Badar Ur Zaman@badar_ur_zaman

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Events attended

Submissions made

Pakistan

1 year of experience

About me

I’m a Software Engineering student currently in my 6th semester. I’m always eager to grow and constantly push myself to take on new challenges. I tend to lose interest in things once they become too easy for me. Right now, I’m transitioning into the Machine Learning field. I believe that university assignments, quizzes, and exams alone aren’t enough to thrive in today’s competitive market. That’s why I’ve also been working in the Web Development industry for the past 6-7 months.

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🤝 Top Collabolators

Badar Ur Zaman

Muhammad Yousif

Data Scientist and Machine Learning Practitioner | Student

Dr Axa

Touqeer Abbasi

I am a recent Bachelor of Science in Computer Science graduate with a strong passion for machine learning and artificial intelligence. Currently, I am honing my skills as an ML intern, where I am gaining hands-on experience in developing and deploying machine learning models. As an AI enthusiast, I am constantly exploring new advancements in the field and looking for innovative ways to apply AI technologies to solve real-world problems. With a solid foundation in computer science and a keen interest in AI, I am excited to contribute to the future of technology.

🤓 Submissions

SPACE SCIENCE CHAT BOT

The limited accessibility of space-related data and insights presents a critical challenge, impeding researchers, educators, and the public from driving innovation, advancing education, and making informed decisions in the domain of space exploration. To address this challenge, we have developed an advanced educational chatbot designed to cater to diverse learning levels, including students, professionals, and children. This intelligent chatbot dynamically adapts to the user's educational background, enabling individuals to ask space-related questions and receive accurate, personalized responses. By simplifying complex space concepts into clear, comprehensible explanations, the chatbot makes space education more accessible. It empowers learners of all ages and backgrounds to explore the intricacies of space science, fostering curiosity and facilitating effortless knowledge acquisition.

Hackathon link

Patient Assistance App

Patient Input: Patients can enter their symptoms, medical history, or concerns into the app. This could range from describing a specific condition, reporting a set of symptoms, or even sharing their daily lifestyle and medical background. LLM-Driven Analysis: The app utilizes advanced language models that analyze the input provided by the patient. These models are trained on a vast dataset of medical knowledge, helping to identify potential conditions or concerns based on the data provided. Preliminary Medical Report: Based on the patient’s input, the app generates a preliminary medical report. This report offers insights into possible diagnoses, recommended next steps, and any potential lifestyle adjustments. It serves as an informative starting point for further medical consultation. Improved Doctor-Patient Interaction: The app enables more effective communication between the patient and the healthcare provider by delivering well-organized, structured reports. This helps doctors understand the patient's concerns more quickly, making their consultations more efficient. The report is not a definitive diagnosis but a tool to guide the doctor’s examination.

Hackathon link