Hello! I'm Mayank, a Machine Learning Engineer from Jersey City, NJ. My background includes a Masters degree in Machine Learning, with a focus on Deep Learning and Natural Language Processing. I also happen to be a Software Engineer with more than 2 years of work experience in Backend Development. I'm skilled at fixing scaling issues, implementing new features, and upgrading microservices to handle more traffic. I'm looking for opportunities to apply my knowledge in Generative AI and Deep Learning to tackle challenging problems.

Feel free to connect with me on LinkedIn or check out my portfolio.

Explore my projects to see detailed applications of machine learning and deep learning across various domains:

A collection of academic projects demonstrating the use of deep learning techniques in various scenarios:

• Lexical Complexity Predictor: Predicting the complexity of words using transformer-based models like BERT and RoBERTa.
• LLM for Sentiment Analysis of market conditions based on global news reports : Using sentiment analysis to predict market conditions from global news reports.
• Sentiment Analysis of IMDB Reviews: Analyzing sentiments in movie reviews using a Word2Vec model in TensorFlow.
• Semantic Network from Tweets: Building semantic networks from tweets containing specific keywords.
• N-Gram and RNN Text Generator: Text generation using N-Gram models and RNNs with TensorFlow.

A modern, responsive social media platform inspired by Meta's Threads. Built with TypeScript, Next.js, and Tailwind CSS.

• Languages and Libraries: Python, C++, JavaScript, Java, Go, typescript, Sk-learn, Keras, PyTorch, React.js,Next.js
• Database and Frameworks: MongoDB, SQL, DynamoDB, REST API, gRPC, GraphQL
• Machine Learning: RAG , LLM , LoRA, Supervised Fine tuning, Reinforcement Learning , Langchain, Pinecone
• Others: Scikit-Learn, Applied Mathematics, AI, Data Modeling, System Design, Exploratory Data Analysis, Algorithm Development,A/B testing, tensorflow, AWS, Apache Kafka ,PostgreSQL, linux, Data Ingestion, git, kubernetes, Distributed Systems , Jenkins ,AutoML

• Micron Technology: Designed a distributed Deep Learning model using PyTorch Lightning to improve the electronic design automation process by 17%. Trained the GCN model on a multi-GPU cluster using Pytorch DDP.
• BYJU'S: Developed microservices using Node.js and Java as per REST architecture to meet the requirements of over 2 million inventory requests used for global delivery of retail products. Reduced the latency by 42% using an event driven architecture using Apache Kafka.
• KloudOne: Built and deployed microservices in Go using gRPC for Accuknox, a container security platform.Improved CI/CD (Continuous Integration/Continuous Deployment ) pipeline using Jenkins to reduce downtime by 27%.

• Master of Science in Machine Learning, Stevens Institute of Technology
• Bachelor of Technology in Computer Science and Engineering, Manipal Institute of Technology

• Deep Neural Network Approach for Navigation of Autonomous Vehicles
  • Designed a CNN-based Deep Learning model for navigation of autonomous vehicles using over 200,000 real-world images and sensor data, integrating image compression and normalization techniques for GPU memory optimization
  • Published in IEEE, 6th International Conference for Convergence in Technology as first author. Citations – 4, h- index -1