Sujal S.

About

Passionate software engineer with a flair for solving complex problems, especially in collaborative settings. Enthusiastic about systems programming, algorithm design, and the intersections of finance and biotech with software. I value environments that foster intellectual curiosity and prioritize happiness and personal growth. Currently evolving as a graduate student at Northeastern University while continuing to contribute to innovative projects through teaching, research, and software development.

Experience

• Graduate Teaching Assistant · Northeastern University01-01-2025 – 08-01-2025

  Guided graduate students in designing and deploying a full-stack, serverless application on AWS, utilizing CDK, Lambda, DynamoDB, EC2, and S3 to deliver a production-ready project. Algorithms: Conducted weekly recitations for 30 graduate students on advanced topics, including graph theory and dynamic programming, introducing detailed solution keys to clarify complex problem-solving strategies.

• Teaching Assistant- CSE 331 Algorithm and Complexity · University at Buffalo02-01-2023 – 05-01-2024

  Instructed 600+ students on core coding and algorithmic concepts in Python and C++, refining proficiency in data structures and design patterns. Coordinated collaboration among 10+ teaching assistants, 2 professors, and students to maintain a productive learning environment. Developed personalized learning strategies for over 300 students, focusing on dynamic programming, graph theory, and NP-completeness topics to enhance comprehension and engagement.

• Peer Mentor · University at Buffalo08-01-2022 – 05-01-2024

  Actively mentoring 6 first-year undergraduate students through their transition to university life and studies in the Computer Science & Engineering program. Providing personalized mentorship, assisting students with course selection, scheduling, study techniques, and access to resources to facilitate academic success. Cultivating a supportive community among students by fostering open communication and collaboration, promoting a conducive learning environment.

• SEAS Student Assistant · University at Buffalo01-01-2022 – 01-01-2024

  Managed phone inquiries and welcomed visitors at the academic center, ensuring efficient triaging of requests and accurate data entry. Assisted students in scheduling academic advising appointments, providing crucial support for their educational journey. Engaged with prospective students and parents, facilitating tours, open houses, and special outreach events to showcase the opportunities within the academic program.

• Tutor · University at Buffalo10-01-2021 – 05-01-2022

  Provided tailored tutoring sessions to 3 athletes, focusing on Introductory Computer Science, Mathematics, and Physics courses. Developed personalized learning techniques to cultivate effective study habits and enhance coding proficiency among athletes.

• Research Assistant · Buffalo Neuroimaging Analysis Centre (BNAC)04-01-2022 – 01-01-2023

  Led the development of an autonomous MRI scan annotation and upload system on XNAT, boosting collaboration and efficiency in medical imaging data sharing. Developed a scan classifier to convert DICOM scans to NIfTI format, simplifying data handling and improving workflow efficiency. Led the structured processing of NIfTI formatted scans, conducting extensive statistical analysis to fuel the development of a predictive model for brain diseases. Leveraged multiple machine learning algorithms to achieve accurate predictions based on MRI scan data, contributing to advancements in medical research and diagnosis.

• Research Assistant · xLab- University at Buffalo02-01-2022 – 08-01-2022

  Developed a nationality prediction application in an experiential learning project, leveraging Natural Language Processing (NLP) and Pattern Recognition techniques on a 1 million-entry dataset. Enhanced prediction accuracy from 6% to 70% using Machine Learning (ML), AI, NLP, and deep learning methods such as BERT, GRU, and RNN, validated through thorough data visualization. Implemented MapReduce for distributed computing and data preprocessing, optimizing performance and scalability to handle large datasets, informed by in-depth statistical analysis.

Education

• Northeastern UniversityMaster of Science - MS, Computer Science
• University at BuffaloBachelor of Science - BS, Mathematics and Computer Science

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