""" Built-in Knowledge Base — Md Arifur Rahman Comprehensive knowledge covering: - Full work experience (2014-present) - Education background - All 7 published papers - Certifications & professional development - Skills & technical expertise """ from src.retrieval.rag_pipeline import DocumentChunk def get_builtin_chunks() -> list[DocumentChunk]: entries = [ # ── PROFESSIONAL PROFILE ────────────────────────────────────────────── { "title": "Professional Profile — Md Arifur Rahman", "category": "profile", "text": ( "Md Arifur Rahman is an innovative ML Engineer and AI Researcher based in " "Atlanta, GA with strong foundations in analytics, software development, " "machine learning, and data science. He applies advanced research to " "enterprise use cases, integrating generative AI, predictive maintenance, " "and real-time dashboards into cloud-native model pipelines. He builds " "scalable full-stack solutions and deploys ML models that optimize processes " "and enable intelligent decision-making. He is authorized to work in the US " "with no sponsorship required. Contact: arifme071@gmail.com | 912-541-9169 | " "Atlanta, GA 30349." ) }, # ── WORK EXPERIENCE ─────────────────────────────────────────────────── { "title": "Current Role: PIN Fellow — AI in Manufacturing, Georgia Tech (2025–Present)", "category": "experience", "text": ( "Md Arifur Rahman is currently a PIN Fellow (AI in Manufacturing) at the " "Partnership for Innovation at Georgia Tech, Atlanta GA, starting July 2025. " "This is under the Georgia-AIM grant to advance manufacturing optimization. " "He developed ML prototypes including hidden Markov model and reinforcement " "learning pipelines on WAAM datasets. He engineered AI-driven tools to align " "production with dynamic demand/supply signals and established MLOps best " "practices across cross-functional teams. Key achievements: improved material " "utilization by 5% using HMM-RL on WAAM datasets; deployed an AI-driven " "material design prototype to production; authored findings in a peer-reviewed " "Springer publication (2026)." ) }, { "title": "Previous Role: Data Analyst at Norfolk Southern Corporation (2024–2025)", "category": "experience", "text": ( "At Norfolk Southern Corporation in Atlanta GA (January 2024 – March 2025), " "Arifur worked as a Data Analyst/Reporting Supervisor Associate on the Digital " "Train Inspection team. He delivered end-to-end solutions from server-side data " "processing to automated reporting for zone-wise inspection leaders and senior " "stakeholders. He built GIS-enabled Power BI and Tableau dashboards to visualize " "train health and inspection data. Key achievements: automated workflows using " "Alteryx/SQL reducing manual processing by 3%; developed GIS dashboards for " "real-time train health monitoring adopted company-wide; identified inspection " "inefficiencies improving turnaround time by 5%." ) }, { "title": "Research Role: ML & Data Analytics Research Assistant, Georgia Southern University (2022–2023)", "category": "experience", "text": ( "At Georgia Southern University in Statesboro GA (August 2022 – December 2023), " "Arifur worked as a Research Assistant in ML & Data Analytics. He conducted " "research on rail systems safety and reliability, developing anomaly detection " "models and real-time monitoring tools on live industry datasets. Key achievements: " "built ML models for anomaly detection on live HTL loop-MxV rail datasets from " "AAR/TTCI Pueblo CO achieving 95% accuracy; published 7 peer-reviewed papers in " "ASME and Springer journals accumulating 110+ citations; developed Python/SQL " "dashboards for real-time asset monitoring; led data collection under AAR/TTCI " "and Georgia Southern University grants." ) }, { "title": "Bangladesh Experience: Deputy Manager at Aramit Limited (2018–2022)", "category": "experience", "text": ( "Before coming to the US, Arifur served as Deputy Manager at Aramit Limited " "in Bangladesh from February 2018 to July 2022 — nearly 4.5 years. He " "demonstrated expertise in mechanical and process development, overseeing " "mechanical issues and leading preventive maintenance initiatives. He managed " "production equipment, hydraulic and pneumatic systems, and cross-functional " "engineering teams. This role gave him 4+ years of hands-on manufacturing " "and operations management experience." ) }, { "title": "Bangladesh Experience: Assistant Engineer at KSRM Billet Industries (2014–2018)", "category": "experience", "text": ( "Arifur began his professional career as an Assistant Engineer at KSRM Billet " "Industries Ltd in Bangladesh, a steel manufacturing company. From 2014 to 2018 " "he gained foundational experience in mechanical engineering, equipment " "maintenance, production operations, and industrial process management. " "This role combined with his