Machine Learning Engineer

Navya Tippananapalya Ramesh

*********@*****.*** +1-517-***-****, San Diego, California www.linkedin.com/in/navya-ramesh13 CAREER HISTORY

Model Medicines California, USA

Machine Learning Engineer 06/2021-06/2024

• Developed and deployed advanced data processing algorithms, enhancing drug discovery platform efficiency by 80% and improving accuracy in potential drug candidate identification.

• Led GAN model projects with transformer networks and attention mechanisms, increasing compound discovery efficiency by 75% and patented newly generated molecules.

• Collaborated and designed a Graph Neural Network (GNN) architecture with explainability module, delivering 92% classification accuracy across datasets and co-authored a research paper for bioRxiv submission leading to 22% hit rate.

• Created a web scraping pipeline with Natural Language Processing (NLP) for data curation and data acquisition, enhancing model prediction post-processing speed by 10x over manual methods.

• Authored groundbreaking white paper on novel graph mining techniques, cutting down false positive compound identification by 85% and MCC of 0.71.

• Analyzed binding pockets and sites on target proteins to assess drug efficacy, using PyMOL for visualization, which informed modifications to chemical structures, improving binding affinity by 15% compared to the baseline models.

• Executed a proof-of-concept model for classifying the protein-molecular interactions between protein-ligand complex with accuracy of 81% and F1 score of 0.78.

Michigan State University Michigan, USA

Graduate Research Assistant- Woldring Lab 04/2020-07/2020

• Led the development and implementation of an advanced product pipeline utilizing Transformer models with attention mechanism to create new chemical entities; achieved a 75% improvement in compound novelty.

• Implemented state of art prediction model to quantify the rigidity strengthening of docking with 0.82 Pearson coefficient.

• Designed a library for cancer cell detection proteins using Machine learning algorithms like KNN, Random Forest had accuracy of 82% for prediction of binding affinity for test datasets. Larsen & Toubro Infotech Bengaluru, India

Associate Software Engineer 10/2017-07/2019

• Led data-driven risk assessments and application development projects, achieving a 25% reduction in project risks and a 85% increase in client satisfaction through the delivery of high-quality services.

• Collaborated on developing a code review tool with 90% accuracy to ensure adherence to coding standards in SAP projects.

• Analyzed and resolved 50+ ERP system issues, enhancing production system reliability through SQL . Projects:

• Advanced Diffusion Models for Drug Discovery: Developed diffusion models, improving structural prediction accuracy by 82%, enhancing drug candidate identification through generative AI.

• Adapted a pre-trained LLM and fine-tuned it to accurately predict specific chemical ADMET properties, such as solubility, toxicity, or reactivity, of the compounds based on their molecular structures. SKILLS

• Programming Languages Python, MATLAB, SQL, SAP-ABAP, C, C++, Linux, OOPS, Data Structures

• Framework Keras, Pytorch, TensorFlow, AWS

• Area of Interest Data Scientist, Machine Learning, Cheminformatics, Computational Science, Image Processing, Artificial Intelligence, NLP, LLM-fine tuning, Diffusion Models, Generative AI EDUCATION

Michigan State University

Master of Science in Electrical and Computer Engineering Course work: Machine Learning, Deep Learning, Pattern Recognition and Analysis, Natural Language Processing PES University

Bachelor’s in engineering in Electronics and Communication Engineering Course work: Robotics, Communication, Image Processing, Artificial Neural networks APPRECIATION/AWARDS

• Poster presentation for AICHE for the project, protein engineering highlighted by deep learning.

• Represented Michigan State University at Annual SAE autonomous driving workshop.

• Organized the electronic design challenge with 60 teams participating in it at PES university.

• Awarded with First place at Electronic Design challenge, a 24-hours Hackathon.

• Awarded the innovative idea at 24-hour Hackathon for Agricultural Autonomous color sensing Robot.

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