rezoansultan.com

Rezoan Sultan

Professional Summary

Doctoral researcher and Human-AI Interaction Engineer at Morgan State University, specializing in machine learning and Large Language Models (LLMs). Developed multiple LLM-powered applications, including adaptive academic advisor systems fine-tuned with Human Feedback Reinforcement Learning (HFRL) for personalized guidance. At the Data Engineering and Predictive Analytics (DEPA) lab, I focus on building scalable AI solutions that bridge NLP and human-centered design. My current work integrates real-time sensor networks and machine learning pipelines for landslide prediction. My research advances Human-AI collaboration, emphasizing practical AI applications for education, safety, and environmental risk management.

EXPERIENCE

05/2025- Current

Research Intern – Landslide Risk Monitoring & ML P

University Transportation Center | Pittsburg, PA

  •  Installing geotechnical and environmental sensors (moisture, rain gauge,
    water pressure transducers, wind speed, LiDAR) at a real-world highway
    site to enable real-time landslide risk monitoring.
  • Developing a Python-based machine learning pipeline integrating
    real-time sensor data with ML models for early landslide detection and
    forecasting.
  •  Processing 3D terrain data from the Realsee Galois M2 LiDAR camera,
    converting point clouds (PLY/E57) for slope deformation analysis and
    model training using Open3D and PyTorch.

09/2023 - Current

Research Assistant

Data Engineering and Predictive Analytics (DEPA) Research lab | Baltimore, USA

  • Developed multi-step agentic applications using Large Language Models
    (LLMs) to create personalized academic advisor systems for educational
    institutions. Utilized Human Feedback Reinforcement Learning (HFRL) to
    iteratively fine-tune GPT models, incorporating user preferences and
    interaction data to optimize alignment and response relevance. Focused on
    enhancing adaptability and contextual accuracy based on individual
    academic and career profiles.
  • Utilizing Large Language Models (LLMs) alongside time series analysis
    techniques to detect and analyze anomalous patterns in system behavior,
    enabling early identification of malicious activities and enhancing
    cybersecurity threat response.
  •  Worked as a TA (Teacher Assistant) with my research advisor, Dr. Kofi
    Nyarko, for the course ‘Machine Learning Applications’ (EEGR 565).

05/2024 - 07/2024

Graduate Mentor

CEAMLS Summer AI Research Institute | Baltimore, MD

  • Mentored and supported a team of diverse undergraduate scholars from different fields.
  • Provided expertise in leveraging OpenCV, YOLO, and Ultralytics to detect key traffic violations, such as jaywalking and red-light running, improving the accuracy and scalability of the solution.
  • Supervised the SQL database architecture to store, manage, and query video data.
  • Assisted in the preparation of graduate students for professional conferences and presentations.

03/2019 - 08/2021

Supply Chain Analyst

Navana LPG LTD | Dhaka, Bangladesh Supply Chain Analyst 03/2019- 08/2021

  • Streamlined inventory stock management by updating records through MS
    Excel and Oracle EBS. 
  • Projected future inventory requirements.
  • Employed Oracle EBS to develop reports and perform data analysis.
  • Applied data analytics for identifying and resolving supply chain concerns,
    resulting in improved performance.
  • Reported on supply chain KPIs to verify compliance with established standards.

Education

Expected in 12/2027

Doctor of Engineering in Electrical & Computer Engineering

Morgan State University | Baltimore, MD

06/2023

Master of Science in Information Technology

Washington University of Science & Technology | Alexandria, VA

12/2016

Bachelor of Science in Electrical & Electronic Engineering

American International University - Bangladesh | Dhaka, Bangladesh

Accomplishments/Awards

Graduate Research Poster Presenter Winner (Spring 2024) Presented a custom-built Large Language Model GPT project at the Spring 2024 Symposium, Morgan State University. Demonstrated the model's capabilities in providing personalized academic guidance by analyzing course materials and offering tailored suggestions for students. Link Here...