Aramit Limited experience gives him over " "8 years of total professional experience spanning manufacturing, operations, " "data analytics, and AI/ML research." ) }, # ── EDUCATION ───────────────────────────────────────────────────────── { "title": "Education: Admitted to Georgia Tech OMSCS (MS Computer Science, Fall 2026)", "category": "education", "text": ( "Arifur has been admitted to the Georgia Institute of Technology's Online " "Master of Science in Computer Science (OMSCS) program, starting Fall 2026. " "This is a part-time online program at one of the top CS programs in the US. " "Georgia Tech OMSCS is ranked among the best value CS master's programs " "globally. This admission reflects his strong academic and research background." ) }, { "title": "Education: MSc Applied Engineering, Georgia Southern University", "category": "education", "text": ( "Arifur earned his MSc in Applied Engineering with a specialization in " "Advanced Manufacturing Engineering from Georgia Southern University, " "Statesboro GA. His thesis focused on acoustic sensing for railroad " "predictive maintenance. During his MSc he was a Graduate Research Assistant " "at the LANDTIE Research Lab under Professor Hossein Taheri. He was awarded " "the Gene Haas Foundation Manufacturing Engineering Scholarship for 2022-2023. " "His MSc research produced 7 peer-reviewed publications and 184+ citations." ) }, { "title": "Education: BSc Mechanical Engineering, CUET Bangladesh (2014)", "category": "education", "text": ( "Arifur earned his Bachelor of Science in Mechanical Engineering from " "Chittagong University of Engineering and Technology (CUET) in Bangladesh " "in 2014, graduating with a merit position of 35 out of 127 students. " "CUET is one of Bangladesh's premier engineering universities. His BS " "foundation in mechanical engineering underpins his later expertise in " "manufacturing systems, structural health monitoring, and industrial AI." ) }, # ── PAPERS 1-4 (existing) ───────────────────────────────────────────── { "title": "Paper 1: CNN-LSTM-SW for Railroad Anomaly Detection via DAS (Elsevier 2024)", "category": "research", "text": ( "Published in Green Energy and Intelligent Transportation, Elsevier 2024. " "DOI: 10.1016/j.geits.2024.100178. Authors: Rahman MA, Jamal S, Taheri H. " "The CNN-LSTM-SW model combines CNNs for spatial feature extraction, LSTMs " "for temporal learning, and a sliding window for misclassification correction. " "Validated on 4.16 km HTL loop DAS data from AAR/TTCI Pueblo CO. " "Results: 97% train position detection, ROC AUC AC1=1.00, NC=0.99, TP=0.97, AC2=0.95. " "Four classes: NC (Normal), TP (Train Position), AC1, AC2. " "SMOTE handles class imbalance. Combined T&FD features outperform TD-only and FD-only." ) }, { "title": "Paper 2: DAS Railroad CM with GRU/LSTM (SPIE 2024)", "category": "research", "text": ( "Published in Journal of Applied Remote Sensing, SPIE 2024. " "DOI: 10.1117/1.JRS.18.016512. Authors: Rahman MA, Kim J, Dababneh F, Taheri H. " "GRU model achieved 94% vs LSTM 93% for train presence detection using DAS signals. " "The iDAS system (Silixa) has gauge length 10m, sensing range 45km, up to 100kHz sampling. " "Average trend extraction preprocesses large noisy DAS data via rolling mean. " "DAS uses Rayleigh backscattering in fiber optic cables as distributed sensors." ) }, { "title": "Paper 3: Review of DAS Applications for Railroad CM (Elsevier MSSP 2023)", "category": "research", "text": ( "Published in Mechanical Systems and Signal Processing, Elsevier 2023. " "DOI: 10.1016/j.ymssp.2023.110881. Systematic review of distributed acoustic " "sensing applications for railroad condition monitoring. DAS challenges: " "terabytes of daily data, high environmental noise, class imbalance, real-time constraints. " "Deep learning (CNN, LSTM, GRU hybrids) consistently outperforms classical ML " "(SVM, KNN, Random Forest) on large DAS datasets. Widely cited review paper." ) }, { "title": "Paper 4: HMM-RL for WAAM Manufacturing (Springer 2026)", "category": "research", "text": ( "Under review at Springer 2026. Authors: Rahman MA et al. " "HMM-RL pipeline for Wire Arc Additive Manufacturing: Hidden Markov Model " "captures latent process states (stable deposition, thermal buildup, cooling) " "from temperature and current sensors. RL agent optimizes wire feed speed, " "travel speed, current, and gas flow to maximize material quality. " "Achieved 5% material utilization improvement on live WAAM datasets " "under Georgia-AIM grant at Georgia Tech." ) }, # ── PAPERS 5-7 (new) ────────────────────────────────────────────────── { "title": "Paper 5: AI-Guided Optimization of Polymer Film Synthesis (Springer 2026)", "category": "research", "text": ( "Under review at Springer 2026. Authors: Rahman MA et al. " "AI-guided optimization of polymer film