PhD Research Portfolio | Fall 2026

I'm Md Anisur Rahman Chowdhury

Researching

I am building my PhD path around cloud security, serverless systems, Zero Trust enforcement, dependable AI, and physical and cloud network infrastructure protection. What matters most to me is doing research that is technically rigorous, experimentally careful, and still useful for the kinds of systems people actually run.

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Md Anisur Rahman Chowdhury portrait

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Published Papers

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Active Pipeline Works

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Google Scholar Citations

May 9, 2026

M.S. IT Completion Date

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About Me

Research Summary

I am building my research direction where cloud security, network infrastructure protection, and dependable AI meet.

My research goal is to work on problems in physical and cloud network infrastructure security that matter to both academia and real operations. I am especially interested in serverless defense, Zero Trust security, federated threat intelligence, secure distributed systems, and AI-supported security models that can move beyond a purely theoretical design.

I am finishing my Master of Science in Information Technology at Gannon University in Erie, Pennsylvania, with expected completion on May 9, 2026. As a Graduate Research Assistant under Dr. Kefei Wang, I have been developing first-author and collaborative work across cloud security, serverless firewall architectures, distributed systems, enterprise AI, and LLM reliability. My earlier enterprise IT and ISP experience keeps that research grounded in deployable systems and measurable operational needs.

Research Goal

I want to produce PhD work that advances cloud security and infrastructure defense while still staying close to real deployment challenges, system constraints, and operational usefulness.

Advisor Fit

I fit best in labs that work on cybersecurity, cloud systems, distributed infrastructure, dependable AI, serverless computing, or network security with strong systems implementation.

Research Ownership

My first-author work usually starts from the question itself and continues through methodology design, implementation, experimentation, paper writing, and technical refinement.

Name Email Current Role
Md Anisur Rahman Chowdhury
engr.aanis@gmail.com chowdhur014@gannon.edu
Graduate Research Assistant, Gannon University
Phone Application Track Location
+1 814-737-5770 PhD / RA / TA / Research Collaboration Erie, Pennsylvania, USA / Anywhere in USA
PhD Site Research portfolio LinkedIn Professional profile GitHub Research builds and code Google Scholar Citation profile ResearchGate Research network

Research Strengths

Cloud Security, Serverless Systems, and Zero Trust Research 99%
Physical and Cloud Network Infrastructure Protection 99%
First-Author Methodology, Implementation, and Experimental Work 98%
Python, Java, JavaScript, C++, SQL, PL/SQL, and JSON 98%
Distributed AI, LLM Reliability, and Agent Systems 97%
Technical Writing, Reproducibility, and Research Communication 98%

Education

Master of Science in Information Technology

Gannon University, Erie, Pennsylvania, USA | Aug 2024 - May 9, 2026 (Expected)

I am completing this degree as a Graduate Research Assistant in the Computer and Information Science Department, with a 3.93/4.00 GPA after the third semester and coursework centered on cloud computing, cybersecurity, networking, distributed systems, and analytics.

Bachelor of Science in Electronics and Telecommunication Engineering

University of Science and Technology Chittagong (USTC), Bangladesh | 2017

This is where I built the engineering base that later supported my work in communications, networking, systems, and infrastructure security.

Chittagong Cosmopolitan College

Science | 2011

I completed my higher secondary science education here before moving into engineering study.

Nasirabad Government Boys' High School

Science | 2009

This is where my early foundation in mathematics, science, and disciplined technical study began.

Experiences

Graduate Research Assistant

Gannon University - CIS Department, Erie, Pennsylvania | Aug 2025 - Present

I work on cloud security, serverless firewall architectures, Zero Trust security, distributed infrastructure protection, experimental implementation, and first-author and co-authored publication development under faculty supervision.

Cybersecurity Lecturer (CPT)

TAAS Services LLC, Remote, USA | Aug 2025 - Dec 2025

I delivered practical cybersecurity instruction in network defense, firewall configuration, threat detection, and vulnerability management, which strengthened the way I explain technical ideas and guide others through complex systems.

