Open to opportunities

Lasya priya Gunishetty

@lasyapriyagunishetty

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Aspiring computer scientist with expertise in deep learning and full-stack development.

India

Message

What I'm looking for

I am seeking opportunities that allow me to apply my technical skills in a collaborative environment, focusing on innovative projects that drive meaningful impact.

I am an undergraduate student pursuing a B.Tech in Computer Science & Engineering at SR University, where I have developed a strong foundation in both theoretical and practical aspects of computer science. My academic journey has been marked by a commitment to excellence, as evidenced by my CPI of 7.01 and my active participation in various projects that leverage cutting-edge technologies.

One of my notable projects involved creating an EEG signal classification system using CSP-LDA-LSTM, achieving an impressive 95% accuracy. Additionally, I developed a deep learning-based web system for kidney disease classification, utilizing CNN and achieving up to 99.5% accuracy. These experiences have not only honed my technical skills but also ignited my passion for solving real-world problems through technology.

Beyond academics, I have gained practical experience through industrial training in Java Full-Stack Development, where I learned essential frontend and backend technologies. My extracurricular achievements, including winning a debate competition and receiving a certification in dance, reflect my diverse interests and ability to excel in various domains.

Experience

Work history, roles, and key accomplishments

Brainwave Classification

SR University

Feb 2024 - Present (2 years 4 months)

Built an EEG signal classification system using CSP-LDA-LSTM with Bayesian optimization for hyperparameter tuning. Achieved 95% accuracy using 10-fold cross-validation on motor imagery signals with a low misclassification rate of 0.072.

EEG Signal Processing CSP LDA LSTM Bayesian Optimization Matlab

Kidney Disease Classification

SR University

Jan 2024 - Present (2 years 5 months)

Developed a deep learning-based web system for kidney CT image classification using CNN, MobileNet, and VGG19, achieving up to 99.5% accuracy. Applied watershed segmentation and data augmentation, deploying the system via Flask, TensorFlow, and an HTML/CSS front-end.

Deep Learning CNN MobileNet VGG19 Flask TensorFlow HTML CSS

Java Full-Stack Development

Talent.io

Dec 2022 - Present (3 years 6 months)

Completed training in Frontend and Backend Technologies including HTML, CSS, JavaScript, Java, Python, and SQL, with foundational knowledge in React.js and Node.js. Developed a front-end project named 'Green Slot' using HTML, CSS, and JavaScript.

HTML CSS JavaScript Java Python SQL React Node Web Development Frontend Development

Education

Degrees, certifications, and relevant coursework

SR University

Bachelor of Technology, Computer Science & Engineering

Grade: 7.01 CPI

Activities and societies: Secured a Winner Certification named Samshodini in a debate out of 150+ people from the institute named KITS. Secured a Certification named RSPAC in a Dance Contest out of 50+ people from the institute.

Studied Computer Science & Engineering at SR University from 2020 to 2024, achieving a CPI of 7.01. Gained foundational knowledge in various programming languages and development frameworks.