Lovey Mishra
6306207252 | loveymishra60@gmail.com | linkedin.com/in/lovey-mishra | github.com/loveymishra
Professional Summary
Data-driven and results-oriented Artificial Intelligence and Machine Learning enthusiast with hands-on experience in deep
learning, computer vision, and natural language processing. Proven ability in designing, developing, and deploying
high-performance models using TensorFlow, PyTorch, and modern frameworks. Adept at leveraging advanced techniques
such as self-attention in variational autoencoders, optimizing CNNs for low-data scenarios, and deploying scalable solutions
on cloud platforms. Strong research background demonstrated through published work and industry collaborations.
Education
Amity University, Lucknow, U.P. Lucknow, India
Bachelor of Technology in Artificial Intelligence Sep 2022 – May 2026
• Relevant Coursework: Machine Learning, Deep Learning, NLP, Computer Vision, Data Structures &
Algorithms, Statistical Analysis.
• Achievements: Dean’s List (2023), Top 10% in AI coursework.
St. Joseph Inter College, Lucknow, U.P. Lucknow, India
Pre-University Education Till 2022
Experience
Research Project - Generative AI Amity University, Lucknow, India
Variational Autoencoder with Self-Attention Nov 2024 – Jan 2025
• Conducted research on advanced Generative AI techniques with a focus on Variational Autoencoders (VAEs)
integrated with self-attention mechanisms.
• Enhanced latent space organization, resulting in significantly improved model interpretability and performance
metrics.
• Utilized Python, TensorFlow, and PyTorch, and leveraged data augmentation, optimization algorithms, and
hyperparameter tuning.
NTCC Research Project - CNN Optimization Amity University, Lucknow, India
Industry-Guided Research Program Aug 2023 – Dec 2023
• Collaborated with industry experts to optimize Convolutional Neural Networks (CNNs) for high accuracy on
minimal datasets.
• Authored a peer-reviewed research paper and a comprehensive white paper detailing methods for efficient CNN
training and transfer learning.
• Applied advanced techniques including data augmentation, dropout regularization, and ensemble methods.
Technical Projects
Formula 1 Car Image Classification | Python, TensorFlow, OpenCV, CNN, Streamlit
• Designed and implemented a CNN model to classify 10 F1 car models with 97% accuracy using advanced data
augmentation and transfer learning.
• Deployed the solution as a scalable Streamlit web application, ensuring real-time image processing and
classification.
Car-0-bar App | Android, Java, Firebase, Figma, Web Scraping
• Developed a feature-rich Android application integrating real-time data updates, web scraping, and Firebase
backend.
• Utilized Figma to design an intuitive UI/UX, significantly improving user engagement and retention.
NLP Next Word Predictor | Python, PyTorch, LSTM, TensorFlow, Streamlit
• Built an LSTM-based next-word prediction model achieving 92% accuracy, leveraging extensive training on large
text corpora.
• Integrated model deployment via Streamlit for interactive, real-time predictions, enhancing user experience.
Generative AI for Car Image Generation | Python, GANs, VAEs, TensorFlow, Streamlit
• Developed a VAE-based generative model to synthesize high-quality, diverse car images from a 60K-image dataset.
• Incorporated self-attention mechanisms to refine the latent space and boost generative performance.
• Published the project on GitHub with an interactive Streamlit interface, enabling real-time experimentation and
visualization.
Technical Skills
Programming: Python, Java, C, SQL, JavaScript, HTML/CSS, R
Frameworks & Libraries: TensorFlow, PyTorch, Keras, Scikit-learn, Flask, React, FastAPI, OpenCV, NumPy,
Pandas, SpaCy
Data Science & ML Tools: Jupyter Notebook, Tableau, Azure ML Studio, H2O.ai, Git, Docker
Cloud & Deployment: Google Cloud Platform (GCP), Firebase, AWS, Streamlit, GitHub, Docker
Methodologies: Deep Learning, Machine Learning, Neural Networks, Transfer Learning, Natural Language Processing
(NLP), Computer Vision, Data Augmentation, Embedding Techniques (Word2Vec, BERT, Glove, etc.)
Certifications
Google Cloud Computing (NPTeL): Certified
Deep Learning Specialization: Extensive training on CNNs, RNNs, GANs, Transformers
Natural Language Processing (NLP): NLP with Python, SpaCy, and Transformers
Machine Learning: Comprehensive coursework in supervised/unsupervised learning and neural networks
Achievements & Extracurriculars
Open Source Contributor: Active contributor to 5+ AI projects, including TensorFlow and PyTorch repositories.
Technical Blog Writer: Authored 10+ in-depth AI/ML articles on Medium, reaching an audience of 5,000+ readers.
Hackathon Winner: Secured 1st place in a national AI hackathon for developing a real-time object detection solution.
Volunteer: Led AI/ML workshops for underprivileged students, impacting over 200 learners.
