Honors CS @ Virginia State University (’26) Machine Learning • Cybersecurity/DFIR • Applied Research
I turn messy, real‑world data into secure, usable tools. My recent work spans SVM‑based neutron event classification, LSTM/XGBoost‑powered climate→yield forecasting, geospatial urban heat analytics in R, and DFIR workflows with Autopsy/FTK. I ship end‑to‑end: data engineering → modeling → visualization → deployment—with a bias for reproducibility and clear communication.
- 🎯 Focus: Applied ML (time series, tabular), secure systems, digital forensics
- 🧪 Method: Clean code, versioned experiments, meaningful visualizations
- 💬 Impact: Translate technical results for non‑technical decision‑makers
Modeling • Forecasting • Analyzing • Securing
- Inclusive AI Apps (Gestura: Android/Kotlin ASL data collection & assistive comms)
- Neutron Event Detection (SVM classification + clustering workflows)
- Climate→Yield Forecasting (USDA + WRF‑HRRR features via LSTM/XGBoost)
- Urban Heat Island Analytics (R + geospatial pipelines for Petersburg, VA)
- Cybersecurity & Forensics (Wireshark packet analysis; Autopsy/FTK triage)
- MS‑CC Undergraduate Summer Research Symposium (2025) — Presented climate‑driven yield prediction findings.
- MS‑CC Undergraduate Summer Research Internship — 10‑week NSF‑funded program (Fisk & Meharry). RF/XGBoost/LSTM for crop yield under climate stress.
- VSU Data Science for the Public Good (DSPG) — Urban Heat analysis in Petersburg, VA; R² ≈ 0.60 negative correlation between tree cover and heat index.
- Savannah River Environmental Sciences Field Station (SRESFS) — Cyber risk assessments, VLAN network design (Cisco Packet Tracer), DFIR labs.
- Languages: Python • R • Kotlin • Java • C++ • SQL • HTML/CSS/JS
- ML/DS: scikit‑learn • XGBoost • TensorFlow/PyTorch (LSTM/TFLite) • Pandas • NumPy
- Viz: Matplotlib • Plotly • ggplot2 • R Shiny
- Cyber/Net: Wireshark • Cisco Packet Tracer • Autopsy • FTK Imager
- Platforms/Dev: Docker • Git/GitHub • Flask • Firebase • Android Studio • FastAPI
| Project | What it does |
|---|---|
| Malware Analysis System | Multi‑node Docker pipeline + VirusTotal integration to analyze samples in a sandbox and return execution logs & scan results. |
| Tech: Python • Docker • FastAPI • VT API | |
| Repo: https://github.com/Rmot1202/malware-triage-pipeline.git | |
| Climate Yield Predictor | Merges USDA yields (2017–2022) with WRF‑HRRR simulations; Random Forest/XGBoost/LSTM models and evaluation suite. |
| Tech: Python • Pandas • XGBoost • LSTM | |
| Results https://gamma.app/docs/Evaluating-Climate-Change-Effects-on-Agricultural-Yield-Using-Dee-0nfr274wz1qkfa7 | |
| AI Food Navigation (Flask) | Website with api food items. Chatbot UX that helps users explore meals and submit feedback. |
| Tech: Flask • SQLite • Jinja | |
| Live: https://rmot1202.pythonanywhere.com/ | |
| Gestura | Companion app for ASL data collection and translation; Firebase auth, contributor dashboard, model update workflow. |
| Tech: Python • CNN • Kotlin • FireBase | |
| Repo: https://github.com/Gestura-Senior-Project/Gestura.git |
Neutron Event Classification (SVM)
- ~95% accuracy on scintillator datasets; tuned for F1 ≈ 0.93 and AUC ≈ 0.96.
Deep Learning for Climate→Yield
- Integrated USDA (2017–2022) with WRF‑HRRR features; LSTM R² > 0.93, reduced RMSE vs. classical baselines.
Urban Heat: Petersburg, VA
- Negative correlation (R² ≈ 0.60) between tree cover and heat distribution; policy‑oriented insights for environmental justice.
Cyber Risk & Forensics
- Segmented VLAN designs + firewall/IDS considerations; disk/memory/log analysis with Autopsy and FTK Imager.
- VSU Tour Guide: Led 50+ tours engaging 1,000+ prospective students.
- Apple Pathways Scholar (2024): Training in algorithms, software practices, and professional skills.
- DEA Mentorship Program (2023): Workplace professionalism, ethics, and teamwork.
- Digital Navigator (2025): Empowering residents to get online, use their devices confidently, and access work, school, and healthcare.
- New‑Grad 2026: Data Science • ML Engineering • Cybersecurity/DFIR
- Research collaborations: time series, remote sensing, geospatial ML
If you think I’d be a fit, let’s connect.
“Striving to innovate where data meets impact.”