Senior Executive - Information Technology

S. Alam Group, Chittagong, Bangladesh | Dec 2021 - Jul 2024

This role grounded me in enterprise Linux and Windows systems, Active Directory, messaging, IP-PBX, monitoring, and large-user environments, and it still shapes the kind of research questions I find meaningful.

Technical Support Engineer - Networking

Link3 Technology Ltd., Chittagong, Bangladesh | Aug 2017 - Dec 2021

I supported enterprise accounts across Cisco, MikroTik, Juniper, Fortinet, and Cyberoam environments, which gave me the provider and production perspective behind my later network-security and infrastructure-protection research.

Google Scholar and Research Pipeline

Research Publications

Published Research Portfolio

This section shows the research path I want to carry into a PhD.

My publication record now spans cloud security, serverless systems, Zero Trust architecture, edge computing, enterprise AI, digital forensics, IoT intrusion detection, multimodal misinformation detection, and infrastructure-aware intelligent systems. The first-author direction I care about most is still cloud and network infrastructure protection, security automation, and dependable AI for real defensive systems.

12 Published Papers
72 Google Scholar Citations
4 First-Author IEEE Papers
7 Active Research Pipeline Items
View Google Scholar View ResearchGate
First-Author Direction

My strongest first-author work is around serverless firewall architecture, cloud security, Zero Trust security, distributed infrastructure protection, and dependable LLM systems.

Collaborative Research

I have also worked with Dr. Kefei Wang and broader teams across enterprise AI, cloud platforms, networking, digital forensics, and intelligent systems research.

PhD Fit Themes

The themes I want to keep pushing are physical and cloud infrastructure security, federated defense, secure distributed systems, and experimental security research that leads to deployable models.

Research Showcase

Featured Publication

A closer look at two research items at a time.

First Author | IEEE CSCloud 2025 | Nov 7, 2025

Towards a Serverless Intelligent Firewall: AI-Driven Security, and Zero-Trust Architectures

I used this paper to establish the first major line of my PhD direction: a serverless intelligent firewall model that combines adaptive defense, Zero Trust principles, and cloud-native protection.

Cloud Security Zero Trust Serverless
IEEE Xplore

First Author | IEEE CSITSS 2025 | Nov 20, 2025

Auction-Based Dynamic Resource Allocation for Optimized Edge Computing in Distributed Networks

This paper reflects my interest in distributed infrastructure behavior, where resource allocation, fairness, and performance have to be studied as real systems problems rather than abstract models.

Edge Computing Distributed Networks Optimization
IEEE Xplore

First Author | IEEE CSITSS 2025 | Nov 20, 2025

AI and Cloud Computing in Business Systems: A Hybrid Model for Enhancing Enterprise Resource Planning

I wrote this paper to show that my research can also work across intelligent enterprise systems, where AI and cloud design have to support decision quality, workflow efficiency, and scalable architecture.

Enterprise AI Cloud Systems ERP
IEEE Xplore

First Author | IEEE COMPAS 2025 | Oct 23, 2025

Deepfake Detection in MIS: Leveraging DenseNet and Multi-Scale Information for Enhanced Digital Forensics

This paper shows another part of my research range: using deep learning and digital forensics methods to improve manipulated-media detection in information systems environments.

Digital Forensics Deep Learning Security Analytics
IEEE Xplore

Co-Authored | IEEE ISAECT 2025 | Dec 18, 2025

Cloud-Based CRM Systems Enhanced by AI and Graph Theory: A Hybrid Model for Optimizing Customer Engagement

I contributed to this collaborative paper to work on a different application space, where AI, graph methods, and cloud systems support CRM intelligence and decision making.

