Jumana Jouhar
A Computer Science graduate passionate about system implementation, driving quality assurance, and exploring intelligent systems.
Core Focus Areas
About Me
Computer Science and Engineering graduate from Saintgits College of Engineering with a Minor in Robotics and Automation. My background spans developing and testing technical solutions and handling data workflows across startups like Ailytics, dynamic banking environments like DBS, and research with National Chung Cheng University, with notable achievements including being named Winner of the Intel Unnati Industrial Training (Summer 2023).
Open to diverse technology roles that leverage my adaptability, problem-solving skills, and collaborative mindset to contribute to impactful initiatives and grow within a forward-thinking organization.
Work Experience
A history of professional roles, technical internships, and research experience.
DBS Bank
Production Support Trainee, Group Technology · Singapore
- Performed System Integration Testing (SIT) and User Acceptance Testing (UAT) during ATM switch migration for ATM, ATM+, BTM, and BTM+ applications by preparing test data, analyzing backend logs across legacy and new systems, documenting test outcomes, developing technical documentation in Confluence, and tracking defects via Jira.
- Supported Knowledge Base (KB) initiative and application rollout by onboarding multiple Group Technology (Applications) teams onto KB Hub and Claude Code, creating user guides, conducting user demos, tracking team progress to completion, and supporting UAT execution.
- Supported critical Change Requests (CRs) and Disaster Recovery (DR) activities during scheduled maintenance windows by coordinating activities, tracking progress, and assisting teams throughout planned system changes across DBS applications.
Ailytics
Data Annotation Specialist Intern · Singapore
- Collected, preprocessed, annotated, and validated 6,000+ images and test videos from existing IP camera infrastructure across multiple industrial safety and operational scenarios for custom YOLO-based object detection models using Python and LabelMe, supporting AI-powered video analytics within Agile sprint cycles.
- Developed scripts and applied data engineering best practices to improve data quality and workflow efficiency.
- Supported project documentation and participated in Agile activities including daily stand-ups, sprint planning, retrospectives, and team syncs to align with cross-functional teams.
National Chung Cheng University
Research Intern (TEEP Scholarship Program) · Chiayi, Taiwan
- Conducted research on Hyperspectral Imaging and its integration with AI and IoT for sustainable smart city applications, reviewing 150+ academic papers.
- Co-authored MDPI journal manuscripts (MDPI Technologies & MDPI Smart Cities) through literature reviews, conceptual frameworks, graphical abstracts, and manuscript editing.
- Delivered weekly technical presentations to supervisors and peers, earning an 'Excellent' evaluation grade along with a performance bonus.
Intel Corporation
Intel Unnati Industrial Trainee · Remote / India
- Developed an NLP-based business contract validation platform to classify content within contract clauses and highlight contract deviations from templates.
- Designed an interactive UI with dynamic views for multi-format document upload, deviation visualization, and clause display, ensuring seamless end-to-end user experience.
- Co-authored a technical report outlining system architecture and potential enhancements.
Intel Corporation
Intel Unnati Industrial Trainee · Remote / India
- Secured 1st Place at Intel Unnati Industrial Training 2023 by implementing a high-performance ML pipeline for fake news detection using Python and scikit-learn.
- Engineered preprocessing workflows including stopword removal, lemmatization, and TF-IDF, evaluating six classifiers and selecting XGBoost as top performer.
- Improved logistic regression training speed by 1.8x using Intel® Extension for Scikit-learn, leading to a peer-reviewed publication in Procedia Computer Science.
Featured Projects
A showcase of software, data and AI/ML projects I have worked on.
Digital Forensics Investigation in Vehicle Accident Cases
Developed an end-to-end blockchain platform integrating React, Node.js, Firebase, Pinata IPFS, and smart contracts via Ganache and Truffle for tamper-proof crash data integrity, enhanced with Deepseek LLM for automated forensic reporting.
Day/Night Photo Classification
Classified 1,850+ images using OpenCV processing and MobileNetV2, incorporating OCR timestamp extraction for day and night categorization.
Research Publications
Peer-reviewed articles and conference proceedings on hyperspectral imaging and machine learning.
Modern Trends and Recent Applications of Hyperspectral Imaging: A Review
Technologies (MDPI)
A comprehensive review highlighting cross-disciplinary applications of hyperspectral imaging across medicine, agriculture, and industry.
Advancing Urban Development: Applications of Hyperspectral Imaging in Smart City Innovations
Smart Cities (MDPI)
An open-access review exploring how hyperspectral imaging enhances smart city applications such as environmental monitoring.
Fake News Detection Using Python and Machine Learning
Procedia Computer Science (Elsevier)
Research exploring machine learning models to combat misinformation through data preprocessing, model training, and evaluation.
Get In Touch
Send a message regarding any technical opportunities.