Aditya Elayavalli
Computational Scientists Co-op @Unravel Biosciences
Signup · Get unlimited contacts
WORK HISTORY
Computational Scientists Co-op @Unravel Biosciences
Boston, MA, US
Develop and test efficient algorithms to improve and streamline drug prediction engine.Assist in porting drug prediction engine to a fully automated cloud-based programConduct cross-disease informatics and drug prediction studies using public and proprietary RNAseq and proteomics datasetsDeveloped a NN model using TensorFlow and Scikit-Learn for breast cancer diagnosis, implementing Stratified K-Fold crossvalidation, feature scaling, and dropout regularization to achieve high accuracy and AUROC scores.
EDUCATION
Northeastern University
Master of Science - MS, Computer Science
Virginia Tech
Bachelor of Science - BS, Biological and Biomedical Sciences
Northeastern University
Master of Science - MS, Bioinformatics
ABOUT ADITYA ELAYAVALLI
Hi everyone! I recently graduated from Northeastern University with a masters in Bioinformatics. I\'m seeking a new grad role and would appreciate your support. If you hear of any opportunities or have new connection recommendations please send me a message or comment below. I\'d love to connect!#OpenToWork About me & what I\'m looking for: I\'m looking for Computational Scientist, Bioinformatics Scientist, Data Scientist, or Machine Learning Engineer roles in biotech/pharma. I am also open to research positions in drug discovery and development. I\'m open to on-site/hybrid/remote roles anywhere in the United States and can start any time. I\'m a results-driven Computational Scientist with experience at Unravel Biosciences, where I\'ve worked on drug prediction engines, pipeline optimization, and machine learning models for disease diagnosis. I have a strong background in bioinformatics and data analytics, with hands-on experience in both academic research and industry applications. My skills include: Computational & Machine Learning: Python, R, TensorFlow, PyTorch, Scikit-Learn, machine learning algorithms (Naive Bayes, Logistic Regression, Decision Trees, Random Forest, Neural Networks), statistical modeling, algorithm development, hyperparameter tuning, cross-validation techniques. Bioinformatics & Genomics: RNA-seq analysis, Nextflow pipeline development, BioPython, Bioconductor, phylogenetic analysis, sequence similarity networks, ORF identification, genomic data analysis, BLAST, UniProt, GEO, NCBI databases. Data Analysis & Visualization: NumPy, Matplotlib, data cleaning and transformation, PCA, correlation analysis, ROC curve analysis, statistical analysis, CRISP-DM methodology. Cloud & Infrastructure: AWS, GCP, SQL database optimization, automated cloud-based pipelines, unit testing. Technical Tools: Kallisto, FastQC, CRISPR analysis, proteomics data analysis, cross-disease informatics. Research Experience: Drug discovery and prediction, breast cancer diagnosis models, photoenzyme research, pharmaceutical synthesis research. Education: MS in Bioinformatics (Data Analytics concentration) at Northeastern University (graduated May 2025), BS in Biological Sciences from Virginia Tech. Github: https://github.com/adihusky99
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.