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Admission Brochure 2026–27

Passionate Researcher and Teacher who loves to solve the challenging problem of Artificial Intelligence. Develop Deep Learning and Machine Learning solution for computer vision and Natural Language Processing problems. Developed Deep Learning solutions for multiple industries such as Bharat Electronics Limited, NSDC, Manupatra.

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Education

  • Ph.D., Indian Institute of Technology, Indore, Computer Science & Engineering (2015)
  • Master in Engineering (M.E.), Shri Govindram Seksaria Institute of Technology and Science, Indore, Computer & Engineering (2011)
  • Bachelor in Engineering (B.E.), Nagaji Institute of Technology andManagement Gwalior (RGPV, Bhopal), Computer Science & Engineering (2009)
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Experience

  • Associate Professor, Gati Shakti Vishwavidyalaya, Vadodara (Nov 2024 – Present)
  • Assistant Professor, Gati Shakti Vishwavidyalaya, Vadodara (Jan 2024 – Nov 2024)
  • Assistant Professor, Pandit Deendayal Energy University, Gandhinagar (Dec 2022 – Dec 2023)
  • Assistant Professor, Bennett University, Greater Noida, U.P. (June 2016 – Dec 2022)
  • Assistant Professor, IMS Engineering College, Ghaziabad (Feb 2016 – May 2016)
  • Postdoctoral Scholar, University of Kentucky, USA (Oct 2015 – Jan 2016)
  • Lecturer, Shri Govindram Seksaria Institute of Technology and Science, Indore (Dec 2011 – June 2012)
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Professional Distinctions

  • Reviewer IEEE Transaction on Artificial Intelligence
  • Reviewer of IEEE Transaction of VLSI
  • Reviewer of IEEE Transaction on Aerospace and Electronic Systems
  • Reviewer of IEEE/IET Journal on Computers & Digital Techniques
  • Reviewer of Expert system with application
  • Certified Nvidia Deep Learning Institute (DLI) Instructor
  • Conducted more than 30 workshops on Machine learning and deep learning across India. Few top industry/institute - Rastriya Raksha University, Gandhinagar|CDAC Noida| GAIL India | DAICT Gandhinagar| COEP, Pune| Symbiosis Institute of Technology Pune
  • NVIDIA DLI Certificate: Applications of AI for Predictive Maintenance
  • NVIDIA DLI Certificate: Fundamentals Of Deep Learning For Computer Vision
  • NVIDIA DLI Certificate: Deep Learning for Healthcare Image Analysis
  • NVIDIA DLI Certificate: Building Transformer-Based Natural Language Processing Applications
  • NVIDIA DLI Certificate: Getting Started With Deep stream For Video Analytics On Jetson Nano
  • NVIDIA DLI Certificate: Getting Started With Ai On Jetson Nano
  • Coursera Certification : Bayesian Methods for Machine Learning
  • Udacity Certification : Secure and Private AI
  • Received Financial Grant from DST as young scientist [2014]
  • Received fellowship from ISED [2014]
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Key Publications

