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33
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Introduction
The candidate has earned a PhD from the MIS department. During his doctoral studies, he was honored with the prestigious Huang Tiyun Innovation Research Award from the MIS department. He has amassed significant industry experience at TATA Motors in India, DIRUI in China, and BALS Elektrotechnik as part of the German-China cooperation. His research pursuits focus on the application of econometrics and AI techniques in Fintech, investigating the business value of IS, and examining sociotechnical.
Current institution
Additional affiliations
February 2018 - present
Education
February 2017 - February 2019
Publications
Publications (33)
This study investigates the impact of Direct Market Access (DMA) on the economic results of Small-Scale Dairy Farmers (SSDF) in Gujarat, India. Specifically, it explores how DMA impacts Profit Margins (PM), Supply Chain Efficiency (SSE), and Economic Resilience (ER), compared to Traditional Market Access (TMA), which intermediaries dominate. A tota...
In other growth trends and sustainable development of the economy’s globalization, low manufacturing utilization rates, production resource imbalances, and impaired coordination functions are growing. To tackle the difficulties mentioned above, organizations must securely determine how to share distant and heterogeneous production resources. Previs...
Competition and concurrent engineering (CE) businesses are growing. Faster product creation, quality improvement, manufacturing process adoption, and reduced client demand cost are vital for corporate success. Implement concurrent engineering to make high-quality goods. CE is a parallel, systematic method to design. The chief executive officer (CEO...
Energy prices (EPs) play an imperative role in South Asian Country (SAC) Gross Domestic Product (GDP). This research empirically examines the influence of sustainable energy price shocks (EPSs) on macroeconomic indicators. The study is to forecast the impact of EPS on macroeconomic indicators from 1980 to 2020. The analysis is carried out by employ...
Power Station (PS) monitoring systems are becoming critical, ensuring electrical safety through early warning, and in the event of a PS fault, the power supply is quickly disconnected. Traditional technologies are based on relays and don’t have a way to capture and store user data when there is a problem. The proposed framework is designed with the...
Internet applications such as Online Social Networking and Electronic commerce are becoming incredibly common, resulting in more content being available. Recommender systems (RS) assist users in identifying appropriate information out of a large pool of options. In today’s internet applications, RS are extremely important. To increase user satisfac...
Access Control Models (ACM) must secure the communication system of devices in Internet of Vehicles (IoV) under cloud computing architecture. Existing ACM, on the other hand, struggles to determine the right granularity of permissions when dealing with vast numbers of data in the IoV. Furthermore, IoV is vulnerable to attacks, as attackers can read...
Traditional banks face the issue of risk diversification, and it is dealt with when they evolve into financial institutions. So, the present study aims to investigate banking and off-balance sheet (OBS)-based risks and regulatory changes in certain age-old South Asian (SA) banks and finds the tenacity of the OBS in the long run. For these research...
With Deep Learning (DL) outperforming previous Machine Learning (ML) techniques in classifying images, the remote sensing community has recently shown an increased interest in using these algorithms to classify Land Use and Land Cover (LULC) using multispectral and hyperspectral data. Land Use (LU) and Land Cover (LC) are two types of cartographic...
Most of the world’s most advanced defense technologies are robots, and the defence industry is slowly moving toward including AI in the military robots they build. For these smart robots to make their own decisions about where to go and what to do, they need to be limited by several algorithms that run continuously and at the same time. Autonomy is...
Deep Learning (DL) in finance is widely regarded as one of the pillars of financial services sectors since it performs crucial functions such as transaction processing and computation, risk assessment, and even behavior prediction. As a subset of data science, DL can learn and develop from their experience, which does not require constant human int...
In the banking business, Machine Learning (ML) is critical for averting financial losses. Credit risk evaluation is perhaps the most important prediction task that may result in billions of dollars in damages each year (i.e., the risk of default on debt). Gradient Boosted Decision Tree (GBDT) models are now responsible for a large portion of the im...
The Sloan Digital Sky Survey (SDSS) comprises about one billion objects classified spectrometrically. Because astronomical datasets are so enormous, manually classifying them is nearly impossible—a huge dataset results in class imbalance and overfitting. We recommend a framework in this research study that overcomes these constraints. The framework...
The present world is intimidated by the problem of water scarcity that is to be addressed immediately. So, it is wise to treat wastewater to meet the massive need for drinking water for the fast-growing population. The magnificent application of Internet of Things (IoT) technology in many smart cities has derived fruitful results. This research stu...
The present world is intimidated by the problem of water scarcity that is to be addressed immediately. So, it is wise to treat wastewater to meet the massive need for drinking water for the fast-growing population. The magnificent application of Internet of Things (IoT) technology in many smart cities has derived fruitful results. This research stu...
This study aims to investigate the relationship of firm performance and corporate social responsibility reporting and the moderating role of a firm’s life cycle stages in Chinese listed companies. We used the sample of all A-share listed firms on the Shanghai and Shenzhen stock exchanges for the period 2010 to 2020. The authors used pooled ordinary...
Purpose – the purpose of this research is to systematically understand the behavioral and emotional aspects of potential tourists and investigated the conceptual model in the context of the travel marketers’ (TMs) facebook fan pages. Research methodology – the present study performed the two-step SEM approach suggested. the first step involved conf...
Purpose – the purpose of this paper is to investigate whether supply line engineering strategies of goods and service exports, exports transport services and export time have a significant impact on GDP growth of BIMSTEC countries or not. Research methodology – the study employed a panel vector error correction model (VECM) instead of loose VAR to...
This article describes how machines are the new breed of traders as news sentiment arrivals drive the stock price change. Strategies are the technical approach to search for profit from event-based speculations. This paper revisits these topics in a novel way and first uncovers distinctive characteristics of high frequency trading in Helsinki stock...
This paper reviews the currently faced challenges of China-Pakistan Economic Corridor (CPEC) from the security standpoint. It’s considered central to China-Pakistan relations and will link Kashgar to Gawadar port through the extension of Silk Road initiative name as One Belt One Road (OBOR). With the investment of 46 billion dollars and expected to...
This paper reviews the currently faced challenges of China-Pakistan Economic
Corridor (CPEC) from the security standpoint. It’s considered central to
China-Pakistan relations and will link Kashgar to Gawadar port through the extension
of Silk Road initiative name as One Belt One Road (OBOR). With the investment of 46
billion dollars and expected to...
