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Entry-Level Software Engineer with Machine Learning, Web Development & Computer Vision expertise
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Motivated IT student with hands-on experience in Machine Learning, Web Development, and Computer Vision. Built real-world applications including a depression detection system and a full-stack job portal using the MERN stack. Passionate about creating impactful, user-focused tech solutions and eager to contribute to innovative engineering teams.
Datta Meghe College of Engineering, Airoli
Bachelor of Engineering · Information Technology
N/A – June 30, 2026
R.K. Talreja College of Science, Arts & Commerce
Higher Secondary Certificate · Science
N/A – May 31, 2021
Yoga Pose Recognition System
January 1, 2026 – June 1, 2026
Built a real-time pose detection system using OpenCV and MediaPipe to extract body keypoints from live video streams. Trained and deployed a classification model to identify yoga poses with corrective feedback, improving user form accuracy. Achieved reliable detection across varied lighting conditions by preprocessing video frames and normalizing keypoint coordinates.
Depression Detection Web Application
January 1, 2025 – June 1, 2025
Developed an ML-powered web application to predict depression risk based on behavioral and questionnaire-based inputs. Designed a structured data collection system, gathering responses across key psychological indicators for model training. Implemented and evaluated multiple classification models, selecting the highest-accuracy model for deployment.
Job Portal Website
January 1, 2025 – June 1, 2025
Built a full-stack job portal with role-based access for recruiters and applicants using the MERN stack. Implemented job posting, search with filters, and application tracking features to streamline recruiter-applicant interaction. Designed a responsive UI using React and Tailwind CSS, ensuring smooth experience across devices.
Android Developer Virtual Internship
AICTE Eduskills
January 1, 2024 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a diverse interest in web development, machine learning, and computer vision, indicating adaptability and a broad technical curiosity. The focus on user-focused solutions (e.g., yoga pose feedback, job portal) suggests an alignment with creating impactful products. The lack of professional experience makes it challenging to fully assess cultural fit in a team setting, but the project diversity and stated passion for innovation are positive indicators.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset and an ability to translate technical concepts into functional applications. The academic projects suggest a capacity for independent work and structured development. However, without actual work experience or psychometric test results, it's difficult to assess stress handling, team collaboration, or direct operational fit in a professional environment.