Natansh
New Delhi, Delhi, India
Experience: 3 years
Open to: Full-Time
Education: Bachelors
Availability: Immediate
Skills: Jupyter Notebooks, LLMs/ChatGPT, Matplotlib, Notion, NumPy, pandas, PostgreSQL, PowerShell, Python, Python3, PyTorch, scikit-learn, TensorFlow
Previously worked at: Startups
Assessment Score: 80
- Machine Learning Expertise with Hands-On Industry Experience
Gained professional experience as a Machine Learning Intern at Reliance JIO, developing advanced models for face detection, feature extraction, and clustering, achieving high accuracy in grouping images. Implemented pre-trained models like YOLOv8 and ResNet18 to build datasets and apply clustering algorithms, showcasing expertise in deep learning and computer vision. - Strong Academic Foundation in Electronics and Machine Learning
Pursuing a B.Tech in Electronics and Communication Engineering with a Minor in Machine Learning from Delhi Technological University, achieving a CGPA of 7.51/10. Academic background reinforced by practical application of skills in AI, computer vision, and data analysis. - Published Research and Innovations in Hybrid Deep Learning Models
Co-authored a research paper on arrhythmia classification using a hybrid CNN-LSTM model, achieving 98.94% accuracy on ECG signal analysis. Presented at the First International Conference on Electronics, Communication, and Signal Processing, showcasing contributions to advancing cardiovascular diagnostics. - Comprehensive Project Portfolio in AI and Generative Models
Delivered innovative projects such as an AI-powered storybook creator using GPT-4o mini and Stable Diffusion, a melody generator leveraging LSTM networks, and a speech-to-text system optimized with OpenAI Whisper, demonstrating proficiency in deploying and optimizing generative AI and deep learning models. - Leadership and International Rover Design Competitions
Served as Science & Research Co-head for Inferno DTU, the official Mars Rover Team, leading the science module design for the University Rover Challenge (URC) in Utah, USA. Successfully integrated PCB sensor systems and achieved high precision in soil and rock composition analysis with real-time visual feedback. - Technical Expertise and Diverse Skill Set
Proficient in Python, TensorFlow, PyTorch, Keras, and tools like SKLearn and Pandas. Skilled in GenAI, LLM fine-tuning, Arduino, and computer vision. Demonstrates strong teamwork, management, and report-writing abilities, essential for collaborative and interdisciplinary projects.