Dr Harshvardhan Tiwari
(IT lecturer)
I am an IT lecturer and a seasoned machine learning researcher and scientist with over a decade of experience. My passion lies in developing cutting-edge AI solutions systems that not only meet user needs but also advance the field of artificial intelligence. My research interests encompass data science, machine learning, and deep learning, areas in which I have published extensively, with over 14 international journal articles, 7 conference papers, and 8 book chapters to my name. Throughout my career, I have demonstrated a strong ability to lead and mentor, effectively interacting with diverse groups and fostering a collaborative environment. My technical skills include proficiency in Python, machine learning, deep learning, and various data visualization and development tools. In addition to my academic achievements, I have participated in and conducted numerous workshops and value addition programs, contributing to the professional development of my peers and students. My goal is to continue pushing the boundaries of AI research and education, driving innovation and excellence in the field.
Academic Background
- PhD (Computer Science and Engineering) | JIIT, Noida | April 2014
- MTech (Computer Science and Engineering) | LNCT/RGPV, MP | Dec 2008
- BE (Computer Science and Engineering) | MIT/RGPV, MP | June 2005
Awards and Honors
Research Grants
TEQIP 1.3 Grant: For organizing a 5-day workshop on Outcome Based Education & NBA Accreditation.
TEQIP 1.3 Grant: For fruit crops yield estimation using machine vision techniques.
- VTU Research Grant: For developing an ML-based decision support system for early detection of CVD.
- Various Proposals: Submitted to DST, SERB, AYUSH, AICTE & VGST.
- Industry Collaborations:
- Aroma Coffee Works: Coffee plant disease identification, Dec-2021.
- Genbioca Science Pvt. Ltd.: Machine and deep learning based disease prediction models, Dec-2020.
- Training Programme: Computer vision at Amadeus Software Labs, Bangalore, April 2017.
Research Interests
Primary Research Interests:
- Data Science
- Machine Learning
- Deep Learning
Areas of Expertise:
- AI/ML Predictive Systems
- ML Algorithms and Tools
- Machine Learning Applications
- Machine Vision Techniques
- Cloud Computing Security
- Medical Image Processing
- Cryptographic Hash Functions
Professional Memberships
IEEE: Member number: 93228612
Enquiries
Share:
Current Research Projects
Early Prediction of Type-2 DM using CARI Dataset
Description: This project aims to create a predictive model for Type-2 Diabetes Mellitus (DM) using the CARI dataset, which includes 40 features related to prameha purvarupa (subclinical features of diabetes) as documented in Ayurveda. The goal is to classify individuals into high-risk and low-risk categories using various supervised machine learning algorithms.
Status: Completed
Collaborators: Central Ayurveda Research Institute, Bengaluru
Modelling and Optimization of Transesterification Process for Biodiesel Production
Description: This project focuses on optimizing the transesterification process for biodiesel production from specific raw materials. By using regression techniques, the project aims to establish a predictive system that accurately assesses the response features of biodiesel production based on process parameters like catalyst concentration, time, temperature, and rotation speed.
Status: Completed
Collaborators: Not applicable
Building Machine Learning Approach for the Correlation of Supercapacitance Performance and Surface Properties of Activated Carbon Derived from Banana Stem Fiber
Description: This research explores the use of machine learning models to predict the supercapacitance performance of activated carbon derived from banana stem fiber. Various regression techniques, including linear regression, random forest regression, Lasso, and artificial neural networks, are used to analyze surface properties such as surface area, pore volume, and pore size.
Status: Completed
Collaborators: Not applicable
Yield Prediction System
Description: This project aims to develop a machine learning model to predict crop yields, specifically using blueberry plant data and climatic factors. The objective is to provide accurate yield estimates to help farmers plan resources and logistics effectively. The project includes visualizing univariate and bivariate relationships using KDE curves and heatmaps.
Status: Completed
Collaborators: Not applicable
Selected Publications
- Tiwari, H. (2024). Enhancing classification accuracy of Diabetes Mellitus prediction using ensemble techniques. In Artificial Intelligence and IoT based Augmented Trends for Data Driven Systems (Intelligent Data-Driven Systems and Artificial Intelligence Series).
- Tiwari, H. (2022). Virtual Machine Selection Optimization using Nature Inspired Algorithms. In Applied Soft Computing Techniques and application, Apple Academic Press, Taylor and Francis Group.
- Tiwari, H. (2021). Early Prediction of heart disease using deep learning approach. In Deep Learning for Medical Applications with Unique Data, Elsevier.
- Tiwari, H. (2021). Parkinson Disease Prediction Model and Deployment on AWS Cloud. In Cloud Computing Technologies for Smart Agriculture and Health Care, Taylor and Francis Group.
- Tiwari, H. (2021). Early Detection of Autism Disorder Using Predictive Analysis. In Cyber-Physical, IoT, and Autonomous Systems in Industry 4.0, Taylor and Francis Group.
- Tiwari, H. (2021). A Review of Particle Swarm Optimization in Cloud Computing. In Smart IoT for Research and Industry, Springer.
- Tiwari, H. (2020). Analysis of Virtual Machine Placement and Optimization Using Swarm Intelligence Algorithms. In Business Intelligence for Enterprise Internet of Things, Springer.
- Tiwari, H. (2021). A Machine Vision Techniques Based Tongue Diagnosis System in Ayurveda. In AIDDMD-2021.