Cloud CRM Graph Theory Business Intelligence
IEEE Xplore

Co-Authored | IEEE QPAIN 2025 | Jul 31, 2025

Enhancing Signature-Based Intrusive Detection System (IDS) for IoT Networks Using Machine Learning Algorithm

This paper let me work on IoT intrusion detection, where machine learning can strengthen the limitations of traditional signature-based detection in connected systems.

IoT Security Intrusion Detection Machine Learning
IEEE Xplore

Co-Authored | IEEE QPAIN 2025 | Jul 31, 2025

AI-Enhanced Adaptive Network Security for 6G and Edge Computing

I worked on this paper because adaptive defense for advanced communications and edge environments sits close to the long-term security problems I want to keep studying.

6G Security Edge Networks Adaptive Defense
IEEE Xplore

Co-Authored | IEEE QPAIN 2025 | Jul 31, 2025

Detecting misinformation with multimodal AI: leveraging vision and NLP for fact-checking

This collaborative work gave me another way to think about dependable AI, especially where multimodal reasoning and large-scale evaluation affect trust and decision quality.

Multimodal AI NLP Fact-Checking
IEEE Xplore

Co-Authored | IEEE QPAIN 2025 | Jul 31, 2025

Driving Industry 4.0 with Digital Twins: Enhancing Predictive Maintenance and Operational Performance Through IoT and Machine Learning

This paper let me contribute to intelligent operational systems research, where IoT, digital twins, and machine learning support predictive maintenance and performance modeling.

Industry 4.0 Digital Twins IoT Analytics
IEEE Xplore

Co-Authored | IEEE QPAIN 2025 | Jul 31, 2025

Leveraging Machine Learning and NLP for Adaptive Education Systems: A Personalized Approach for Children

I worked on this paper to contribute to adaptive intelligent systems research, especially where machine learning and NLP can support personalization and data-driven decisions.

Machine Learning NLP Adaptive Systems
IEEE Xplore

Co-Authored | IEEE ECCE 2025 | Feb 13, 2025

Attention-Enhanced U-Net Models for Breast Cancer Image Analysis: A Comparative Study

This collaborative study expanded my experience with experimental AI evaluation by comparing attention-enhanced architectures for medical imaging and model performance analysis.

Computer Vision Medical Imaging Deep Learning
IEEE Xplore

Co-Authored | IEEE ECCE 2025 | Feb 13, 2025

Enhanced Brain Tumor Detection Using Finetuned Transfer Learning Models: Achieving Superior Accuracy with Xception

This paper added to my experience with transfer learning, model tuning, and careful performance comparison in complex image-analysis tasks.

Transfer Learning Medical AI Image Analysis
IEEE Xplore

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Research Publications

Research Pipeline

Under Review and In Preparation

This is the part of my current research agenda that I am actively moving forward now. Most of it stays close to cloud security, Zero Trust automation, federated intelligence, reliable LLM systems, and AI-assisted infrastructure defense.

Under Review

  • Towards a Serverless Intelligent Firewall: Integrating Cross-Cloud Adaptation, AI-Driven Security, and Zero-Trust Architectures IEEE SmartCloud 2026
  • Federated Threat Intelligence for Multi-Cloud Security: A Privacy-Preserving AI Approach IEEE IC3ECSBHI 2026
  • Continuous Verification in Zero Trust Security: A Model for Secure Automation IEEE IC3ECSBHI 2026
  • Teaching Large Language Models to Think Twice: A Three-Stage Framework for Self-Correcting Mathematical Reasoning CAC'26 | American CSE Draft Submission
    Venue Repo Webpage
  • A Local Distributed Multi-Agent LLM Ensemble System for Complex Problem Solving Under Review
    Repo Webpage

In Preparation

  • Autonomous Self-Learning Serverless Intelligent Firewall: Integrating REST API-Driven Open-Source Threat Intelligence, Multi-Paradigm Machine Learning, and Federated Zero-Trust Architectures Target: Q1 Journal
  • Building a Team of AI Models: A Literature Review on Distributed Agent Networks Target: Conference Submission

GitHub Highlights

Portfolio Projects

These are the research builds I usually point people to when I want them to understand how I think. They help me turn paper ideas into visible systems, test architectures more concretely, and show that my research direction includes implementation, not only writing.