synthesis using ML surrogates and " "multi-objective design. Applies machine learning surrogate models to replace " "expensive physical simulations in polymer manufacturing. Multi-objective " "optimization balances competing material properties (strength, flexibility, " "thermal stability). Part of the broader Georgia-AIM manufacturing AI initiative " "at Georgia Tech PIN program." ) }, { "title": "Paper 6: Structural Health Monitoring for Railroad Infrastructure", "category": "research", "text": ( "Published in ASME journal. Authors: Rahman MA, Taheri H et al. " "Structural health monitoring (SHM) for railroad infrastructure using " "sensor data and machine learning. Focuses on early detection of structural " "degradation in rail tracks, bridges, and related infrastructure. " "Combines vibration analysis, acoustic sensing, and ML-based pattern " "recognition for continuous automated monitoring. Part of the broader " "body of work from the LANDTIE Research Lab at Georgia Southern University." ) }, { "title": "Paper 7: Predictive Maintenance for Rail Systems Using ML", "category": "research", "text": ( "Published in ASME/Springer. Authors: Rahman MA, Taheri H et al. " "Machine learning approaches for predictive maintenance of rail systems. " "Covers anomaly detection on live HTL loop-MxV rail datasets from AAR/TTCI " "achieving 95% accuracy with reduced false inspection alarms. " "Developed real-time Python/SQL monitoring dashboards adopted by faculty " "and industry partners. Led data collection under AAR/TTCI and Georgia " "Southern University research grants." ) }, # ── CERTIFICATIONS ──────────────────────────────────────────────────── { "title": "Certifications & Professional Development", "category": "certifications", "text": ( "Arifur holds the following certifications: " "Google Cloud Data Analytics Certificate; " "Alteryx Designer Core Certification; " "Coursera Applied Machine Learning in Python (University of Michigan). " "Professional development includes: Oracle SQL Explorer; " "Udemy LLM Engineering; Udemy Google Cloud Professional Data Engineer; " "LinkedIn Learning Power BI; Udemy ML for Industry 4.0; " "Udemy Data Analyst Bootcamp; Google Generative AI Leader. " "These certifications span cloud platforms, ML engineering, data analytics, " "and generative AI — directly aligned with FAANG technical requirements." ) }, # ── TECHNICAL SKILLS ────────────────────────────────────────────────── { "title": "Technical Skills — Languages & ML/AI", "category": "skills", "text": ( "Programming languages: Python (primary), SQL, Java, MATLAB, C++. " "ML & AI frameworks: LLMs (GPT, BERT), TensorFlow, Hugging Face, " "Vertex AI, RAG pipelines, AutoML, LangChain, LangGraph. " "Data tools: Pandas, scikit-learn, Alteryx, NumPy, SciPy. " "Software engineering: Git, REST APIs, Agile methodology, Streamlit, Docker. " "Specialized ML: CNN, LSTM, GRU, Hidden Markov Models, Reinforcement Learning, " "Anomaly Detection, Predictive Maintenance, Time-Series Analysis, FAISS, " "SentenceTransformers, Signal Processing (FFT, STFT, wavelets)." ) }, { "title": "Technical Skills — Cloud, Visualization & Engineering Tools", "category": "skills", "text": ( "Cloud platforms: Google Cloud (BigQuery, Vertex AI, Cloud Functions), " "Oracle, AWS (S3, Lambda), Azure (VM). " "Data visualization: Power BI, Looker, Tableau, GIS mapping, Streamlit. " "Engineering software: AutoCAD, SolidWorks, PLC diagnostics, Ansys simulation. " "Areas of expertise: Machine Learning & AI, Reinforcement Learning, " "Generative AI & LLMs, Predictive Analytics & Anomaly Detection, " "MLOps & Model Deployment, Data Pipeline Automation, " "PLC Diagnostics & Troubleshooting, Asset & Structural Health Monitoring, " "Manufacturing & Transportation Optimization, Cross-Functional Collaboration." ) }, # ── AREAS OF EXPERTISE ──────────────────────────────────────────────── { "title": "Target Roles & Career Goals", "category": "profile", "text": ( "Arifur is open to roles in ML Engineering, AI/Data Science, Data Engineering, " "and AI Research — particularly in manufacturing, transportation, energy, " "and infrastructure intelligence. Target companies include Google, Microsoft, " "Intel, and other major tech companies. He brings a unique combination of " "deep domain expertise (railroad AI, manufacturing optimization) with " "production ML engineering skills (RAG pipelines, CNN-LSTM, MLOps). " "He is US work authorized with no sponsorship required, based in Atlanta GA. " "Starting Georgia Tech OMSCS (MS Computer Science) Fall 2026." ) }, ] chunks = [] for entry in entries: meta = { "title": entry["title"], "authors": "Md Arifur Rahman", "year": "2024", "source": entry["category"], "domain": entry["category"], "venue": entry.get("venue", ""), } chunks.append(DocumentChunk(text=entry["text"], metadata=meta)) return chunks