Best Paper)

Teaching

• 6th/8th Sem CSE - Bioinformatics (2019-2020)
• 4th Sem CSE – Operating System (2019-2020, 2018-2019)
• 3rd Sem CSE - Computer System Organization (2018-2019)
• 3rd Sem CSE/ECE- IT Worksop (2019-2020, 2018-2019)

Research

• Area of Research

• Bioinformatics
• Data Analysis

• Research Project

• Ongoing: Covid-19 research project on genomic analysis of Coronavirus and its correlation to immune system, approved by IIT Delhi Supercomputing facility.
• Complete:Computational characterization of genes in multiple cancers - This research focusses on detection of common genes in multiple cancer types using large scale data analysis

• Reviewer for Journal / Conference

• Faculty Advisor 3rd year section B, CSE
• Organizing Committee member in five days’ workshop on High Performance Computing (HPC) held on 14th May 2018 to 18th May 2018.
• Organizing Committee member in STTP on Biological Databases and Machine Learning in R VNIT, Nagpur, 5-10 Dec 2016.
• Organizing Committee member at 81st Annual Conference on THE INDIAN MATHEMATICAL SOCIETY, 27-30 DEC 2015.
• PG coordinator, CSE, SSGB COET, Bhusawal (2014-12).
• NBA coordinator, CSE, SSGB COET, Bhusawal(2012-13).
• Organized Workshop on Latex, at SSGB COET, Bhusawal,19-21 Oct 2012.

• Best paper award at International Conference SocPros 2018, held at Vellore Institute of Technology, Vellore, India.
• Conduction of Session on “Machine learning with R” in STTP on “Open Source Technologies” conducted on 26th Oct 18, at Rajiv Gandhi College of Engineering and Research, Nagpur.

• PhD Pursuing from IIIT, Nagpur
• M. Tech. in CSE from GHRCE, Nagpur (2011)
• B. E. in Information Technology form Shri Ramdeobaba College of Engineering, Nagpur (2008)

• July 2019 to till date - Adjunct Assistant Professor on Practice, IIIT Nagpur
• July 2018 - May 2019 - Adjunct Assistant Professor on Practice, IIIT Nagpur
• 2015 - 2018 - Assistant Professor, RCOEM, Nagpur
• 2014 - 2015 - Assistant Professor, PBCOE, Nagpur
• 2012 - 2013 - Assistant Professor, PCE, Nagpur
• 2010 - 2011 - Assistant Professor, RCOEM, Nagpur
• 2008 - 2009 - Assistant Professor, KDK, Nagpur

• 1st Sem CSE - Computer Programming (2018-2019)
• 3rd Sem CSE - Data Structures (2018-2019)
• 6th Sem CSE - Business Intelligence (2018-2019)
• 5th Sem CSE - Theory of Computation (2019-2020)

• Area of Research

• Machine Learning
• Smart Grids
• Natural Language Processing

• Research Project

• Reviewer for Journal / Conference

• Khushboo. A. Jain, P. Mishra, L. Arora, M.S. Kotian, "Hardware Interaction using Hand Gestures", Journal on Computer Science and Engineering(IJCSE), Vol-6, Issue-5, May-2018.
• Khushboo Thakkar, Urmila Shrawankar, "Text Categorization and Text Summarization for Topic Tracking", International Journal on Science and Technology (IJSAT), Volume II, Issue II, page 68-74, Apr-June 2011
• Khushboo Thakkar, Urmila Shrawankar, "Test Model for Text Categorization and Text Summarization", International Journal on Computer Science and Engineering (IJCSE), Vol.3 No. 4 Apr 2011
• Khushboo Thakkar, Dr. R. V. Dharaskar, M. B. Chandak, "Graph-Based Algorithms for Text Summarization", Third International Conference on Emerging Trends in Engineering and Technology(ICETET 2010)

Supervision

• PhD.

• M. Tech.

• B.E. / B. Tech.

