I am a researcher and data analyst focused on the intersection of Plant Genomics and Digital Phenotyping. My work bridges the gap between raw biological data and actionable agricultural insights.

• Genomics / TE Annotation: Comparative Genomics, Transposable Element (TE) Annotation, PFM Motif Analysis, De novo assembly (Hifiasm, Jellyfish), RagTag scaffolding, Prokka, BLAST+, LTR retrotransposon analysis, RITE DB validation.
• Data Science / Analytics: R (tidyverse, ggplot2, ANOVA, linear models), Python, Bash scripting, HPC (PBS/Slurm) workflows.
• AI / Software Engineering: Model Context Protocol (MCP), LLM function calling, REST API design, Git/GitHub, Docker reproducibility.
• Experimental / Wet Lab: CTAB DNA extraction, PCR, gel electrophoresis, microbial cultivation, spectrophotometry & bioassays.
• Engineering: Laboratory automation (Python GUIs) and Cloud-based sample tracking (MIT App Inventor).

• Experimental / Wet Lab: Recombinant protein production (Pichia pastoris expression), Gibson/NEBuilder Assembly, Tn5 transposon mutagenesis, CTAB & Miniprep DNA extraction, PCR/Colony-PCR, SDS-PAGE, Agarose Gel Electrophoresis, Spectrophotometry (NanoDrop).
• Bioinformatics & In Silico Cloning: Geneious Prime (plasmid mapping, Nanopore/Plasmidsaurus verification), BLAST+, R/Bioconductor, Slurm HPC.

• University of Arizona (BIO5 / Wing Lab): Comparative genomics of transposable elements in wild rice.
• MBZUAI (CBCRG Lab / UGRIP 2026): Ask JASPAR — LLM & MCP-driven regulatory genomics tools.
• Kozybayev Labs: Environmental biotechnology & biosensors.
• KAUST (Jesse Poland Lab): Research internship focusing on digital phenotyping and high-throughput field data analysis.

• Focus: Bioinformatic pipeline and visualization tools for investigating Transposable Element (TE) dynamics across Oryza CC/BBCC genomes.

• Tools: R, Python, Bash, HPC (UA Cluster), CyVerse.

• Natural-language interface and MCP server tools for querying transcription factor binding profiles from JASPAR.
• My Contribution: Designed the result-ranking layer, built pagination-aware retrieval (1,700+ records/query), engineered compare_matrices (Pearson correlation), and conducted benchmark parsing evaluations (doubling accuracy from 25% to ~54%).

• Focus: Eukaryotic genome reconstruction using PacBio HiFi reads.
• Tools: Hifiasm, Jellyfish, RagTag, Augustus.
• Key Skill: Scaffolding, k-mer profiling, and organelle sorting.
• Live Report: View Project Website

• Focus: Automated workflow for E. coli genome assembly.
• Tools: fastp, SPAdes, Prokka, QUAST.
• Key Skill: Automation & Genomic Annotation.

• Focus: Identifying significant genes in stress-response transcriptomes (LS vs HS).
• Tools: R, Tidyverse, ggplot2.
• Key Skill: Statistical hypothesis testing and biological visualization (Volcano Plots).

• Focus: Automated summarization of multi-trait field breeding trials.
• Tools: R, Functional Programming, dplyr.
• Key Skill: Data engineering and automated plot-level variability analysis.

• Focus: Reproducible R pipeline and interactive Shiny web dashboard for cleaning, QC filtering, and mixed-model analysis (LMM/BLUPs) of field trial data.
• Tools: R (tidyverse, lme4), R Shiny, Docker, Field Book CSV.
• Key Features: Automated dual-layer outlier detection (biological limits + IQR), spatial field layout visualization, and exportable summary tables for breeding research.

• Focus: Python desktop tools for routine lab calculations.
• Features: Tm calculation (Wallace Rule), DNA-to-RNA transcription.
• Key Skill: Python Software Development & UI Design.

• Focus: Cloud-based Android application for laboratory inventory.
• Features: Real-time data sync via CloudDB, item management for reagents/samples.
• Key Skill: Mobile Development (MIT App Inventor) & Cloud Integration.

• Focus: Large-scale sequence identification and hit validation.
• Tools: NCBI BLAST+, Bioconductor, R.
• Key Skill: Processing command-line output into statistical reports.

• Focus: Intensive curriculum for biological data analysis and inference.
• Topics: CLT simulations, ANOVA, Tukey HSD, and Linear Regression.
• Key Skill: Mathematical foundations and reproducible modeling.

• Bioinformatics: Bash Scripting, Conda, HPC, SRA-tools, K-mer Analysis.
• Development: Python (Tkinter), Git/GitHub, Mobile App Development (AIA).
• Domain: PCR Design, Genomic Annotation, Molecular Biology, Laboratory Automation.