About Me

DESIGN & THINKING

DIGITAL-FIRST PRODUCT VISION

I approach technology as a tool for real-world impact, not just functionality. My work begins with understanding people—students, researchers, or communities—and translating their needs into intuitive, scalable digital solutions. Whether building an AI research pipeline or a volunteering platform, I prioritize clarity, usability, and purpose-driven design that feels natural across devices and audiences.

SYSTEMS-LEVEL PROBLEM SOLVING

I think in systems, not features. From distributed ML workflows to end-to-end app architectures, I design solutions that consider data flow, edge cases, scalability, and long-term maintainability. This mindset allows me to connect research, engineering, and user experience into cohesive, resilient products rather than isolated components.

DEVELOPMENT

FULL-STACK ENGINEERING

I build production-ready applications across the stack, from responsive frontends to scalable backends. My experience includes React / React Native, Expo, Firebase, REST APIs, authentication, real-time updates, and deployment pipelines. I focus on clean architecture, modular code, and performance-aware design—ensuring systems are fast, reliable, and easy to evolve.

AI & MACHINE LEARNING IMPLEMENTATION

I design, train, and deploy machine learning models for real-world use cases. My work spans computer vision, medical imaging, time-series analysis, and large-scale data pipelines. I focus on validation, interpretability, and cross-dataset verification—bridging the gap between experimental models and defensible, research-grade results.

DATA & RESEARCH

ASTROPHYSICS & TIME-DOMAIN ANALYSIS

I conduct data-driven astrophysical research using large astronomical surveys such as ZTF, Gaia, WISE, and Pan-STARRS. My work emphasizes statistical rigor, multi-survey cross-validation, and physical plausibility—particularly in identifying rare transient phenomena like changing-look AGNs. I treat scientific claims conservatively, prioritizing evidence over novelty.

EXPERIMENTAL DESIGN & VALIDATION

I design experiments that scale—from thousands to millions of data points—while maintaining reproducibility and interpretability. I focus on separating signal from noise, understanding uncertainty, and applying domain-appropriate metrics to avoid over-claiming results. This approach applies equally to scientific research and applied ML systems.

ROBOTICS & HARDWARE

EMBEDDED SYSTEMS & AUTONOMOUS PLATFORMS

I work hands-on with robotics systems integrating hardware, sensors, and onboard intelligence. My experience includes Arduino, Raspberry Pi, Jetson Nano, motor control, power systems, and real-time data processing. I design systems with careful attention to constraints such as weight, power efficiency, reliability, and modularity.

AI-ENABLED PERCEPTION

I integrate computer vision and AI models into physical systems for tasks such as object detection, navigation, and environment mapping. I focus on making perception systems robust to real-world conditions rather than ideal lab setups—handling noise, latency, and incomplete data.

STRATEGY & LEADERSHIP

PRODUCT OWNERSHIP & EXECUTION

I take ideas from concept to deployment. I've led projects where I defined the vision, built the technology, iterated based on feedback, and delivered usable products with real users. I balance ambition with execution, ensuring projects move forward without sacrificing quality or credibility.

COMMUNITY-DRIVEN INNOVATION

I build technology with service in mind. Through platforms like NexoLink and educational AI workshops, I focus on empowering communities, increasing access, and lowering barriers to participation. Leadership, to me, means building tools that others can use, trust, and grow with.

COMMUNICATION

TECHNICAL STORYTELLING

I translate complex technical ideas into clear, compelling narratives for diverse audiences. Whether explaining astrophysical variability, machine learning models, or system architecture, I focus on why something matters before how it works. This approach ensures ideas are understood, trusted, and actionable—by researchers, students, and non-technical stakeholders alike.

EDUCATION & KNOWLEDGE SHARING

I actively design and deliver educational content that lowers the barrier to advanced technology. Through workshops, presentations, and interactive platforms, I teach AI concepts, scientific thinking, and problem-solving in a way that emphasizes intuition, ethics, and real-world relevance. My goal is not just to inform, but to empower others to explore, question, and build independently.