Skills

Python

Specialist

Excel, PowerPoint, Outlook

Specialist

PyTorch, TensorFlow

Specialist

KNIME

Specialist

Supervised & Unsupervised Learning

Specialist

SQL & MySQL

Specialist

Arduino

Specialist

Windows, Linux

Specialist

Regression, Classification

Specialist

Splunk

Specialist

Deep Learning

Specialist

OpenCV, YOLO, DeepSORT

Specialist

Tableau

Specialist

R

Specialist

Microsoft 365

Specialist

Arduino & Raspberry Pi

Specialist

CERTIFICATIONS

Introductory Data Analytics (Tableau) by National FinTech Center

Technical Support Fundamentals by Google

The Bits and Bytes of Computer Networking by Google

Operating Systems and you: Becoming a Power User by Google

Introductory Data Science by IBM

Cisco Certified Network Associate

Microsoft Azure Fundamentals

Rezoan Sultan

About Me

Doctoral researcher and Human-AI Interaction Engineer at Morgan State University, specializing in machine learning and Large Language Models (LLMs). Developed multiple LLM-powered applications, including adaptive academic advisor systems fine-tuned with Human Feedback Reinforcement Learning (HFRL) for personalized guidance. At the Data Engineering and Predictive Analytics (DEPA) lab, I focus on building scalable AI solutions that bridge NLP and human-centered design. My current work integrates real-time sensor networks and machine learning pipelines for landslide prediction. My research advances Human-AI collaboration, emphasizing practical AI applications for education, safety, and environmental risk management.

EXPERIENCE

05/2025- Current

Research Intern – Landslide Risk Monitoring & ML P

University Transportation Center | Pittsburg, PA

  • Installing geotechnical and environmental sensors (moisture, rain gauge,
    water pressure transducers, wind speed, LiDAR) at a real-world highway
    site to enable real-time landslide risk monitoring.
  • Developing a Python-based machine learning pipeline integrating
    real-time sensor data with ML models for early landslide detection and
    forecasting.
  • Processing 3D terrain data from the Realsee Galois M2 LiDAR camera,
    converting point clouds (PLY/E57) for slope deformation analysis and
    model training using Open3D and PyTorch.

09/2023- Current

Research Assistant

Data Engineering and Predictive Analytics (DEPA) Research lab | Baltimore, USA

  • Developed multi-step agentic applications using Large Language Models
    (LLMs) to create personalized academic advisor systems for educational
    institutions. Utilized Human Feedback Reinforcement Learning (HFRL) to
    iteratively fine-tune GPT models, incorporating user preferences and
    interaction data to optimize alignment and response relevance. Focused on
    enhancing adaptability and contextual accuracy based on individual
    academic and career profiles.
  • Utilizing Large Language Models (LLMs) alongside time series analysis
    techniques to detect and analyze anomalous patterns in system behavior,
    enabling early identification of malicious activities and enhancing
    cybersecurity threat response.
  • Worked as a TA (Teacher Assistant) with my research advisor, Dr. Kofi
    Nyarko, for the course ‘Machine Learning Applications’ (EEGR 565).

05/2024- 07/2024

Graduate Mentor

CEAMLS Summer AI Research Institute | Baltimore, MD

  • Mentored and supported a team of diverse undergraduate scholars from
    different fields.
  • Provided expertise in leveraging OpenCV, YOLO, and Ultralytics to detect
    key traffic violations, such as jaywalking and red-light running, improving the accuracy and scalability of the solution.
  • Supervised the SQL database architecture to store, manage, and query
    video data.
  • Assisted in the preparation of graduate students for professional
    conferences and presentations.

03/2019- 08/2021

Supply Chain Analyst

Navana LPG LTD | Dhaka, Bangladesh

  •  Streamlined inventory stock management by updating records through MS
    Excel and Oracle EBS.
  •  Projected future inventory requirements.
  • Employed Oracle EBS to develop reports and perform data analysis.
  •  Applied data analytics for identifying and resolving supply chain concerns,
    resulting in improved performance.
  •  Monitor KPIs for compliance with established guidelines and standards.

Education

Expected in 12/2027

Doctor of Engineering in Electrical & Computer Engineering

Morgan State University | Baltimore, MD

06/2023

Master of Science in Information Technology

Washington University of Science & Technology | Alexandria, VA

12/2016

Bachelor of Science in Electrical & Electronic Engineering

American International University - Bangladesh | Dhaka, Bangladesh

Accomplishments

Graduate Research Poster Presenter Winner (Spring 2024) Presented a custom-built Large Language Model GPT project at the Spring 2024 Symposium, Morgan State University. Demonstrated the model's capabilities in providing personalized academic guidance by analyzing course materials and offering tailored suggestions for students. Link Here...

