# Fakharyar Khan > Software Engineer @ TheGuarantors Location: New York City Metropolitan Area, United States Profile: https://flows.cv/fakharyar πŸ” Computer Science Graduate Student | Minor in Math | Minor in Computer Science | Aspiring Software Engineer πŸ‘‹ Hi! I'm Fakharyar Khan, a graduate student at Cornell University pursuing a Master of Engineering in Computer Science with a keen interest in machine learning and backend development. My academic journey has equipped me with a solid foundation in Electrical Engineering, complemented by a minor in Computer Science and Math. πŸ’Ό Backend Proficiency: Adept in backend technologies such as PostgreSQL, NoSQL, and ORM libraries such as SQLAlchemy and JPA, I specialize in designing and implementing scalable, efficient, and secure software solutions. πŸ› οΈ Technical Skills: Excel in programming languages such as Python, Java, C# and C++. πŸ“ˆ Open to Opportunities: Currently exploring career opportunities in software engineering and machine learning. Excited about the prospect of contributing my skills and passion to a forward-thinking organization. ## Work Experience ### Software Engineer @ TheGuarantors Jan 2025 – Present | New York, New York, United States ### Software Engineer Intern @ Con Edison Jan 2023 – Jan 2025 | New York City Metropolitan Area πŸ’Ό Software Engineer Intern @ Con Edison (Jan 2023 – Present) New York, NY | Python, Java, SQL, LangChain, Outlook API, Flask, PostgreSQL, cron During my time at Con Edison, I drove key automation initiatives that streamlined internal operations and reduced manual overhead. Highlights include: πŸ”„ Mass Update Management System Built backend components for a scalable contact management system and dashboard that tracks the status of thousands of EMOPSYS customer accounts during the bi-annual four-month update cycle. πŸ€– LLM-Powered Mailing Agent Developed an intelligent email automation pipeline using LangChain and the Outlook API to send personalized contact update requests to customers, automatically parse responses, and update the database. Scheduled and orchestrated monthly email waves with cron, ensuring timely outreach while dynamically removing responders to prevent duplicate messages. Significantly improved communication efficiency and customer engagement through automation and NLP. 🐍 Automated Data Pipelines Designed and implemented Python-based automation scripts for internal data processing, eliminating repetitive workflows and saving the department over 450 hours of manual labor annually. ### Computer Science Instructor @ Ai Plus Learning Center Jan 2017 – Jan 2022 | New York, New York, United States As a dedicated Computer Science Instructor at the AI Plus Learning Center, a dynamic cram school for young students eager to delve into the world of computer science, I played a pivotal role in shaping the next generation of tech enthusiasts. Key contributions include: πŸ–₯️ Lab Session Facilitation: Conducted engaging lab sessions to bridge theoretical concepts with hands-on applications, empowering students to solve practical problems in the realm of computer science. πŸ’» Coding Guidance and Support: Provided personalized guidance on coding assignments, offering assistance in debugging code and troubleshooting errors. Ensured students developed a robust understanding of programming principles. πŸ‘©β€πŸ« Programming Languages Instruction: Led classes on Python, Netlogo, Java, and Object-Oriented Programming, fostering a comprehensive understanding of diverse programming languages and paradigms. ### Software Engineer Intern @ EmmyCo Jan 2021 – Jan 2021 | New York City Metropolitan Area At EmmyCo, a company revolutionizing patient care, I played a crucial role in ensuring the success of our mission to offer an Uber-like service, where we transported patients from hospitals to their homes when familial support was unavailable. Within this dynamic startup environment, I gained invaluable experience in diverse facets of software development and healthcare technology, notably excelling in: πŸ”„ Agile Development Practices: Embraced agile development methodologies to foster adaptability and responsiveness. Engaged in regular sprint planning, retrospectives, and daily stand-ups to enhance communication within the team and facilitate a rapid and iterative development cycle. πŸ“ˆ Performance Optimization: Utilized performance testing tools such as JMeter and Selenium to identify and address bottlenecks in the system, ensuring a seamless and efficient experience for users on our company website. Collaborated closely with the development team to implement optimizations and enhance overall platform performance. πŸ›‘οΈ Backend Unit & Integration Testing Improved software quality by implementing thorough unit and integration tests and identifying critical defects increasing code coverage by 30%. ### Research Intern @ University of Florida Jan 2019 – Jan 2019 | Gainesville, Florida, United States During my research internship at the University of Florida, I shadowed Dr. James Hamlin who does research on the synthesis of superconductive compounds under high pressure. Superconductivity, characterized by zero resistance at cryogenic temperatures, holds immense potential, particularly in creating power lines with no transmission loss. Yet, the impractical refrigeration costs have spurred a significant materials science effort to discover room-temperature superconductivity for more practical large-scale applications. My specific contributions included: πŸ” Modeling Superconductivity: Presently, the search for room-temperature superconductivity often relies on an inefficient trial-and-error process. A primary objective of my internship was to develop a regression and classification model that could predict superconductivity in compounds and the critical temperatures at which they become superconductive. The motivation behind this was to provide researchers with a valuable toolβ€”a preliminary filter to markedly reduce the pool of compounds requiring testing. For my regression model, I had used and implemented SISSO, a feature construction and selection algorithm originally developed in Fortran, in Python. Ultimately, my regression model didn't do as well as I had hoped but my classification model achieved an accuracy of roughly 73% which was surprisingly high given the size of the dataset I had to train on. πŸ“Š Data Curation: Curated a dataset from our database of superconductive compounds which was used to train the machine-learning models. ## Education ### Master of Engineering - MEng in Computer Science Cornell University ### Bachelor of Electrical Engineering in Electrical and Computer Engineering The Cooper Union for the Advancement of Science and Art ### Stuyvesant High School ## Contact & Social - LinkedIn: https://linkedin.com/in/fakharyar-khan-124582229 - GitHub: https://github.com/fkhan000 --- Source: https://flows.cv/fakharyar JSON Resume: https://flows.cv/fakharyar/resume.json Last updated: 2026-04-13