Nafiz Imtiaz

Queens, NY · AI Researcher & Applied Data Scientist

Hi, I'm Nafiz Imtiaz.

Published researcher with a Best Paper Award at IEEE CS BDC Symposium 2024 and an M.S. in Business Analytics from Montclair State University (GPA 3.91). My work spans Educational Data Mining, fairness-aware machine learning, adaptive learning, and applied analytics for real-world teams.

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Educational Data Mining Learning Analytics Business Analytics
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About

Research, analytics, and product work grounded in real educational and business systems.

I am an AI researcher and applied data scientist specializing in Educational Data Mining, learning analytics, and fairness-aware machine learning. My work focuses on building open-source, equity-centered tools, including digital biomarkers for early screening of learning disabilities and transparent Early Warning Systems.

Alongside research, I have worked across business analysis, adaptive learning product development, teaching, curriculum support, and data storytelling in both the United States and Bangladesh. That mix has shaped how I approach data: not only as modeling and prediction, but as something that must stay useful, interpretable, and people-centered.

Educational Data Mining Learning Analytics Fairness-Aware ML Early Warning Systems Predictive Modeling SQL Data Visualization Adaptive Learning Open-Source Research Predictive analytics Data storytelling

Future

The next chapter is already visible in the research directions I am building toward.

These themes already run through my CV and current work: adaptive learning, transparent decision-support systems, and equity-centered uses of AI in education and analytics.

01

Digital biomarkers for early screening

Exploring digital biomarkers and learning signals that can support earlier screening for learning disabilities through responsible, evidence-based modeling.

02

Transparent Early Warning Systems

Designing interpretable Early Warning Systems for education settings, with a focus on fairness, trust, and meaningful support rather than opaque prediction alone.

03

Open-source learning analytics tools

Developing equity-centered, open-source tools that connect research in Educational Data Mining with practical support for students, educators, and institutions.

Journey

Work experience, told as a moving line through the roles that shaped my practice.

January 2019 – March 2022 Project Research Assistant · BacBon Limited

Platform development, curriculum work, and teaching

At BacBon Limited in Dhaka, I collaborated with agile software teams to help develop and improve BacBon School and BacBon Tutors, with a hands-on focus on platform performance and user experience. I also worked on Math and English materials with the Asian Development Bank, taught English remotely to Japanese high school students through the SLC platform in collaboration with Shinkoshuppansha Keirinkan Co., Ltd., and supported marketing strategy and content review.

February 2025 – October 2025 Consultant Business Analyst · NetCom Learning Global

Adaptive learning product work and market analysis

At NetCom Learning Global in Manhattan, I developed visualizations for operations, sales, and stakeholder requirements, analyzed marketing datasets and documents through Excel pivot tables and dashboards, and consulted with local professionals to identify trigger points and shape customized learning solutions.

October 2025 – February 2026 Business Analyst · DCITM LLC

AI automation, workflows, and agentic AI research

At DCITM in Richmond, Virginia, I supported product launches by gathering requirements, preparing reports, and assisting with documentation and workflow evaluation. I also contributed to internal AI automation for data stacking and organization, and researched agentic AI architectures for automated decision-making pipelines.

February 2026 – Present Business Analyst · Bits and Binaries, Inc.

Local LLM tools, SQL pipelines, and reporting validation

At Bits and Binaries in Irving, Texas, I help brainstorm and build customer-centric local LLM tools for forecasting sales and reducing lost customers. I also develop complex SQL queries across relational data sources, gather analytics requirements with stakeholders, and support UAT by validating data logic and resolving reporting issues.

Work

Projects, publications, recognition, and leadership collected in one place.

Publications

Peer-reviewed work across education and analytics

  • Data-Driven Dashboards for Enhancing Investor Reporting Transparency in American Capital Markets (2026)
  • Leveraging AI for Data-Driven Decision Making and Automation in the USA Education Sector (2025)
  • Transforming Business Analytics: The Impact of Machine Learning on Performance Prediction in US Financial Sectors (2025)
  • Embracing Data-Driven Process Optimization to Highly Transform Instructional Administration in Higher Education Institutions (2023)
  • Overcoming Data Excess to Improve Decision-Making and Information Systems Plans for Organizational Performance (2020)

Google Scholar: View profile

Academic Project

Simulation-Based Adaptive Learning Analytics Framework

Developed and documented a simulation-based ALA framework in April 2025 using secondary datasets and computational modeling of community-college enrollment scenarios in collaboration with Illinois State University.

Using logistic regression, random forest, and gradient boosting, the project projected an 18% increase in completion, a 15% increase in retention, and a 12% improvement in workforce-readiness alignment when compared with static curricula.

Process Mining

Celonis process redesign project

In December 2024, I worked on a team-based Celonis project to analyze and redesign a complex business process, identify structural inefficiencies, enable concurrency, and improve workflows. I also completed the Celonis Academy certification in Academic Process Mining Fundamentals.

Recognition

Best Paper Award and international leadership

My paper “Optimizing Stroke Prediction Models for Real-World Application: Tackling Data Imbalance Without Synthetic Samples” received the Best Paper Award at the IEEE CS BDC Symposium 2024 in Dhaka. Earlier, I represented Bangladesh in Tokyo as a LAMP young leader, working on socio-economic and entrepreneurial challenges.

Research focus

Developing open-source, equity-centered tools, including digital biomarkers for early screening of learning disabilities and transparent Early Warning Systems.

Contact

Reach out by email and say Hi, or find me through my academic and professional profiles.

For research collaborations, analytics work, or academic conversations, the easiest way to contact me is by email.

Email

Personal: imtiazither@gmail.com

University: imtiazn1@montclair.edu