  • T. choudhary, V. K. Mishra, and A. Goswami, “Automated deep learning model optimization,” Indian Patent 202 111 013 437, Granted, Apr. 30, 2021.
  • V. K. Mishra, T. badal, and R. das, “Mechanism for obtaining multi-source information,” Indian Patent 202 111 054 025, Published, Nov. 23, 2021.
  • V. K. Mishra, T. Badal, and A. Goswami, “System and method for evaluating student learning using ai based real-time analysis,” Indian Patent 202 111 034 143, Published, Jul. 29, 2021.
  • T. Choudhary, S. Gujar, A. Goswami, V. Mishra, and T. Badal, “Deep learning-based important weightsonly transfer learning approach for covid-19 ct-scan classification,” Applied Intelligence, pp. 1–15, 2022.
  • T. Choudhary, V. Mishra, A. Goswami, and J. Sarangapani, “Heuristic-based automatic pruning of deep neural networks,” Neural Computing and Applications, vol. 34, no. 6, pp. 4889–4903, 2022
  • T. Choudhary, V. Mishra, A. Goswami, and J. Sarangapani, “Inference-aware convolutional neural network pruning,” Future Generation Computer Systems, vol. 135, pp. 44–56, 2022.
  • M. Dixit, K. Chaurasia, V. K. Mishra, D. Singh, and H.-N. Lee, “6+: A novel approach for building extraction from a medium resolution multi-spectral satellite,” Sustainability, vol. 14, no. 3, p. 1615, 2022.
  • S. Mishra, T. Ahmed, V. Mishra, S. Bourouis, and M. A. Ullah, “An online kernel adaptive filtering-based approach for mid-price prediction,” Scientific Programming, vol. 2022, 2022.
  • S. Sinha, S. Mishra, V. Mishra, and T. Ahmed, “Sector influence aware stock trend prediction using 3d convolutional neural network,” Journal of King Saud University-Computer and Information Sciences, vol. 34, no. 4, pp. 1511–1522, 2022.
  • S. Suryawanshi, A. Goswami, P. Patil, and V. Mishra, “Adaptive windowing based recurrent neural network for drift adaption in non-stationary environment,” Journal of Ambient Intelligence and Humanized Computing, pp. 1–15, 2022.
  • A. Aggarwal, V. Sharma, A. Trivedi, et al., “Two-way feature extraction using sequential and multimodal approach for hateful meme classification,” Complexity, vol. 2021, 2021.
  • T. Choudhary, V. Mishra, A. Goswami, and J. Sarangapani, “A transfer learning with structured filter pruning approach for improved breast cancer classification on point-of-care devices,” Computers in Biology and Medicine, vol. 134, p. 104 432, 2021.
  • M. Dixit, K. Chaurasia, and V. K. Mishra, “Dilated-resunet: A novel deep learning architecture for building extraction frommedium resolution multi-spectral satellite imagery,” Expert Systems with Applications, vol. 184, p. 115 530, 2021.
  • K. Kotecha, D. Garg, B. Mishra, P. Narang, and V. K. Mishra, “Background invariant faster motion modeling for drone action recognition,” Drones, vol. 5, no. 3, p. 87, 2021.
  • K. Kotecha, R. Verma, P. V. Rao, et al., “Enhanced network intrusion detection system,” Sensors, vol. 21, no. 23, p. 7835, 2021
  • B. Mishra, D. Garg, P. Narang, and V. Mishra, “A hybrid approach for search and rescue using 3dcnn and pso,” Neural Computing and Applications, vol. 33, no. 17, pp. 10 813–10 827, 2021.
  • S. Mishra, T. Ahmed, V. Mishra, et al., “Multivariate and online prediction of closing price using kernel adaptive filtering,” Computational Intelligence and Neuroscience, vol. 2021, 2021.
  • I. Puthige, K. Bansal, C. Bindra, et al., “Safest route detection via danger index calculation and k-means clustering,” 2021.
  • T. Choudhary, V. Mishra, A. Goswami, and J. Sarangapani, “A comprehensive survey on model compression and acceleration,” Artificial Intelligence Review, vol. 53, no. 7, pp. 5113–5155, 2020.
  • B. Mishra, D. Garg, P. Narang, and V. Mishra, “Drone-surveillance for search and rescue in natural disaster,” Computer Communications, vol. 156, pp. 1–10, 2020.
  • V. K. Mishra and A. Sengupta, “Swarm-inspired exploration of architecture and unrolling factors for nested-loop-based application in architectural synthesis,” Electronics Letters, vol. 51, no. 2, pp. 157–159, 2015.
  • A. Sengupta and V. K. Mishra, “Simultaneous exploration of optimal datapath and loop based high level transformation during area-delay tradeoff in architectural synthesis using swarm intelligence,” International Journal of Knowledge-Based and Intelligent Engineering Systems, vol. 19, no. 1, pp. 47–61, 2015.
  • V. K. Mishra and A. Sengupta, “Mo-pse: Adaptive multi-objective particle swarm optimization based design space exploration in architectural synthesis for application specific processor design,” Advances in Engineering Software, vol. 67, pp. 111–124, 2014.
  • A. Sengupta and V. K. Mishra, “Automated exploration of datapath and unrolling factor during power– performance tradeoff in architectural synthesis using multi-dimensional pso algorithm,” Expert Systems with Applications, vol. 41, no. 10, pp. 4691–4703, 2014.
  • A. Sengupta, R. Sedaghat, and V. K. Mishra, “Execution time–area tradeoff in gausing residual load decoder: Integrated exploration of chaining based schedule and allocation in hls for hardware accelerators,” Facta Universitatis. Series: Electronics and Energetics, vol. 27, no. 2, pp. 235–249, 2014.
  • V. K. Mishra, A. Varshney, and S. Yadav, “Mitigating adversarial attacks using pruning,” in Proceedings of the 2023 Fifteenth International Conference on Contemporary Computing, ser. IC3-2023, Noida, India: Association for Computing Machinery, 2023, pp. 523–529, isbn: 9798400700224.  doi: 10.1145/3607947. 3608057.
  • 2d-attention mechanism with deep learning,” in 2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS), 2022, pp. 533–538. doi: 10.1109/ICCCIS56430.2022.10037742
  • A. Gupta, M. Dixit, V. K. Mishra, A. Singh, and A. Dayal, “Brain tumor segmentation from mri images using deep learning techniques,” in International Advanced Computing Conference, Springer, 2022, pp. 434– 448.
  • S. Mishra, T. Ahmed, and V. Mishra, “Mid price prediction via statistical feature expansion and kernel adaptive filtering,” in Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing, 2022, pp. 461–466.
  • P. Ravula, S. K. Ch, S. Gopisetty, H. Pedhamallu, V. K. Mishra, and T. Badal, “Voip spam detection using machine learning,” in 2022 6th International Conference on Intelligent Computing and Control Systems (ICICCS), IEEE, 2022, pp. 1251–1258.