Security Research, Distributed Systems, and Dependable AI

I use these projects to make the research path easier to see.

I rely on these builds to show how my work moves from idea to implementation across serverless firewall design, Zero Trust security, threat intelligence integration, reproducible research tooling, distributed AI systems, and LLM reliability. They are one of the clearest ways to show how I work in a PhD setting.

6 Live research showcases
3 Firewall and cloud security builds
2 LLM and distributed AI systems
1 Reproducible data workflow tool

Project Showcase

Featured Project

A focused look at two projects at a time.

SIF-01 Serverless Firewall

Adaptive cloud-native defense design

First-Author Security Research Build

Serverless Intelligent Firewall

I built this project to turn the core firewall paper into a visible research system and to study how Zero Trust controls, traffic inspection, and serverless logic can work together in a cloud-native security model.

Serverless Security Zero Trust Research Prototype
View Repo Open Live Demo
SIF-02 Cross-Cloud Defense

Adaptive security across distributed clouds

Cross-Cloud Security Research Build

Serverless Intelligent Firewall Research-2

I used this version to move the firewall idea into a more realistic multi-cloud setting where policy adaptation, AI-assisted response, and Zero Trust enforcement have to deal with distributed infrastructure complexity.

Multi-Cloud Security Adaptive Defense Cloud Architecture
View Repo Open Live Demo
SIF-03 Autonomous Firewall

Threat intelligence and self-learning protection

Autonomous Security Architecture Build

Serverless Intelligent Firewall Research-3

I built this project to move toward an autonomous firewall model that combines REST API threat intelligence, machine learning, and federated Zero Trust ideas for more adaptive cloud network protection.

Threat Intelligence Machine Learning Federated Security
View Repo Open Live Demo
DataMentor Notebook Automation

Reproducible analysis and reporting workflows

Research Workflow and Reproducibility Tool

DataMentor / Notebook Studio

I built this project to make data analysis, notebook execution, and technical reporting easier to repeat, which matters to me because reproducibility is part of research quality, not just convenience.

Reproducibility Notebook Automation Research Workflow
View Repo Open Live Demo
Dist-AI Multi-Agent Ensemble

Local collaborative LLM reasoning system

Distributed AI Research Build

Distributed AI Multi-Agent Ensemble

I built this system to test a more distributed view of AI where local agents can coordinate, divide work, and solve harder problems together without depending on a centralized cloud runtime.

Agent Orchestration LLM Systems Distributed AI
View Repo Open Live Demo
ThinkTwice Self-Correcting LLM

Reliable reasoning through staged review

LLM Reliability Research Build

Self-Correcting LLM Mathematical Reasoning

I built this framework to test whether a model can become more dependable if it slows down, reviews its reasoning, and improves the answer before responding.

LLM Reliability Reasoning Evaluation Self-Correction
View Repo Open Live Demo

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Portfolio Projects

Knowledge Sharing

Blog and Insights

I use this part of my site to explain the research side of my work in a more readable way. Paper titles, project cards, and resume bullets only go so far, so here I write about the questions behind the work, the systems I built, and the direction I want to keep following in a PhD.

Why I Write Here

I wanted one place where I could explain the research in simpler language without losing the technical meaning.

On the homepage, I keep things compact. In the blog, I slow down and explain what problem I was trying to solve, why a project or paper matters, what I learned from it, and where it fits in my broader research path. I write mostly about cloud security, serverless systems, Zero Trust security, distributed AI, LLM reliability, and infrastructure protection.

4 research lanes I explain here
12 + 7 papers and pipeline items
6 research demos with context
19 research notes across the blog
Read My Blog See All Notes
For Faculty Review

If you are reviewing my research fit, this part shows how I think through problems, how the projects support the papers, and what direction I want to keep building.