- Tiwari, H. (2023). Future Fusion+ UNet (R2U-Net) deep learning architecture for breast mass segmentation. Engineering Proceedings, 59(1), 44. https://doi.org/10.3390/engproc2023059044
- Tiwari, H. (2023). Future Fusion+: Breast cancer tissue identification and early detection. Journal of Autonomous Engineering, 6(3). https://doi.org/10.32629/jai.v6i3.789
- Tiwari, H. (2020). Genetic Algorithm approach to optimize test cases. IJETT, ISSN:2231-5381.
- Tiwari, H. (2021). A Reliable framework for virtual machine selection in cloud data center using practical swarm optimization. IJMCS, Vol 2, 677-685.
- Tiwari, H. (2021). Virtual Machine placement using energy efficient particle swarm optimization in cloud data center. Bulgarian Academy of Sciences, Volume 21, ISSN: 1311-9702.
- Tiwari, H. (2019). Test Case Generation Process using Soft Computing Techniques. International Journal of Innovative Technology and Exploring Engineering (IJITEE), Volume-9, Issue-1, pp. 4824-4831.
- Tiwari, H. (2018). Logistic map-based image encryption scheme. Vol. 13, no. 23, pp. 16573-16577.
- Tiwari, H. (2017). Merkle-Damgård Construction Method and Alternatives: A Review. Journal of Information and Organizational Sciences, vol. 41, no. 2, pp. 283-304.
- Tiwari, H. (2014). WIDPS: Wormhole Attack Intrusion Detection and Prevention Security Scheme in MANET. International Journal of Computer Applications, vol. 105, no. 10, pp. 21-26.
- Tiwari, H. (2014). Building a 256-bit Hash Function on a Stronger MD variant. Central European Journal of Computer Science, Springer, vol. 4, no. 2, pp. 67-85.
- Tiwari, H. (2013). Enhancing the Security Level of SHA-1 by Replacing the MD Paradigm. Journal of Computing and Information Technology, SRCE, vol. 21, no. 4, pp. 223-233.
- Tiwari, H. (2012). A Secure and Efficient Cryptographic Hash Function Based on NewFORK-256. Egyptian Informatics Journal, vol.13, no. 3.
- Tiwari, H. (2010). Cryptographic Hash Function: An Elevated View. European Journal of Scientific Research, vol. 43, no. 4.
- Tiwari, H. (2010). A Secure Hash Function MD-192 with Modified Message Expansion. International Journal of Computer Science and Information Security, vol. 7, no. 2.
- Tiwari, H., Pandey, N., & Swathi, B. (2024). Comparative analysis of predictive models for post-surgery kyphosis persistence. In 2024 2nd International Conference on Advancement in Computation & Computer Technologies (InCACCT), Gharuan, India (pp. 474-479). https://doi.org/10.1109/InCACCT61598.2024.10551156
- Tiwari, H. (2021). Hybrid Model for Virtual Machine optimization in cloud data center. 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS), pp. 137-141. doi: 10.1109/ICICCS51141.2021.9432149
- Tiwari, H. (2021). Test Automation Framework using Soft Computing Techniques. 2021 International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), pp. 1-4.
- Tiwari, H. (2021). Yield Estimation In Mango Orchards Using Machine Vision. National Institute of Technology Calicut, Kerala India CSMCS-20, AIP Conference proceeding 2336, 050004.
- Tiwari, H. (2019). Ensuring Confidentiality in BSN with 1-D Chaos Based Image Encryption Scheme. ICACCCN-18, July 2019, pp. 331-334.
- Tiwari, H. (2016). Preserving Confidentiality and Integrity of DICOM Images Using Cryptographic Algorithms. Third International Symposium on Computer Vision and the Internet (VisionNet), ACM, 21-24 Sep., LNMIIT, Jaipur, India.
- Tiwari, H. (2012). Crypto-Precision: Testing Tool for Hash Function. SNDS’12, Communications in Computer and Information Science proceedings, Trivandrum, India, vol. 335, pp. 206-216.
Copyrights
- Tiwari, H. (2023). Machine learning approach for the correlation of supercapacitance performance and surface properties of activated carbon derived from banana stem fibre. Successful Copyright Registration. Registration Number SW-17650/2023.
- Tiwari, H. (2023). Chitra-kavya based crypto system for securing the message communication. Successful Copyright Registration. Registration Number SW-16282/2023.
Workshops
- 2017: Workshop on “Basic Concepts of R and its Implication on Signal Processing” at Bangalore Institute of Technology.
- 2019: Workshop on “Process of NBA Accreditation” at SIET, Tumakuru.
- 2019: Workshop on “NBA Refresher” at PESITM, Shivamogga.
- 2020: Webinar on “EDA using Python” organized by SIRT, Bhopal.
- 2021: ATAL sponsored online FDP on “Potential Research Avenues in Computer Science and Biology” organized by MCE, Hassan.
- 2020: Workshop on “Data Science: Trends, Forecast and Challenges” organized by SVVV, Indore.
- 2021: Webinar on “Storytelling with Data Science” organized by SIRTE, Bhopal.
- 2022: Talk at international workshop on machine learning and human intelligence, MU-Jaipur.
Fellowship
SAVVY Fellowship Program: For aspiring and early-stage entrepreneurs, April 2021.
