Business graduate applying computational and technological methods to traditional business subjects
Ujire, IN.
About
Highly analytical Business Administration graduate with First Class Distinction, adept at applying computational and technological methods to complex business challenges. Proven expertise in machine learning, predictive analytics, and econometric modeling, demonstrated through extensive research in cryptocurrency security, consumer behavior, and corporate finance. Eager to leverage strong quantitative skills and research acumen to drive data-driven insights and innovation in forward-thinking organizations.
Work
Balaji Dinasl LineSale
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Field Research and Business Intelligence Analyst
Ujire, Karnataka, India
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Summary
Analyzed customer consumption patterns and brand perception drivers to inform strategic decision-making, utilizing empirical surveys and CRM data to identify recurring market trends.
Highlights
Investigated consumption patterns and brand-perception drivers across 150+ customers, systematizing insights for strategic business applications.
Executed empirical field surveys and CRM-based data collection, applying spreadsheet-based panel and cross-sectional analysis to identify recurring consumption and perception patterns.
Synthesized findings into actionable business intelligence reports, which were adopted for strategic decision-making and informed FMCG survey instrument design.
Developed a deep understanding of customer behavior at the point of sale, translating complex data into clear, concise reports for management.
Volunteer
Campaign Lead
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Best Foundation & National Service Scheme
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Led community service initiatives, organizing blood donation camps and coordinating free tuition for underprivileged students.
Highlights
Organized successful blood donation camps, contributing to community health and welfare initiatives.
Coordinated free tuition provision for underprivileged students, enhancing educational access and support.
Managed campaign logistics and stakeholder engagement, demonstrating leadership and organizational skills in community service.
Education
SDM College (Autonomous), Mangalore University
Mangalore, Karnataka, India
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BachelorBusiness AdministrationGrade: First Class Distinction
Awards
First Class Distinction, BBA
SDM College (Autonomous), Mangalore University
Awarded for achieving First Class Distinction in the Bachelor of Business Administration program, demonstrating academic excellence.
Excellence in Financial Analytics and Forecasting
Institution/Program Award
Recognized for developing a momentum/volatility model utilizing options implied-volatility skew and order-book depth.
Innovation in Technology and Product Design
Institution/Program Award
Honored for contributions to an AI-integrated cryptocurrency trading platform.
Publications
A zero-trust architecture for blockchain network infrastructure
Journal of Digital Assets and Monetary Research (JDAMR), Glint Open Access
Proposes a four-layer zero-trust architecture (identity and trust, network, consensus, application) for blockchain peer-to-peer network security, grounded in NIST SP 800-207.
Corporate governance and ownership structure in the digital age
SSRN
Systematic review of corporate governance under digital transformation, developing a four-pillar framework for firms and regulators addressing AI's simultaneous broadening and concentration of shareholder activism.
Cryptocurrency and cross-border remittances
SSRN
Reviews crypto-enabled remittance channels for developing economies, estimating ~90% cost reduction for stablecoin-based transfers relative to traditional FX corridors and proposing a four-pillar policy framework.
Multi-method study identifying an inverted-U relationship between MVP distinctiveness and growth, moderated by AI human capital.
Skills-based hiring versus degree-based hiring
SSRN
Reviews the 2020-2026 shift toward skills-based hiring, reporting skills-assessment validity roughly five times that of education credentials.
Supply chain resilience and geopolitical risks
SSRN
Identifies five persistent disruption mechanisms in global supply chains (2020-2026) and a 167% year-on-year rise in disruption alerts, developing a three-dimensional resilience framework.
AI for predictive preventive healthcare
SSRN
Examines AI/ML and wearables for chronic-disease detection, reporting ensemble models reaching 96.4% cardiovascular-disease prediction accuracy.
Economic modeling of AI integration in healthcare
SSRN
Part of a broader program examining the economic case for AI integration in healthcare, with findings translated into an applied prediction stack and early-stage product roadmap.
Healthcare expenditure and economic burden on families
SSRN
Part of a broader program examining out-of-pocket expenditure burdens in India, reporting on ensemble models for chronic-disease prediction.
Closing the response-latency gap in cryptocurrency wallet security: Can incident response be fully automated? [Research Problem]
Octopus.ac
Investigates whether full automation can achieve near-zero latency in cryptocurrency wallet incident response.
An ensemble ML detection engine coupled to an automated cold-storage evacuation bridge can close the wallet response-latency gap [Hypothesis]
Octopus.ac
Proposes an ensemble machine learning detection engine combined with an automated cold-storage evacuation bridge to reduce wallet response latency.
CryptoAgent: Architecture, detection pipeline, and evaluation protocol [Method]
Octopus.ac
Details the architecture, detection pipeline, and evaluation protocol designed for the CryptoAgent project.
CryptoAgent evaluation results: Detection latency, response latency, and accuracy, including a simulated deployment scenario [Results]
Octopus.ac
Presents the evaluation results for CryptoAgent, including detection latency, response latency, and accuracy in a simulated deployment.
Comparative analysis of CryptoAgent against manual, alert-only, and freeze-only response models [Analysis]
Octopus.ac
Provides a comparative analysis of CryptoAgent's performance against traditional incident response models.
What CryptoAgent's evaluation implies for automated wallet defence: Guarantees and limits [Interpretation]
Octopus.ac
Interprets the implications of CryptoAgent's evaluation for automated wallet defense, outlining its guarantees and limitations.
Deploying CryptoAgent: Practical requirements and applicability to institutional and retail wallets [Applications]
Octopus.ac
Discusses the practical requirements and applicability of deploying CryptoAgent in institutional and retail wallet contexts.
CryptoAgent: An Ensemble Machine-Learning Detection Engine for Cryptocurrency Wallet Security
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Summary
Led an independent research project to develop an ensemble machine-learning detection engine designed to automate incident response for cryptocurrency wallet compromises, aiming for near-zero latency.
Television Advertising and Brand-Switching Behavior in FMCG Categories
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Summary
Conducted an undergraduate research project to analyze the impact of television advertisement exposure on brand-switching behavior among FMCG consumers in a semi-urban retail market.