I am an aspiring AI/ML Researcher with a keen interest in advancing Deep Learning and Large Language Models (LLMs). My primary focus is on conducting impactful research that pushes the boundaries of artificial intelligence. With a background in Computer Science and Engineering, I am constantly seeking opportunities to contribute to cutting-edge research, particularly through internships in AI/ML research labs.
- Deep Learning: Working on novel architectures to improve model performance in various domains, including computer vision and natural language processing.
- Large Language Models (LLMs): Exploring the power and limitations of LLMs, focusing on tasks like language understanding, generation, and fine-tuning for specific applications.
- High-Frequency Trading Data Analysis: Leveraging machine learning techniques for analyzing real-time financial data and enhancing predictive models in high-stakes environments.
- Connectomics: Studying the comprehensive mapping of neural connections in the brain using advanced imaging techniques and machine learning algorithms to understand brain structure and function.
- B.Tech in Computer Science & Engineering.
- Currently enrolled in the Machine Learning Specialization on Coursera, strengthening my knowledge of core machine learning concepts and methodologies.
- Violent Activity Detection using LSTM, LRCN, and ConvLSTM: Designing models to improve public safety by detecting violent activities in real-time from video feeds.
- ECG Signal Classification: Developing a deep learning model for classifying ECG signals into four categories and comparing its performance with transformer-based approaches to advance healthcare technology.
- High-Frequency Trading Analysis: Studying market patterns using machine learning to detect trends and improve decision-making in financial trading systems.
- Intern at a leading AI research organization like Google DeepMind to gain hands-on experience in solving real-world problems through advanced AI techniques.
- Continue publishing research in the areas of Deep Learning and Natural Language Processing to contribute to the broader AI community.
- Advanced Neural Networks and their applications in signal processing and image recognition.
- Transformer Architectures and their influence on state-of-the-art NLP models.
- Enhancing my proficiency in Data Structures and Algorithms (DSA) to solve complex problems efficiently.
- Programming Languages: Python, TensorFlow, PyTorch, Keras
- Research Tools: Jupyter, LaTeX, Git
- Libraries/Frameworks: NumPy, SciPy, OpenCV, Hugging Face
I am actively seeking research intern roles where I can apply my knowledge of Deep Learning and Machine Learning. If you are working on exciting research or have internship opportunities, I would love to connect!