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Aditya Mettu Location: Tempe, ArizonaGithub LinkedIn Email: EMAIL AVAILABLE Mobile: PHONE NUMBER AVAILABLE EDUCATIONArizona State University Tempe,ArizonaMasters in Computer Science (GPA - 4.0/4.0) August 2022  May 2024 Indian Institute of Technology (IIT), Kharagpur India Bachelor of Technology in Electronics and Communication June 2018  June 2022 TECHNICAL SKILLSProgramming Languages: Python, SQL, C++, Java, JavaScript, PHP, HTML, CSS Technologies & Tools: PyTorch, TensorFlow, Keras, Matplotlib, Seaborn, Pandas, NumPy, MongoDB, PostgreSQL Additional Skills: Git, Object-oriented programming, Agile Software Development Cycle, MLOps PROJECTSCross-Modal Data retrieval & Generation Python, Deep Learning, Transformers, Pytorch Jan 2024  May 2024 Executed end-to-end project tasks, involving advanced image preprocessing and data augmentation, alongside developing deep learning architectures optimized for batch processing and GPU efficiency. Engineered a dual-purpose system on the MSCOCO dataset, utilizing Deep Canonical Correlation Analysis (DCCA) for robust cross-modal data retrieval and a transformer model based on cross attention combining Vision Transformer(ViT) and GPT-2 for dynamic image caption generation, achieving synchronized image-text mapping and generation. Healthcare Mining & Generation BioBERT, RAG,Scrapy, GPT-2, BART Sep 2023  Nov 2023 Spearheaded the integration of BioBERT and Retrieval-Augmented Generation (RAG) techniques to enhance the precision and accessibility of medical data from online sources. Utilized advanced NLP models for data extraction and query expansion, employing algorithms like cosine similarity, BERT, and TF-IDF for efficient information retrieval and response generation. Engineered a robust platform using Scrapy for data scraping, React for dynamic UIs, and Flask for backend tasks. ML-Based Detection of Website Activity Digital Signal Processing, Machine learning May 2023  Jul 2023 Developed a machine learning model utilizing SVM and RSSI data to predict unauthorized website access during online exams, achieving 95% accuracy in identifying exam integrity breaches through network activity monitoring.s Speaker Recognition Digital Signal Processing, Deep learning, Neural Networks Jan 2022  Mar 2022 Developed a CNN model for bi-modal input with audio and visual modalities using SincNet deep learning architecture for speech recognition and speaker verification. Trained the model using video and audio data collected from NPTEL video lectures.Worked on proposing a new data set and fine-tuned the model for better results EXPERIENCEMachine learning Development Internship CityMall Jan 2022  June 2022 Actively Contributed to the creation of an AI-driven recommendation engine for CityMalls e-commerce platform, leveraging Angular for the front end and Spring Boot with MongoDB for backend data handling. Aimed at enhancing the shopping experience through personalized user behavior and preference analysis. Developed CityMalls machine learning infrastructure within a microservices architecture, focusing on AI features for product recommendations and predictive analytics, significantly improving service tracking and user satisfaction Machine learning Research Internship IIT-Kanpur May 2021  Aug 2021 Engineered advanced Machine Learning models for COVID-19 forecasting using real-time data, employing web scraping for data collection. Utilized Keras and PyTorch for model development and time series analysis. Developed and implemented SIR, LSTM and FbProphet models for precise COVID-19 case predictions, leveraging Keras and PyTorch frameworks to enhance forecasting accuracy in public health analytics. AI/ML Research and Development Internship SensorDrops Networks Pvt Ltd. Aug 2021  Oct 2021 Developed a smart digital stethoscope - SkopEdge, an AI-powered digital stethoscope application to provide reliable remote e-health monitoring with a minimum delay while enhancing overall network performance. Provided an analysis of the heartbeats and heart health in an audio clip by SkopEdge. Built a Machine learning model to predict the number of beats, cutoff frequency, and heart health with 95% accuracy. COURSESCloud Computing, Data Processing at Scale, Spatial Data Science, Data Structures & Algorithms, Operating Systems, Data Visualization, Artificial Intelligence, Statistical Machine Learning, Digital Signal Processing, Natural Language Processing(NLP), Human Computer Interaction (HCI), Software Verification Validation and Testing