Asif Syed | ML Scientist Asif Syed | ML Scientist

About Me

I’m Md Asif Bin Syed, a Sr. Supply Chain Data Analyst at The Home Depot, the world’s leading home improvement retailer. I’m passionate about leveraging machine learning and data science to solve complex business problems and drive innovation in supply chain operations.

Professional Journey

Current Role: Sr. Supply Chain Data Analyst — The Home Depot, Atlanta, GA (Jan 2024 – Present)

  • Led a team of seven Data Scientists and Software Engineers to develop a SmartFulfill agent using offline RL, reducing on-time delivery failures by 4.5% ($6.5M retained revenue)
  • Conducted statistical analysis on 10M+ orders to identify key delivery drivers
  • Built an ML model forecasting on-time delivery with 84% accuracy, now being integrated into sourcing logic
  • Created dashboards to monitor ML performance and detect ~50% of on-time completion failures
  • Designed dashboard for “Ship from Best Location,” identifying a 500K order opportunity for faster shipment
  • Analyzed order split patterns to optimize split logic for leadership

Previous Experience

Supply Chain Data Analyst — The Home Depot, Atlanta, GA

  • Built SQL workbook + API validation for pallet counts; developed compliance dashboard, saving ~$2M annually
  • Optimized truck compliance dashboard load time from 226s → 2.56s (100x faster)
  • Developed Python-based “Control Tower” improving Truck Type Model accuracy
  • Co-developed carrier optimization model yielding potential $30M savings

Logistics Purchasing Co-op — Volvo Group, Greensboro, NC (Jan 2023 – Dec 2023)

  • Won Global Volvo Idea of the Month Award: saved $200K with AI-based logistics optimization
  • Reduced inbound CO₂ emissions by 500 tonnes with sustainable solutions
  • Led contingency analysis moving $12M annual business to backup carriers

Graduate Research/Teaching Assistant — West Virginia University (Aug 2021 – Dec 2022)

  • Led AI research for marine surveillance → Q1 journal publications
  • Authored NSF-sponsored study on forecasting cardiovascular disease from social media
  • Published IEEE papers on PCOS prediction, pediatric bone age, and satellite/debris detection

Executive Industrial Engineer — Vanguard Dresses Ltd., Bangladesh (Feb 2021 – Jun 2021)

  • Led Kaizen project, reducing rework by 5% across 700 workers
  • Built Power BI skill-metrics dashboard for 200 workers, improving line balancing

Education

  • M.S. Industrial Engineering — West Virginia University (2021–2023), GPA: 3.62
    Thesis: Spatio-Temporal Deep Learning Approaches for Addressing Track Association Problem using AIS Data

  • B.Sc. Industrial & Production Engineering — SUST (2016–2020), GPA: 3.61
    Thesis: Grey-Taguchi Approach for Optimizing FDM Process in Terms of Mechanical Properties & Dimensional Accuracy

Research & Publications

I have published extensively in top-tier journals and conferences, including Journal of Marine Science and Engineering, Sensors, IEEE conferences, and IISE. My research spans:

  • Marine AI & Surveillance: Deep learning approaches for vessel tracking using AIS data
  • Medical AI: PCOS diagnosis, pediatric bone age prediction, cardiovascular disease prediction
  • Computer Vision: Satellite and debris detection using YOLO
  • Federated Learning: Applications in manufacturing and Industry 5.0
  • NLP & Education: AI chatbot adoption analysis using PLS-SEM

View my complete publications →

Technical Expertise

Programming & Frameworks

  • Languages: Python, R, SQL, C
  • ML/DL Frameworks: Scikit-learn, Keras, TensorFlow, PyTorch
  • Data Analysis: MS Excel, Tableau, Power BI, Minitab

MLOps & DevOps

  • Containerization: Docker, Kubernetes
  • CI/CD: Jenkins, Git, GitHub Actions
  • Cloud Platforms: AWS, Azure ML, GCP, Vertex AI
  • MLOps Tools: MLflow, DVC, Weights & Biases

Databases & Web Development

  • Databases: BigQuery, MySQL, PostgreSQL
  • Web Development: HTML, CSS
  • Other Tools: SAP Ariba, SAP MDCS, SolidWorks, MS Project, MS Access, CPLEX

Awards & Recognition

  • Finalist, Home Depot Data Science Hackathon, 2024
  • Finalist, QCRE Data Challenge, 2023
  • Global Volvo Idea of the Month Award, 2023
  • University Scholarship for Outstanding Performance, SUST, 2020

Certifications

  • Microsoft Certified Data Analyst Associate (PL-300), 2023
  • Six Sigma Green Belt (IISE), 2022
  • MITx: Probability (6.431x), Supply Chain Design, Supply Chain Tools & Tech

Professional Affiliations

  • Member: IISE, INFORMS
  • Session Chair: INFORMS Annual Meeting, 2022
  • Vice President: WVU Bangladesh Student Association

Research Philosophy

My research philosophy centers on bridging the gap between academic theory and practical industry applications. I believe in developing AI solutions that not only advance scientific knowledge but also create tangible business value. My work at The Home Depot exemplifies this approach, where I’ve successfully translated complex machine learning algorithms into production systems that directly impact operational efficiency and customer satisfaction.

I’m particularly passionate about:

  • Applied AI: Taking cutting-edge research and making it work in real-world scenarios
  • Supply Chain Innovation: Using data science to optimize complex logistics networks
  • Interdisciplinary Collaboration: Working across domains to solve multifaceted problems
  • Mentorship: Sharing knowledge and helping others grow in their data science journey

For more information about my research and publications, please visit my publications page or contact me.

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