For Admissions Review

If you want a clearer picture of my academic preparation, this section helps connect the publications, the research systems, and the longer-term PhD goals.

For Research Collaboration

If you are considering collaboration, I use these notes to show how I move from idea to implementation, evaluation, and writing across security and AI-related projects.

Blog Showcase

Featured Reading Lane

Two reading lanes at a time, with the same compact flow as the rest of the site.

5 Themes

Research Direction

This is where I explain the questions I want to keep working on in a PhD.

I write about the themes that shape my research most: cloud security, network infrastructure protection, Zero Trust automation, serverless firewall models, federated defense, and dependable AI systems.

  • Why physical and cloud infrastructure security remains my core direction
  • How I connect serverless defense and Zero Trust research questions
  • Why I care about deployable security systems, not only abstract models
Read This Part More Notes
12 + 7

Publication Notes

Here I break down the papers in simpler language so the main idea is easy to follow.

I use this part to explain what each paper is actually trying to solve, where my first-author work fits, and how the published papers connect to the under-review and in-preparation work.

  • Short explanations for the papers on Google Scholar
  • Context for the current submission pipeline and ongoing themes
  • Research notes that make the papers easier to discuss before reading the full text
Read This Part Open One Paper
6 Demos

Research Projects

Here I explain how the GitHub builds support the papers and the next ideas.

I wanted the project section to show more than repositories. In these notes, I explain the problem behind each build, how I approached it, and what it says about my interests in cloud security, distributed AI, LLM reliability, and reproducible research systems.

  • How the firewall research builds grew across multiple versions
  • Why DataMentor matters to my research workflow and reproducibility
  • What I am trying to learn from distributed AI and self-correcting LLM systems
Read This Part Open One Project
Current Work

Current Pipeline

I also use the blog to explain the work that is still moving toward submission or review.

Some of the most important parts of my research path are still in motion. I use this part to explain where the firewall agenda is going next, why federated threat intelligence matters to me, and how the LLM projects connect to future papers.

  • How the current under-review papers extend the first-author direction
  • Why the LLM systems work belongs in the broader research plan
  • How I think about next-step papers before they are finalized
Read This Part Open One Note

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Blog and Insights

How To Read It

You can start anywhere and follow the research part that matches your interest.

I wrote these notes in a direct way because I want the research side of the site to feel useful, not heavy. Whether you care most about publications, cloud security projects, AI systems, or the pipeline that is still developing, this part of the site makes the path easier to follow.

Paper and Research Notes Research Project Notes Firewall Paper Note Project Write-Up All Blog Notes
Go to My Blog View All Notes

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Resume Center

I use this section for the academic version of my record. It is written for faculty review, PhD admission, research applications, and collaboration conversations that need more than a short profile summary.

Research Track

I keep the PhD resume aligned with the portfolio, the papers, the project work, and the next research direction.

If you are reviewing me for a PhD position, a research lab, or academic collaboration, this is the document that matches the rest of the page. It focuses on research direction, first-author work, collaborative publications, ongoing submissions, systems implementation, and the questions I want to continue in doctoral study.

12 published papers
7 active pipeline items
72 Google Scholar citations
3.93 current GPA

PhD Application Track

PhD Resume

Focused on research direction, first-author work, co-authored publications, ongoing submissions, reproducible systems, and the areas where I want to contribute in future academic work.

12 Published 7 In Pipeline Cloud + Security + AI Faculty Review Ready
Read PDF Download PDF Download DOCX

PhD Admission and Collaboration

Contact Me

Open to Fully Funded PhD Opportunities

I am actively looking for fully funded PhD opportunities for Fall 2026, including RA or TA support, where I can keep building on cloud security, network infrastructure protection, serverless systems, dependable AI, and security-focused distributed systems research.

This message goes straight to my email through the contact form.