Software Engineer with CSMS Focus and ME Background

Rohan Jaiswal

Lubbock, Texas 806-***-**** ********@***.*** LinkedIn Github

SUMMARY

Software Engineer and Computer Science graduate student with a Mechanical Engineering background, experienced in building automation and backend solutions using Python, C++, Java, and SQL. Built projects including an RL-based feature selection framework and an AI-powered quiz generation platform using Flask and PHP. Seeking software engineering roles focused on scalable, reliable systems. EDUCATION

Texas Tech University

Master of Science, Computer Science (GPA: 3.6)

• Coursework: Neural Networks, Reinforcement Learning Shri Shankaracharya Institute of Professional Management and Technology Bachelor of Technology, Mechanical Engineering (GPA: 3.52)

• Coursework: Robotics, Numerical Analysis and Computer Programming PROFESSIONAL EXPERIENCE

Aug 2023 - May 2026

Jul 2018 - Jun 2022

Texas Tech University Software Engineer Graduate Assistant. Oct 2025 - Present

• Built secure REST-based MediaSite-Azure integrations using PHP, enabling seamless enterprise authentication & identity mapping.

• Developed custom WordPress plugins and backend services, reducing manual administrative workflows by ~40%.

• Optimized API handling and data persistence layers, improving performance and reducing failures by ~30%.

• Implement logging with Monolog, add input validation, and develop error-handling routines, achieving 90.9% data accuracy and increasing system reliability

• Collaborated with stakeholders to deliver Azure integrations that met security standards and were deployed on schedule, supporting reliable system operation Data Science Graduate Assistant. Jun 2025 - Oct 2025

• Leveraged Polars to accelerate data analysis by 50% compared to pandas, enabling faster business insights.

• Identified a 30% drop in seasonal demand, revealing reverse trends against expectations.

• Developed memory-efficient ETL pipelines using Python, reducing compute and storage resource usage by 40%.

• Created dashboards and reports with a 25% faster turnaround using Power BI and Excel.

• Ensured data quality and alignment through cross-functional collaboration, improving data reliability and consistency. Data Science Research Assistant Aug 2024 - Jun 2025

• Developed a structured dataset of ~198,000 cells using Excel and R, which served as the basis for analyzing AI technology acquisitions and enabled identification of strategic impacts across leading companies

• Led a team of 5 with faculty supervision to design and annotate the dataset, completing the project ahead of schedule.

• Analyzed 750+ qualitative sources using QDA Miner and Atlas.ti, enabling structured evaluation across multiple case studies.

• Applied NLP and regression techniques in Python and R, uncovering 10+ key factors driving successful AI adoption.

• Created visualizations using Matplotlib, improving stakeholder interpretability and reducing early analysis turnaround time by 40%.

• Prepared and cleaned datasets for public release and drafted a research paper now under peer review, using R and Pandas for analysis and GitHub for version control, which expanded the project's data accessibility for external researchers Tata Consultancy Services Assistant System Engineer Jul 2022 - Jun 2023

• Developed client-specific C++ applications in Visual Studio using Agile sprints, delivering features that met requirements and earned positive client feedback

• Worked on a YOLOv5-based vehicle recognition system, achieving 87% mAP on 5K+ images with enhanced detection accuracy.

• Analyzed enterprise marketing trends with Pandas and Matplotlib, creating visual reports that guided client strategy and improved campaign relevance

• Automated testing workflows and collaborated with cross-functional teams, resulting in scalable and maintainable solutions that improved efficiency. THESIS : Reinforcement Learning–Guided Hybrid Neural Framework for Sparse Feature Selection

• Developed RL-guided feature selection framework combining a learnable gating module with LSTM/Attention models for high dimensional financial and gene expression data.

• Conducted 10-seed experiments using stratified splits and evaluated models using F1, Accuracy, RMSE, MAE, and R .

• Achieved improved classification performance and reduced feature redundancy through sparsity-controlled feature selection. PROJECTS

AI-Driven Quiz Application Aug 2024 - Dec 2024

• Developed an AI-powered quiz generator by integrating Flask (Python), PHP, and the Gemini AI model.

• Automated quiz creation from lecture videos, reducing manual effort by over 80% and enabling real-time performance tracking for 50+ students. Reinforcement Learning: Q-Learning & SARSA Oct 2024

• Implemented Q-Learning and SARSA in a 10 10 maze environment for path optimization.

• Improved policy convergence near goal states by 40% through iterative value updates.

• Visualized learning behavior and state values using Matplotlib for performance analysis. TECHNICAL SKILLS

• Programming/Databases: C++, Python, Java, C, MySQL, PostgreSQL, R Language

• Data Visualization: Matplotlib, Seaborn, Tableau, Power BI

• Big Data & Cloud: AWS, Kubernetes

• Data Science & AI: Text Analysis, Reinforcement Learning, Data Modelling, Statistical Analysis, Machine Learning, Neural Networks, Regression Analysis, Time Series Analysis, Natural Language Processing, Model Interpretability

• Software & Development Tools: GitHub, Excel, Anaconda, Visual Studio

• Frameworks: TensorFlow, PyTorch, Scikit-Learn, Keras, Flask, OpenCV, NumPy, Pandas

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