My primary research areas are the taxonomy and evolutionary biology of the arthropod class Diplopoda with a strong focus on molecular phylogenetics. I aim to elucidate the intricate phylogenetic connections within and among millipedes of various orders. Some of the molecular tools and techniques I have so far worked with include:
Trace Data Analysis: BioEdit
Sequence Preprocessing:
Alignment: MAFFT
Validation: MEGA
Model Selection: PartitionFinder
Phylogenetic Tree Inference:
Gene Tree Estimation: IQ-TREE, RAxML-NG, MrBayes
Species Tree Estimation: StarBeast
Species Delimitation:
Discovery: ABGD, ASAP, PTP, bPTP, mPTP, sGMYC, mGMYC, bGMYC
Validation: BPP, STACEY
Evaluation: LIMES
Molecular Dating: BEAST
Historical Biogeography: BioGeoBEARS
Diversification Analysis: LTT, LTST, BAMM/BAMMtools
Tree Editing: FigTree
Sequence Submission: BankIt
I also have a strong interest in Geographic Information Systems (GIS), given their wide range of applications across multiple fields, and I am skilled in analyzing spatial data and creating various types of maps using QGIS.
In addition to the aforementioned fields, I am deeply interested in some areas of data science including machine learning, deep learning, computer vision (CV) and natural language processing (NLP). I have interned as a data scientist at several companies and have proficiency in the following tools and technologies:
Programming Language: Python
Data Preprocessing: MS Excel, Pandas, NumPy
Data Visualization: Seaborn, Matplotlib, Plotly
Database Management: MySQL
Hyperparameter Optimization: Optuna, KerasTuner
Machine Learning: Scikit-learn
Deep Learning & Computer Vision: TensorFlow, Keras
Natural Language Processing: NLTK, spaCy, Gensim
Time Series Analysis: ARIMA and it's variants, Prophet
Big Data Handling: PySpark
Coding Platforms: Jupyter Notebook, Google Colab
Operating Systems: Windows, Linux (Ubuntu)