Richwell Colleges, Incorporated, Plaridel, Bulacan

A full-time load of four subjects across nine sections in three degree programs. Class adviser to BSIS 3-2.

• Advanced Object-Oriented Programming and Data Structures (IS313C), BS Information Systems
• Usability Engineering (IS313B), BS Information Systems
• IT Audit and Control (ISELECT313A), BS Information Systems
• Living in the IT Era (ELEC 113 and GEC ELECT 1s), BS Tourism Management and BS Civil Engineering

I wrote the CHED-aligned syllabus for every offering and rebuilt Advanced OOP around a full-stack track (HTML, CSS, Bootstrap, JavaScript, PHP, MySQL), ending with data structures from first principles. Every graded activity can be completed on paper when the lab or internet is unavailable. Complete courses deployed to Google Classroom, including graded assessments, using Google Apps Script.

ACLC College of Baliuag, Bulacan

Four tertiary IT subjects under the BS Information Technology program.

• Data Communications and Networking 1 (DCN1)
• Data Communications and Networking 3 (DCN3)
• Information Assurance and Security 2 (IAS2)
• Principles of Operating Systems and its Applications (POSA)

Prepared the complete course package for each subject: semester program, laboratory manual, and all four major examinations, following the institutional LMS and the prescribed BSIT curriculum outcomes. Networking is delivered through Cisco Packet Tracer and Cisco Networking Academy material; security through live demonstrations. I lecture bilingually for mixed-ability sections.

Keeping the Class Online: A Thematic Review of Network Performance Optimization Trends for Reliable E-Learning, 2022 to 2026

MSIT 643, Advanced Operating Systems and Networking. Adviser: Assoc. Prof. Carlo Inovero.

Synchronous online learning has become a permanent fixture of higher education, yet its delivery depends on residential and campus networks that were never engineered for sustained real-time media. This paper reviews fifteen peer-reviewed studies published between 2022 and 2026 to establish how contemporary operating system and network technologies address the reliability gap in e-learning. The review is organized thematically across six themes, from quality-of-service measurement and software-defined networking to edge computing, adaptive video delivery, security as a performance determinant, and the digital divide. Three findings emerge: the literature has shifted decisively from static provisioning toward learned, predictive control; prioritization consistently outperforms capacity expansion, because the flow that fails in an online class is low-bandwidth and latency-sensitive rather than bandwidth-hungry; and a measurement gap persists between the optimization literature, validated in simulation, and the education literature, which measures learner outcomes. The paper closes by mapping these trends onto a diagnosed Philippine household failure case and recommending an intervention order for school network administrators.

Early Identification of At-Risk Students Using Attendance and Quiz Data: An Explainable Learning Analytics Model for Low-Infrastructure Philippine Higher Education Institutions

MSIT 632, Technology and Project Management. Individual research proposal, ACM format.

Students who fail a course usually show warning signs weeks before the final grade: missed classes, skipped quizzes and falling scores. Instructors in many Philippine higher education institutions see these signs too late because the records sit in separate attendance sheets, gradebooks and learning management systems. Most learning analytics research predicts at-risk students from rich LMS clickstream data collected in online or well-resourced settings, which does not match blended, low-infrastructure classrooms where LMS use is uneven. This proposal describes a quantitative, predictive study that will build and evaluate an explainable early warning model using only the two data sources such classrooms reliably have: attendance check-ins and quiz records. Logistic regression, decision tree, Random Forest and gradient boosting classifiers are compared at three checkpoints in the term, with recall as the primary metric and SHAP values used to explain each prediction. The expected output is a validated model and a weekly, printable risk list that tells the instructor which students to contact and why.

Asalus Corporation (Intellicare)

• Resolved daily hardware and software incidents on Windows and Linux workstations, averaging 150+ tickets a month, most on first contact.
• Deployed and configured workstations to the security baseline; administered Active Directory, group policy, and user access.
• Took part in three OS and software migrations with the accompanying hardware refresh.

Smart Communications, Inc.

• Monitored high-availability platforms on a 24-hour rotation; handled critical escalations within service levels.
• Coordinated the transfer of ISP circuits, surveillance, and biometric systems during an office relocation, with no service interruption.

Philippine Long Distance Telephone Company (PLDT)

NET25 live national television

Invited as resource person for a live segment on super intelligent AI, about twenty minutes with the three hosts. I explained narrow AI, AGI, and superintelligence for a general audience, ran two live generative-AI demonstrations, and discussed which jobs are most and least exposed to automation. The hosts invited me back for future segments.

YouTube and TikTok

Free instructional content in Tagalog on IT certification and careers, reaching roughly 900,000 views and over 8,000 followers. I also maintain this site, which hosts a free CompTIA Network+ practice trainer for self-study learners.