Time-Table In-charge of CSE at IIIT, Nagpur

• PhD in IT from IIIT Allahabad (2020)
• M.Tech. in IT from IIIT Allahabad (2015)
• B. Tech in IT form RGTU (2009)

• January 2020 to till date – Adjunct Assistant Professor, IIIT Nagpur

• 4th Sem ECE – Android Programming (IT Workshop)
• 4th Sem CSE – Discrete Mathematics and Graph Theory
• 4th Sem CSE- Software Engineering
• 4^th Sem CSE- Operating System
• 5th Sem CSE – Theory of Automata
• 3rd Sem CSE- Data Structure
• 7th Sem CSE- Cloud computing

Area of Research

• Big data and analytics
• Internet of Things
• Wireless Sensor Network
• Data Mining
• Machine Learning
• Data Science

Reviewer for Journal / Conference

• Reviewer of Journal of Supercomputing, springer
• Reviewer of IEEE Journal of Communications and Networks
• Reviewer of Transactions on Emerging Telecommunications Technologies Wiley
• Reviewer of IEEE System Journal

• Lal, Nidhi, Shishupal Kumar, and Vijay Kumar Chaurasiya. “A Road Monitoring Approach with Real-time Capturing of Events for Efficient Vehicles Safety in Smart City” Wireless Personal Communication, Springer, 2020.
• Nidhi Lal & Shishupal Kumar (2019) An Efficient Uplink Scheduler for WiMAX Communication System with Prevention from Security Attacks, New Review of Information Networking, 24:2, 133-152, DOI: 10.1080/13614576.2019.1608580.           
• Lal, Nidhi, Shishupal Kumar, and Vijay Kumar Chaurasiya. “An Energy-efficient IPv6 Packet Delivery Scheme for Industrial IoT over G.9959 Protocol based Wireless Sensor Network (WSN)” Computer network Elsevier, 2019. DOI: 10.1016/j.comnet.2019.03.001.

• Lal, Nidhi, Shishupal Kumar, and Vijay Kumar Chaurasiya. "A Network-Coded Caching-Based Multicasting Scheme for Information-Centric Networking (ICN)." Iranian Journal of Science and Technology, Transactions of Electrical Engineering (2019): 1-12. DOI: https://doi.org/10.1007/s40998-018-0171-4.
• Lal, Nidhi, Shishupal Kumar, and Vijay Kumar Chaurasiya. "An efficient update strategy for content synchronization in Content-Centric Networking (CCN)." China Communications 16, no. 1 (2019): 108-118.
• Kumar, Shishupal, and Vijay Kumar Chaurasiya. "A strategy for elimination of data redundancy in the internet of things (IoT) based wireless sensor network (wsn)." IEEE Systems Journal 13, no. 2 (2018): 1650-1657.
• Kumar, Shishupal, Nidhi Lal, and Vijay Kumar Chaurasiya. "A forwarding strategy based on ANFIS in internet-of-things-oriented wireless sensor network (WSN) using a novel fuzzy-based cluster head protocol." Annals of Telecommunications 73, no. 9-10 (2018): 627-638. DOI: https://doi.org/10.1007/s12243-018-0656-1.
• Kumar, Shishupal, and Vijay Kumar Chaurasiya. "A multisensor data fusion strategy for path selection in Internet?of?Things oriented wireless sensor network (WSN)." Concurrency and Computation: Practice and Experience 30, no. 18 (2018): e4477.
• Lal, Nidhi, Shishupal Kumar, and Vijay Kumar Chaurasiya. "An adaptive neuro-fuzzy inference system-based caching scheme for content-centric networking." Soft Computing (2018): 1-12. DOI: https://doi.org/10.1007/s00500-018-3105-1.
• Lal, Nidhi, Shishupal Kumar, Garima Kadian, and Vijay Kumar Chaurasiya. "Caching methodologies in Content-centric networking (CCN): A survey." Computer Science Review 31 (2019): 39-50. DOI: https://doi.org/10.1016/j.cosrev.2018.11.001
• Kumar, Shishupal, Nidhi Lal, and Vijay Kumar Chaurasiya. "Performance Analysis of Software Defined Network with Three Controllers." In Proceedings of the Future Technologies Conference, pp. 718-732. Springer, Cham, 2018. DOI: 10.1007/978-3-030-02683-7_51

• Lal, Kumari Nidhi, and Anoj Kumar. "A cache content replacement scheme for the information-centric network." Procedia Computer Science 89 (2016): 73-81. DOI: https://doi.org/10.1016/j.procs.2016.06.011.
• Lal, Nidhi, Shishupal Kumar, Aditya Saxena, and Vijay Km Chaurasiya. "Detection of malicious node behavior via I-watchdog protocol in mobile Ad Hoc network with DSDV routing scheme." Procedia Computer Science 49 (2015): 264-273.     DOI: https://doi.org/10.1016/j.procs.2015.04.252.
• Lal, Nidhi, Shishupal Kumar. "Modified trial division algorithm using KNJ-factorization method to factorize RSA public key encryption." In 2014 International Conference on Contemporary Computing and Informatics (IC3I), pp. 992-995. IEEE, 2014.  DOI: DOI: 10.1109/IC3I.2014.7019588.

• Faculty advisor of 2^nd year