  • S. Agarwal, M. Gupta, S. Khandelwal, et al., “Fitme: A fitness application for accurate pose estimation using deep learning,” in 2021 2nd International Conference on Secure Cyber Computing and Communications (ICSCCC), IEEE, 2021, pp. 232–237.
  • M. Dixit, K. Chaurasia, and V. K. Mishra, “Automatic building extraction from high-resolution satellite images using deep learning techniques,” in Proceedings of the International Conference on Paradigms of Computing, Communication and Data Sciences, Springer, 2021, pp. 773–783.
  • J. M. R. Dwarampudi, D. Rampavan, M. A. S. Sathwik, et al., “Image caption generation in telugu,” in 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), IEEE, vol. 1, 2021, pp. 438–443.
  • H. Kataria, A. Gupta, and V. Mishra, “Bennettnlp at semeval-2021 task 5: Toxic spans detection using stacked embedding powered toxic entity recognizer,” in Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), 2021, pp. 941–947.
  • S. Mishra, T. Ahmed, and V. K. Mishra, “Close-price prediction using online kernel adaptive filtering,” in 2021 Thirteenth International Conference on Contemporary Computing (IC3-2021), 2021, pp. 217–222.
  • A. Singh,N. Dua, V. K. Mishra, D. Singh, A. Agrawal, et al., “Predicting elections results using social media activity a case study: Usa presidential election 2020,” in 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), IEEE, vol. 1, 2021, pp. 314–319.
  • A. Tiwari, R. Goomer, S. S. Yenneti, S. Mehta, and V. Mishra, “Classification of humans and animals from radar signals using multi-input mixed data model,” in 2021 International Conference on Computer Communication and Informatics (ICCCI), IEEE, 2021, pp. 1–6.
  • A. Varshney, A. Bansal, A. Agarwal, V. K. Mishra, and T. Badal, “A comparative study of deep learning models for detecting pulmonary embolism,” in International Advanced Computing Conference, Springer, 2021, pp. 82–98.
  • K. Chaurasia, B. Neeraj, D. Burle, and V. K. Mishra, “Topographical feature extraction using machine learning techniques from sentinel-2a imagery,” in IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium, IEEE, 2020, pp. 1659–1662.
  • A. Gupta, H. Kataria, S. Mishra, T. Badal, and V. Mishra, “Bennettnlp at semeval-2020 task 8:Multimodal sentiment classification using hybrid hierarchical classifier,” in Proceedings of the Fourteenth Workshop on Semantic Evaluation, 2020, pp. 1085–1093.
  • M. Rathor, P. Sarkar, V. K. Mishra, and A. Sengupta, “Securing ip cores in ce systems using key-driven hash-chaining based steganography,” in 2020 IEEE 10th International Conference on Consumer Electronics (ICCE-Berlin), IEEE, 2020, pp. 1–4.
  • V. K. Mishra, N. Tiwari, and S. Ajaymon, “Dengue disease spread prediction using twofold linear regression,” in 2019 IEEE 9th International Conference on Advanced Computing (IACC), IEEE, 2019, pp. 182–187.
  • V. K. Mishra, “Cost aware majority logic synthesis for emerging technologies,” in 2017 IEEE International Symposium on Nanoelectronic and Information Systems (iNIS), IEEE, 2017, pp. 69–73.
  • V. K. Mishra and A. Sengupta, “Comprehensive operation chaining based schedule delay estimation during high level synthesis,” in 2017 IEEE International Symposium on Nanoelectronic and Information Systems (iNIS), IEEE, 2017, pp. 66–68.
  • V. K. Mishra and H. Thapliyal, “Heuristic based majority/minority logic synthesis for emerging technologies,” in 2017 30th International Conference on VLSI Design and 2017 16th International Conference on Embedded Systems (VLSID), IEEE, 2017, pp. 295–300.
  • V. K. Mishra and A. Sengupta, “Psdse: Particle swarm driven design space exploration of architecture and unrolling factors for nested loops in high level synthesis,” in 2014 Fifth International Symposium on Electronic System Design, IEEE, 2014, pp. 10–14.
  • A. Sengupta and V. K. Mishra, “Integrated particle swarm optimization (i-pso): An adaptive design space exploration framework for power-performance tradeoff in architectural synthesis,” in Fifteenth International Symposium on Quality Electronic Design, IEEE, 2014, pp. 60–67
  • A. Sengupta and V. K. Mishra, “Swarm intelligence driven simultaneous adaptive exploration of datapath and loop unrolling factor during area-performance tradeoff,” in 2014 IEEE Computer Society Annual Symposium on VLSI, IEEE, 2014, pp. 106–111.
  • A. Sengupta and V. K. Mishra, “Time varying vs. fixed acceleration coefficient pso driven exploration during high level synthesis: Performance and quality assessment,” in 2014 international conference on information technology, IEEE, 2014, pp. 281–286.
  • V. K. Mishra andD.Mehta, “Performance enhancement of numa multiprocessor systems with on-demand memory migration,” in 2013 3rd IEEE International Advance Computing Conference (IACC), IEEE, 2013, pp. 40–43.
  • V. K. Mishra and A. Sengupta, “Swarm intelligence driven design space exploration: An integrated framework for power-performance trade-off in architectural synthesis,” in 2013 25th International Conference on Microelectronics (ICM), IEEE, 2013, pp. 1–4.
  • A. Sengupta and V. K. Mishra, “D-logic exploration: Rapid search of pareto fronts during architectural synthesis of custom processors,” in 2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI), IEEE, 2013, pp. 586–593.
  • A. Sengupta, V. K. Mishra, and P. Sarkar, “Rapid search of pareto fronts using d-logic exploration during multi-objective tradeoff of computation intensive applications,” in Fifth Asia Symposium on Quality Electronic Design (ASQED 2013), IEEE, 2013, pp. 113–122.
  • S. Mishra, T. Ahmed, and V. Mishra, “Mid-price prediction using online kernel adaptive filtering,” in Emerging Technologies for Computing, Communication and Smart Cities, Springer, 2022, pp. 701–714.
  • S. Mishra, T. Ahmed, and V. Mishra, “Reliable biomedical applications using ai models,” in Healthcare Solutions Using Machine Learning and Informatics, Auerbach Publications, 2022, pp. 147–172.
  • S. D. Nukala, V. K. Mishra, and G. K. M. Nookala, “Modeling earthquake damage grade level prediction using machine learning and deep learning techniques,” in Data Management, Analytics and Innovation, Springer, 2021, pp. 421–433.
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Key Research Projects

