Kanishk reddy

I am Kanishk Reddy, currently pursuing my Bachelor of Engineering in Computer Science from SRM Institute of Science and Technology, Chennai. With a strong academic background and a CGPA of 8.41, I have consistently demonstrated my commitment to academic excellence and technical proficiency.

I have a robust skill set in programming languages like C/C++, Python, JavaScript, TypeScript, HTML, and CSS. My proficiency extends to frameworks such as Tailwind CSS, Next.js, Bootstrap, and Flask, along with libraries like Numpy, Pandas, Matplotlib, React.js, Tkinter, and Streamlit. Additionally, I am well-versed in tools like Jupyter Notebook, VScode, Github, Git, and Google Colab, and have hands-on experience with databases such as MySQL and PostgreSQL. My expertise also encompasses machine learning and deep learning frameworks like TensorFlow, PyTorch, scikit-learn, Keras, and Librosa, particularly in the area of computer vision.

What drives me is a passion for solving real-world problems through technology. I thrive on challenges and am motivated by the opportunity to create impactful solutions. This is evident from my experience as a Web Developer at Next-Gen AI, where I designed and developed a user-friendly, responsive website for their flagship event, Pentathon, which increased registrations by 30%. Additionally, I organized a 24-hour Webathon event, guiding participants through technical challenges and contributing significantly to the development of the official Next-Gen AI website and various client projects.

Among the interesting projects I have built, PlantPath stands out. This deep learning-based system for early detection and identification of plant pathogens has achieved an impressive accuracy of 98.27%. Developed using TensorFlow and Keras, PlantPath empowers farmers with on-the-go pathogen detection capabilities through a user-friendly interface. Another notable project is the EDA Audio Classification, where I created a machine learning model to classify urban sounds, achieving 80% accuracy on the test set using MFCC features and neural networks.

Additionally, I developed the Dark Pattern Buster Chrome extension to combat deceptive design tactics, which boosts user reporting and site blacklisting accuracy to 97%. Another project, Daily Dash, is an all-in-one web application integrating a To-do list, personal notes, and an expense tracker, optimized for performance and responsiveness across all devices.

Beyond my technical projects, I have been actively involved in academic and extracurricular activities. I participated in multiple hackathons, such as the Prayagraj Mahakumbh Hackathon 2025, where our team developed a crowd surveillance system utilizing advanced computer vision techniques. I have also been an active member of several technical clubs, organizing events and hackathons, and participated in a fundraising internship to support underprivileged children's access to education.

In October 2024, I am honored to present my research paper, "PlantPath: Deep Learning Based Pathogen Detection System," at ICCCNet 2024 in the UK. This prestigious international conference will allow me to share my findings and engage with fellow researchers, industry professionals, and academia.