Likith Dabilpuram

Completed my B.Tech at IIIT Kottayam, eager to launch my career in your company, bringing a robust background in machine learning, NLP, deep learning, data pre-processing, object detection, and predictive analysis. Throughout my academic journey, I have demonstrated a commitment to excellence, translating theoretical knowledge into practical applications. Proficient in NLP, deep learning, and various projects, my exceptional problem-solving and critical thinking skills, combined with a passion for staying current with industry trends. My dedication to continuous learning positions me as a promising candidate ready to contribute meaningfully to an innovative environment.

• Hindi
• Telugu
• English

• Reinforcement Learning Assisted And Evolutionary Algorithm Vehicle Routing Problem, Developed a project focusing on enhancing optimal solutions for Capacitated Vehicle Routing Problems, addressing complex logistics and transportation challenges which in turn aid for sustainable betterment of the society. Integrated interdisciplinary domains, employing Q-learning in reinforcement learning and evolutionary algorithms, to optimize solution exploration and exploitation for improved performance. Incorporated time series data based on the busiest traffic times for delivery locations, allowing the algorithm to consider heavy traffic information and optimize routes accordingly. Achieved key objectives, including the creation of a versatile framework, enhancement of solution quality, validated through testing on both simulated and real-world settings
• Predictive Modeling for Weather Events, The primary objective of this project is to develop a robust predictive model capable of accurately forecasting weather events. By leveraging advanced data analysis techniques, our goal is to provide timely and reliable predictions to empower individuals, communities, and decision-makers to better prepare and respond to these natural phenomena. Through accurate forecasting, we aim to mitigate the potential risks and impacts associated with weather events, enhancing overall resilience and safeguarding lives and property. Ultimately, this project seeks to harness the power of predictive analytics to support proactive measures and ensure readiness in the face of unpredictable weather patterns. Using attention mechanisms to focus on important parts of the time series, improving the LSTM's ability to capture relevant information, by integrating an attention layer into the LSTM network to dynamically weigh the importance of different time steps, training the combined LSTM-attention model on the time series data, allowing it to learn where to focus attention for better predictions.
• Digitalized Notice Board, Led a development team in creating a Digitalized Notice Board application, showcasing proficiency in Android Studio and FIREBASE database integration. Designed a user-centric platform facilitating seamless event viewing and posting across diverse categories, enhancing accessibility and engagement which is currently under deployment at our student council. Demonstrated strong leadership capabilities as the Team Lead, driving collaborative efforts to successfully bring the project to fruition.
• Vibe-Chat, Spearheaded the development of 'Vibe-Chat,' a real-time chat application, with a focus on interactive and seamless user experiences. Designed and implemented the frontend using React.js, showcasing proficiency in crafting responsive and user-friendly interfaces. Engineered the backend using Node.js to ensure robust real-time chatting capabilities, emphasizing performance and reliability. Established a secure user authentication system and integrated MongoDB for efficient database management, contributing to the overall success of the project and highlighting expertise in web development.
• Human Emotion Detection, Developed a high-accuracy Machine Learning application for human emotion detection, achieving a 92% accuracy rate through webcam input. Implemented MediaPipe and Convolutional Neural Network (CNN) technologies to classify emotions, showcasing proficiency in advanced machine learning techniques. Recognized and addressed vulnerabilities in the project, emphasizing a commitment to enhancing security and robustness in emotion detection capabilities. This includes ongoing efforts to mitigate potential risks and improve overall model reliability
• OTT Trending Movies Website, Utilized the Netflix API for content retrieval, showcasing proficiency in working with external APIs to enhance website functionality and user engagement. Implemented Firebase for hosting and deployment, ensuring a highly available and performant platform for seamless user experiences. Demonstrated expertise in web development, API integration, and efficient deployment strategies, underscoring the ability to create engaging and dynamic user-centric platforms.

• Machine Learning A-Z Python and R in Data Science, Udemy Sep 2022 — Dec 2022
• The Complete 2023 Web Development Bootcamp, Udemy Jan 2023 — Jun 2023
• The Complete Android 12 and Kotlin development, Udemy Jun 2022 — Sep 2022