  • Development of AI model for real-time Detection, Tracking and Classification of human/vehicle activities from video stream Project cost - Bharat Electronics Limited R&D PROJECT 48.4 Lakhs INR.
  • Study on External Factors Affecting Success Rates in Skilling Programs. (Sponsored by NSDC India) as PI Project
  • Song Analyser (Sponsored from Radio Mirchi) Project cost - 6 Lakh INR
  • Predictive Analytics in Skill Development - Leveraging Artificial Intelligence and Machine Learning Techniques ((Sponsored from NSDC India) Project Cost - 50k.
  • Context based Legal Search Project Cost - 7.5 Lakh
  • Handwritten character recognition (With EXL services Noida)
  • Digital Assistant Attorney Project (R&D PROJECT Technology Innovation Hub -DST )Cost - 10 Lakh
  • A web-based portal for assisting education platform using Generative AI Techniques Project (R&D PROJECT Technology Innovation Hub -DST) Cost - 10 Lakh
  • Atomic AI - Tiny AI systems for Resource constraint devices such as IoT,Mobile devices.
  • Deep Learning Powered Drone Surveillance for Assisting on Search and Rescue Operation during Disaster such as Earthquake, and Flood.
  • Secure Neural Network Model – Detecting Trojan in deep neural network model using explainable AI.

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