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Schedule Interview NowMy name is Ayesha Y. and I have over 1 year of experience in the tech industry. I specialize in the following technologies: Data Science, Machine Learning, Python, Deep Learning, Natural Language Processing, etc.. I hold a degree in , Master of Computer Science (MSCS), Master of Computer Science (MSCS). Some of the notable projects I've worked on include: WA Agent for Real-Time Messaging & Automation with Voice & Text, Multi-Agent AI System Using ReAct, Reflection & Tool-Using Agents, Harmonizing Tourism and Nature Protection in Bavarian Forest Park 🌲, Mboathoscope- AI-based stethoscope App, Lung cancer Identification and classification using deep learning. I am based in Jaranwala, Pakistan. I've successfully completed 5 projects while developing at Softaims.
I value a collaborative environment where shared knowledge leads to superior outcomes. I actively mentor junior team members, conduct thorough quality reviews, and champion engineering best practices across the team. I believe that the quality of the final product is a direct reflection of the team's cohesion and skill.
My experience at Softaims has refined my ability to effectively communicate complex technical concepts to non-technical stakeholders, ensuring project alignment from the outset. I am a strong believer in transparent processes and iterative delivery.
My main objective is to foster a culture of quality and accountability. I am motivated to contribute my expertise to projects that require not just technical skill, but also strong organizational and leadership abilities to succeed.
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Munich Center for Machine Learning
Developed an Automated WA AI Agent for customer engagement, support, and sales automation. Integrated OpenAI for dynamic text responses, Whisper for Speech-to-Text, and ElevenLabs for Text-to-Speech t
Built agentic AI patterns from scratch using Python, Groq (Mixtral), and OpenAI-compatible models. Includes Multi-Agent Systems (Planner, Researcher, Executor), ReAct Agents (Reason + Act), Reflection
Developed and implemented an end-to-end solution for Bavarian Forest National Park to predict real-time visitor traffic at the hourly level for different regions of the park. The solution includes for
Mboathoscope is a digital stethoscope AI application that enables users to record, visualize, and analyze heart sounds. It employs machine learning algorithms to provide insights from the audio data,
This project demonstrates the implementation and deployment of multiple deep-learning models for lung nodule classification. The web application allows users to upload CT scan images of lung nodules a
in Data Science
Master of Computer Science (MSCS) in
2021-01-01-2023-01-01
Master of Computer Science (MSCS) in
2018-01-01-2020-01-01