Key Skills & Areas of Expertise
Over the years, my work has evolved across teaching, faculty development, research support, and professional training. Rather than being confined to a single domain, my expertise spans multiple technical and academic areas that intersect in real-world problem solving. This page outlines those areas of expertise and the tools and approaches applied in academic and professional contexts.
Open Source Technologies & Research-Oriented Tools
A significant part of my work has involved the use of open-source technologies within teaching, research, and experimentation environments. This includes working extensively with open source ecosystems and other open platforms to support automation, prototyping, and reproducible research workflows.
The emphasis has consistently been on transparency, adaptability, and long-term usability, enabling learners and researchers to understand systems at a foundational level rather than treating tools as black boxes.
Artificial Intelligence (AI) & Machine Learning
My engagement with artificial intelligence spans both foundational concepts and applied perspectives. This includes work across artificial intelligence, machine learning, deep learning and natural language processing (NLP), primarily using Python-based development environments.
I have practical exposure to large language model (LLM) platforms, including hands-on work with prompt engineering, retrieval-augmented generation (RAG) architectures, vector databases and OLLAMA-based local deployments.
Emphasis is placed on understanding how these systems generate outputs, where their limitations arise, and how supporting components influence reliability and system behavior.
Responsible & Academic Use of Generative AI
Alongside technical exposure, considerable attention is given to the responsible and academically sound use of generative AI. This includes work on AI hallucination detection and mitigation, human-in-the-loop validation, and frameworks for responsible generative AI adoption.
Specific focus areas include the role of AI in academic research, maintaining research integrity in the AI era, and guiding learners on how to make AI-assisted outputs academically defensible and methodologically sound.
Web & Application Development
My background in web and application development spans both traditional and modern approaches. Work in this area has included web technologies, PHP-based development, content management systems (CMS), and Java-based application concepts, along with exposure to semantic web principles and NoSQL databases.
The emphasis has always been on clarity of architecture, maintainability, and understanding system design choices rather than reliance on specific frameworks alone.
Internet of Things (IoT), Cloud Computing & Network Simulation
In the area of Internet of Things, my experience includes both hands-on development and conceptual system design. This work has involved microcontroller-based platforms such as ESP32 and Arduino, along with MicroPython-based development for introducing device-level programming in an accessible and practical manner.
I have conducted hands-on work with MQTT, and explored communication patterns using CoAP, BLE and AMQP for backend messaging scenarios.
Beyond device-level implementation, I have worked with LoRaWAN, NB-IoT and LTE-M / Cat-M at conceptual and simulation levels. This is complemented by experience with edge and fog computing concepts, cloud integration, and network and IoT architecture simulation.
Digital Pedagogy & Learning Technologies
A core part of my professional journey has involved digital pedagogy and the effective use of learning technologies. This includes experience with MOODLE LMS, AI-assisted tools for teaching and research, online assessments, e-learning delivery and SCORM-compliant content.
The emphasis remains on pedagogy-first design, with technology serving as an enabler rather than the driver of learning outcomes.
Instructional Design & Content Authoring
My work in instructional design focuses on aligning learning objectives, instructional flow, and assessment strategies. This includes instructional design methodologies, storyboarding, and digital content development using tools such as Articulate Storyline.
Attention is given to learner engagement, clarity, and outcome-driven design rather than purely visual presentation.
Blockchain & FinTech
My exposure to blockchain and financial technology is grounded in understanding system architecture, trust models, and practical constraints. This includes work with blockchain technology fundamentals, smart contract programming concepts, cryptocurrency mechanisms and broader FinTech ecosystems.
The approach remains analytical and application-oriented, with emphasis on real-world relevance rather than speculative narratives.
Cyber Security & Digital Forensics
In the area of cybersecurity, my work has focused on building foundational understanding rather than tool-driven specialization. This includes exposure to penetration testing concepts, server fingerprinting techniques, and introductory digital forensics workflows relevant to academic and enterprise environments.
The emphasis is on understanding attack surfaces and defensive thinking.
Data Science & Statistical Computing
My engagement with data science emphasizes interpretation and reasoning over automated outcomes. Experience includes working with Python, R, Julia, and Mojo, along with statistical tools such as SPSS and PSPP.
Work in this area focuses on data mining, statistical data interpretation, and communicating insights with methodological clarity.
Technical & Scientific Computing
I have long worked with tools used in technical documentation and scientific computation, including LaTeX, MATLAB, SciLab and Octave. These tools are applied primarily for research communication, numerical experimentation, and structured problem-solving.
Systems & Software Engineering Foundations
My background also includes systems-level understanding such as Linux administration, shell programming, software testing practices and audit and quality assurance concepts.
Mobile, AR/VR & Immersive Technologies
Exposure to cross-platform, hybrid, and native mobile application development has been complemented by exploratory and educational work in augmented reality (AR) and virtual reality (VR).
Quantum Computing (Foundational Perspective)
My engagement with quantum computing is focused on foundational understanding, including quantum computing principles, quantum information processing, qubit implementation concepts and quantum machine learning (QML) using Google Cirq, IBM Qiskit and other platforms for simulation.
The emphasis remains on conceptual clarity and realistic expectations.
How These Skills Are Applied
These areas of expertise collectively support my work across faculty development programs, academic mentoring, professional workshops, and research-oriented engagements.
Rather than being applied in isolation, they are combined selectively based on context, audience background, and learning objectives.