I am a technology leader and hands-on software engineer focused on building scalable, production-grade systems at the intersection of AI, software engineering, product, and business.
I specialize in turning complex ideas and AI research into real systems that work reliably in production.
Build intelligent systems that scale
Turn research into real products
Make technology decisions driven by value, not hype
I believe:
- AI is a tool, not a goal
- Architecture quality defines product longevity
- Strong engineering beats quick hacks
As a CTO / Tech Lead, I take ownership of:
- Defining long-term technical vision and roadmap
- Designing scalable, maintainable architectures
- Selecting technologies based on business value
- Leading and mentoring engineering teams
- Bridging business, product, and engineering
- Managing technical risk, security, and scalability
Advanced Studies / Research Focus:
- Physics-Informed Machine Learning (PIML)
- Scientific Computing
- Simulation + AI
Focused on integrating AI with physics-based models to produce predictive, efficient, and reliable systems.
Role: CTO · System Architect · Lead Engineer
Focus: AI-driven health management and lifestyle optimization
Key contributions:
- Offline-first system architecture with real-time Firebase sync
- Flutter UI inspired by Huawei Health
- Local AI inference via Rust + FFI
- Smart AI-generated muscle, nutrition, and general health reports
- SQLite storage for offline resilience
- Advanced dashboards and interactive charts
- Smart notifications
- Apple Watch & Fitbit integration
Business & Research Value:
- On-device privacy-preserving AI
- Production-grade reliability
- Combines ML + real-time data pipelines + health analytics
Role: Lead Researcher / CTO
Focus: Predicting complex physical system behavior using AI
Key contributions:
- Developed ML models integrating physics domain knowledge
- Applied Physics-Informed Machine Learning (PIML) techniques
- Built predictive pipelines combining Scientific Computing + Simulation + ML
- Produced accurate, robust predictions for physical systems
Business & Research Value:
- Integrates AI with engineering simulations
- Faster, reliable predictions than classical simulation-only pipelines
Role: Lead Engineer / CTO
Focus: Improving energy efficiency in industrial processes
Key contributions:
- Designed AI algorithms using Reinforcement Learning + Simulation
- Optimized energy consumption in factories
- Built end-to-end pipelines: Simulation → ML → Actionable Recommendations
Business & Research Value:
- Reduced energy costs, improved sustainability
- Applied advanced ML in real operational environments
Role: Lead Engineer / CTO
Focus: Industrial plant simulation with AI integration
Key contributions:
- Built simulation models of production lines
- Coupled simulations with ML to forecast bottlenecks and optimize workflow
- Designed end-to-end pipelines for real-time analytics
Business & Research Value:
- Enables decision support and operational efficiency
- Bridges gap between simulation research and practical industrial applications
Role: Founder · CTO
Focus: Intelligent credit and installment platform for the US market
Key contributions:
- Built secure and compliant architecture
- AI-driven credit behavior prediction
- Scalable backend and API design
- Risk management and fraud prevention systems
Business & Research Value:
- AI-powered financial product with B2C + B2B applicability
- Production-ready fintech platform leveraging AI and engineering best practices
- Production-ready AI services (Dockerized)
- REST APIs for AI & data systems
- Local & cloud-based LLM integration
- Data pipelines & analytics dashboards
- Clean, documented open-source contributions
As a CTO-level leader, I focus on transforming technology into measurable business impact:
- Define and execute technology strategy aligned with company vision
- Drive scalable, maintainable, and secure architecture that supports rapid growth
- Turn research & advanced AI into production-grade systems with ROI
- Optimize infrastructure & operational costs through smart engineering
- Mentor and empower engineering teams to deliver high-quality products fast
- Identify and mitigate technical and business risks proactively
- Enable cross-functional collaboration between product, engineering, and business teams
- Architecture-first mindset: Build systems that scale and adapt to future growth
- Simplicity with rigor: Prefer simple, elegant solutions that minimize technical debt
- Data-driven decision-making: Technical choices guided by metrics, business KPIs, and empirical evidence
- Risk-aware innovation: Encourage innovation while maintaining security, reliability, and compliance
- Team empowerment: Strong teams produce sustainable results; mentorship is key
- Offline-first & resilient systems: Design for reliability, performance, and high availability in all environments