Skills

Python

Specialist

Excel, PowerPoint, Outlook

Specialist

PyTorch, TensorFlow

Specialist

KNIME

Specialist

Supervised & Unsupervised Learning

Specialist

SQL & MySQL

Specialist

Arduino

Specialist

Windows, Linux

Specialist

Regression, Classification

Specialist

Splunk

Specialist

Deep Learning

Specialist

OpenCV, YOLO, DeepSORT

Specialist

Tableau

Specialist

R

Specialist

Microsoft 365

Specialist

Arduino & Raspberry Pi

Specialist

CERTIFICATIONS

Introductory Data Analytics (Tableau) by National FinTech Center

Intermediate Data Visualization Using Tableau: Bootcamp by Morgan State University

Building Generative AI-Powered Applications with Python by IBM

Technical Support Fundamentals by Google

The Bits and Bytes of Computer Networking by Google

Operating Systems and you: Becoming a Power User by Google

Microsoft Azure Fundamentals

Introductory Data Science by IBM

Rezoan Sultan

About Me

Doctoral researcher and Human-AI Interaction Engineer at Morgan State University, specializing in machine learning and Large Language Models (LLMs). Developed multiple LLM-powered applications, including adaptive academic advisor systems fine-tuned with Human Feedback Reinforcement Learning (HFRL) for personalized guidance. At the Data Engineering and Predictive Analytics (DEPA) lab, I focus on building scalable AI solutions that bridge NLP and human-centered design. My current work integrates real-time sensor networks and machine learning pipelines for landslide prediction. My research advances Human-AI collaboration, emphasizing practical AI applications for education, safety, and environmental risk management.

EXPERIENCE

05/2025- Current

Research Intern – Landslide Risk Monitoring & ML P

University Transportation Center | Pittsburg, PA

  • Installing geotechnical and environmental sensors (moisture, rain gauge,
    water pressure transducers, wind speed, LiDAR) at a real-world highway
    site to enable real-time landslide risk monitoring.
  • Developing a Python-based machine learning pipeline integrating
    real-time sensor data with ML models for early landslide detection and
    forecasting
  • Processing 3D terrain data from the Realsee Galois M2 LiDAR camera,
    converting point clouds (PLY/E57) for slope deformation analysis and
    model training using Open3D and PyTorch

09/2023- Current

Research Assistant

Data Engineering and Predictive Analytics (DEPA) Research lab | Baltimore, USA

  • Developed multi-step agentic applications using Large Language Models
    (LLMs) to create personalized academic advisor systems for educational
    institutions. Utilized Human Feedback Reinforcement Learning (HFRL) to
    iteratively fine-tune GPT models, incorporating user preferences and
    interaction data to optimize alignment and response relevance. Focused on
    enhancing adaptability and contextual accuracy based on individual
    academic and career profiles.
  • Utilizing Large Language Models (LLMs) alongside time series analysis
    techniques to detect and analyze anomalous patterns in system behavior,
    enabling early identification of malicious activities and enhancing
    cybersecurity threat response.
  • Worked as a TA (Teacher Assistant) with my research advisor, Dr. Kofi
    Nyarko, for the course ‘Machine Learning Applications’ (EEGR 565).

05/2024 - 07/2024

Graduate Mentor

CEAMLS Summer AI Research Institute | Baltimore, MD

  • Mentored and supported a team of diverse undergraduate scholars from different fields.
  • Provided expertise in leveraging OpenCV, YOLO, and Ultralytics to detect key traffic violations, such as jaywalking and red-light running, improving the accuracy and scalability of the solution.
  • Supervised the SQL database architecture to store, manage, and query video data.
  • Assisted in the preparation of graduate students for professional conferences and presentations.

03/2019 - 08/2021

Supply Chain Analyst

Navana LPG LTD | Dhaka, Bangladesh

  • Streamlined inventory stock management by updating records through MS Excel and Oracle EBS.
  • Projected future inventory requirements.
  • Employed Oracle EBS to develop reports and perform data analysis.
  • Professional Summary Skills Experience Applied data analytics for identifying and resolving supply chain concerns, resulting in improved performance.
  • Monitor KPIs for compliance with established guidelines and standards.

Education

Expected in 12/2027

Doctor of Engineering in Electrical & Computer Engineering

Morgan State University | Baltimore, MD

06/2023

Master of Science in Information Technology

Washington University of Science & Technology | Alexandria, VA

12/2016

Bachelor of Science in Electrical & Electronic Engineering

American International University - Bangladesh | Dhaka, Bangladesh

Accomplishments

Graduate Research Poster Presenter Winner (Spring 2024) Presented a custom-built Large Language Model GPT project at the Spring 2024 Symposium, Morgan State University. Demonstrated the model's capabilities in providing personalized academic guidance by analyzing course materials and offering tailored suggestions for students.

Link Here...

Skills

Python

Specialist

PyTorch, TensorFlow

Specialist

Supervised & Unsupervised Learning, Transfer Learning

Specialist

Regression, Classification, and Deep Learning

Specialist

OpenCV, YOLO, DeepSORT

Specialist

SQL & MySQL

Specialist

Tableau

Specialist

R

Specialist

KNIME

Specialist

MATLAB

Specialist

Microsoft 365

Specialist

Windows, Linux

Specialist

Arduino & Raspberry Pi

Specialist

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