Machine Learning Computer Science

KESHAVAN SESHADRI

New York, NY +1-201-***-**** ad5w83@r.postjobfree.com

www.linkedin.com/in/keshavan-seshadri www.github.com/K7S3 EDUCATION

Cornell University, New York, NY Aug 2023 – May 2024 Master of Engineering in Computer Science GPA: 3.91/4.0 Relevant Coursework: NLP, CV, Machine Learning Engineering, VR/AR, Algorithms, Building Entrepreneurial Ventures, Startup Studio International Institute of Information Technology, Hyderabad, India Aug 2017 – Jul 2023 Bachelor of Technology (Honours) in Computer Science and Master of Science by Research (Thesis) in Computational Natural Sciences GPA: 8.15/10.0 Relevant Coursework: Optimization Methods, Data Analytics, Distributed Systems, Statistical Methods in AI (Artificial Intelligence) TECHNICAL SKILLS

Languages: C++, Python, C, JavaScript, Java, C#; Machine Learning: Pytorch, Keras, Numpy, Scipy, Pandas; Full Stack: React, Flask, Django, Fast API, Ruby, Docker, K8s; Others: AWS, Unity, OpenGL, WebGL, LaTeX, SQL, Git, Linux; ENTREPRENEURSHIP

Synergii, Technical Founder, New York, NY (https://synergii.org/) Nov 2023 – Present

● Built an innovative grant discovery and application tool from the ground up using Retrieval-Augmented Generation

(RAG), GPT-4, BERT, Docker, AWS App Runner, RDS, Cognito, EC2, GitHub Actions CI/CD, Flask, and React.

● Designed in Figma and developed the MVP (Minimum Viable Product) from 0 to 1, integrating public datasets to capture a $34 billion market opportunity with targeted early revenue projections of $85 million.

● Gained significant traction with a growing user base and potential early customers, including nonprofits, entrepreneurs, and SMBs, and interviewed with accelerators. Secured a spot in the Cornell Johnson Summer Startup Accelerator. Assist, Technical Co-founder, Hyderabad, IN Aug 2020 – Feb 2021

● Created an e-learning app prototype using GPT-2 transformer to enhance memory retention for exam-preparing students.

EXPERIENCE

BrowserStack, Software Engineer, Mumbai (Remote), IN Jul 2022 – Dec 2022

● Updated test frameworks (Playwright, Puppeteer, Cypress) on AWS EC2 remote machines for enhanced functionality.

● Improved product stability and reliability by debugging and improving performance, using Node.js, Python, Ruby on Rails. Couture.AI, Full-Stack AI Developer Intern, Bangalore (Remote), IN Sep 2021 – Nov 2021

● Created GUI platform for training ResNet, Inception, and Deep Speech models with Docker, Kubernetes, and Django.

● Engineered AI platform for news video upload, flagging Violent and NSFW content, and obtaining censored versions. PROJECTS

Mini Torch – Cornell University, NY Aug 2023 – Dec 2023

• Completed the Mini Torch project, a Python-based educational library for deep learning, encompassing fundamentals, ML (Machine Learning) basics, auto-diff, tensor operations, efficiency, and networks, ensuring Torch code compatibility. Center for Computational Natural Sciences and Bioinformatics, Graduate Researcher, Hyderabad, IN May 2019 – Jul 2023

● Researched in computer-aided drug design, using all-atom molecular dynamics simulations to reveal metastable states in drug binding to G-Protein Coupled Receptors (GPCRs) through Potential of Mean Force (PMF) and K-Means Clustering.

● Utilized correlation analyses and machine learning regression (Linear Regression, Decision Trees, Random Forest, XGBoost, K Nearest Neighbours) to find crucial residues, helping automated ligand dynamics exploration. Google Summer of Code, Remote (Pittsburgh), US (Active Learning Environment in 3Dmol.js) May 2019 – Aug 2019

• Extended 3DMol.js for clicker-based active learning and Flask server for interactive 3D molecule viewing, synchronized state across 1000s of users via web sockets with minimal latency. Virtual Labs, Research Assistant, Hyderabad, IN May 2018 – Nov 2018

• Developed a research-driven gamified e-learning software on data structures and algorithms using JavaScript libraries and empowered over 200 students from under-represented colleges, preparing them for web development roles in the industry.

PUBLICATIONS

• Keshavan Seshadri, Marimuthu Krishnan; Molecular Dynamics and Machine Learning Study of Adrenaline Dynamics in the Binding Pocket of GPCR, Journal of Chemical Information and Modeling, Jul 2023 DOI: 10.1021/acs.jcim.3c00401

• Keshavan Seshadri, Peng Liu, David Ryan Koes; The 3Dmol.js learning environment: A classroom response system for 3D chemical structures. Journal of Chemical Education, Aug 2020. DOI: 10.1021/acs.jchemed.0c00579

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