🚀 Welcome to my GitHub profile! I'm passionate about Large Language Models, Reinforcement Learning, Signal Processing, Autonomous Systems, Computer Vision, and AI-driven research. My work spans data science, machine learning, traffic safety, and computational perception. Here, you'll find a collection of my research, coursework, challenges, and projects.
🔎 For more details about my experience and expertise, feel free to check my Resume.
Explore my coursework, research projects, and challenge participations below.
- 🚀 COMS 576 – Motion Strategy Algorithms and Applications
- 🛠 ME 592 – Data Analytics and Machine Learning for Cyber-Physical Systems Applications
- 👁 COM S 575 – Computational Perception & Computer Vision
- 🤖 COM S 573 – Machine Learning
- 📊 COM S 574 – Intro to Machine Learning
- 🖥 COM S 572 – Artificial Intelligence
🔗 More Coursework and Projects: Complete List
👨🔬 Graduate Research at Iowa State University (Aug 2020 – Present)
🚀 My current research focuses on applying AI and machine learning to transportation safety systems, computational modeling, and video-based crash detection.
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Crash Data Analysis – Developing AI-based frameworks to analyze crash data, predict risks, and reduce fatality rates.
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Leveraging Video-LLMs for Crash Detection – Applying Large Language Models (LLMs) to generate real-time crash video descriptions and automated crash detection.
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Teaching & Course Development – Assisting faculty in designing machine learning and AI coursework while evaluating student performance.
Enhanced snowplow operations in Iowa using AI-based autonomous navigation to improve lane assistance and winter road safety.
- 📰 Featured In:
Applying Large Language Models (LLMs) to generate real-time crash video descriptions and automated crash detection.
🔗 Publication Link
Exploring change-point detection methods for temporal action localization in video analysis.
🔗 Publication Link
Engineered ADAS technology to enhance vehicle safety in extreme driving conditions, contributing to traffic accident prevention.
Developed deep learning models to accurately predict heart and respiratory rates, aiding health monitoring and biomedical research.
Applied Reinforcement Learning (RL) models to study biological cellular behavior.
🔗 Publication Link
Enhancing sidewalk detection with ensemble learning to improve accessibility and urban planning.
🔗 Publication Link
📍 Iowa State University | 🗓 Aug 2020 – Present
- Conducting AI-driven research in transportation, safety, and video-based crash detection.
- Developing crash analysis models, Video-LLMs for crash detection, and AI-enhanced urban planning tools.
- Assisting in teaching machine learning and AI coursework, and mentoring students in research projects.
📍 SoilSerdem, Ames, IA | 🗓 Jan 2024 – Dec 2024
- Developed a Soil Mapping Engine to provide personalized soil maps for growers/farmers.
- Optimized geospatial data processing for improved decision-making.
- Designed QGIS scripts for AWS integration, reducing hosting costs.
📍 Etalyc Inc, Ames, IA | 🗓 May 2021 – Jul 2021
- Built pedestrian safety models with machine learning to enhance urban planning.
- Created advanced analytics protocols to improve predictive capabilities.
- Delivered data-driven reports highlighting key trends for better decision-making.
📍 The University of Vermont, Burlington, VT | 🗓 Aug 2019 – May 2020
- Taught machine learning and deep learning concepts to over 100 students.
- Developed interactive teaching materials for improved engagement.
🎓 Ph.D., Computer Science (Expected Dec 2025)
📍 Iowa State University
🎓 M.S., Artificial Intelligence (Graduated Jan 2024)
📍 Iowa State University
🎓 B.Sc., Computer Science & Engineering (Graduated 2018)
📍 BRAC University
Here are some of my recent research papers:
- "Precise and Robust Sidewalk Detection: Leveraging Ensemble Learning to Surpass LLM Limitations in Urban Environments"
I. F. Shihab, S. R. Bhagat, A. Sharma – 2024 Link
- "Effects of sequence features on machine-learned enzyme classification fidelity"
S. Ferdous, I. F. Shihab, R. Chowdhury, N. Reuel – Biotechnology and Bioengineering, 2024 Link
For a complete list of my publications, visit my Google Scholar Profile.
💻 Programming & Development
Languages: Python, Java, SQL, C++, R, Go;
Web: FastAPI, Flask, Streamlit, React (Amateur);
Databases: MySQL, PostgreSQL, MongoDB, SQLite, Elasticsearch, Amazon Athena;
DevOps: AWS, Git, GitHub, Jenkins, Docker, Kubernetes, Terraform
🧠 Machine Learning & GenAI
Frameworks: PyTorch, Scikit-learn, Keras, ONNX Runtime;
LLMOps: Azure Databricks, LangChain, Ollama, TorchServe;
Vector DBs: Chroma, Faiss, Pinecone
⚙ Data Engineering
Big Data: Spark, PySpark, Hadoop;
Pipelines: ETL, AWS Data Pipeline, Apache Kafka;
Monitoring: Splunk, Datadog
👀 Computer Vision & Simulation
Tools: OpenCV, SUMO, Isaac Gym, CARLA, OpenAI Gym
🤖 Reinforcement Learning
Frameworks: Ray, RLlib, Stable Baselines3
📊 Data Visualization & GIS
Tools: Tableau, Matplotlib, Seaborn, Plotly, QGIS, ArcGIS;
Capabilities: Digital mapping, remote sensing, terrain modeling, spatial analytics
📈 Statistical Analysis
Tools: R Studio, MATLAB
🔬 QNN and QML
Frameworks: torchquantum, Qiskit, StrawberryFields, PennyLane
📩 Email: [email protected]
📩 Academic Email: [email protected]
📞 Mobile: +1-347-571-4757
🔗 LinkedIn: Ibne Farabi Shihab
🔗 GitHub: farabi1038