class AatmajSalunke:
def __init__(self):
self.name = "Aatmaj Amol Salunke"
self.education = {
"Masters": "Artificial Intelligence @ Northeastern University",
"Bachelors": "Computer Science & Engineering @ Manipal University Jaipur"
}
self.experience = ["ISRO Scientific Researcher", "WictroniX ML Intern", "IBM AI Mentee"]
self.interests = ["Machine Learning", "Deep Learning", "NLP", "Computer Vision", "Reinforcement Learning"]
self.currently_learning = "Advanced AI Techniques for Real-world Applications"
self.looking_for = "Internship Opportunities (May 2025 - Dec 2025)"
self.pronouns = "he/him"
def say_hi(self):
print("Thanks for dropping by! Let's collaborate on something innovative!")
me = AatmajSalunke()
me.say_hi()- 📚 Pursuing MS in Artificial Intelligence at Northeastern University
- 🔬 Exploring advanced concepts in Reinforcement Learning and NLP
- 🌟 Building AI solutions that solve real-world problems
- 🤝 Open to collaborate on futuristic, high-impact projects
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🛰️ Scientific Research Intern, ISRO - Worked in SIPG Department at SAC, enhancing satellite-based weather prediction algorithms through advanced signal and image processing.
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🌿 Research Intern, NIT Trichy - Specialized in Machine Learning applications for the Plants and Botany sector, contributing to three research projects on plant tagging and document recommendation systems.
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🚦 Machine Learning Engineer Intern, WictroniX - Contributed to a Government of Gujarat project on traffic and vehicle analysis for improved transportation systems.
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📊 Data Science Intern, Celebal Technologies - Gained hands-on experience in data analysis, modeling, and visualization for real-world projects.
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🧠 Artificial Intelligence Mentee, IBM - Collaborated with experienced AI professionals to contribute to cutting-edge AI projects.
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☁️ Salesforce Developer Trainee, Salesforce - Learned Salesforce fundamentals and developed applications during intensive training program.
- RAG-based financial insights system leveraging FinBERT, FAISS & LangChain
- 85% higher retrieval accuracy & 37% faster query response time
- NLP-powered search with hybrid retrieval (dense embeddings + BM25)
- 40% improvement in search relevance using Google's Gemini model
- AI-driven grocery shopping platform built during Innovate 2025 Hackathon
- Reduced manual shopping effort by 50-60% with LLM-powered features
- Enhancing Contextual Understanding in NLP: A Subword Tokenization Approach with ELMo and BERT
- OTPLM: An Ontology-Driven Approach for Tagging Plants using Hybrid Semantics and Strategic Learning Models
- DRHA: Document Recommendation for Horticulture and Agro-Based Farming
When I'm not coding or exploring AI algorithms, you can find me trying to solve complex algorithms by hand – just for fun!