Share Profile
Syeda Samah Daniyal
Aspiration Statement
I am driven by AI/ML and Data Science to solve complex problems. I aim to pursue impactful professional roles in machine learning and predictive analytics.
Core Skills
- Data Analysis & Visualization
- Large Language Models (LLMs)
- Python
- PostgreSQL/MS SQL Server
- PyTorch
Core Competencies
- Agility
- Collaborates Openly
- Strategic Thinking
Preferred Career Paths
First priority: AI Engineer
Second priority: Data Scientist
Third priority: Product Manager
Academic Awards / Achievements
- Dean's List 2025
Experience
Leadership / Meta-curricular
- Participated In Texas A&M's Invent For The Planet 2025
- Ta For Linear Algebra & Data Structures And Algorithms
- Volunteered For Wintercamp'22 Workshop, Wise (Women in Science and Engineering)
- Pr Lead, Computer Science And Engineering Club
- Event Manager (Pr Team), Computer Science And Engineering Club
Internship / Volunteer Work
- Campus Ambassador - Graduate Trainee Program, Salesflo (January – March 2026)
- Ai Data Analyst Intern, Excelerate (October – November 2025)
- Undergraduate Research Assistant, Habib University (June – August 2024)
Publications / Creative Projects
- Research Paper – Research Project Poster on Data Visualization of "Data Analysis Across Boundaries" accepted in the International IEEE VIS Conference 2025.
Final Year Project
Project Title
Al Khidmat Public Chat Portal
Description
The AI-powered multilingual chat portal for Alkhidmat Foundation addresses manual query-handling delays by providing a centralized, inclusive solution. Using a Self-RAG (Retrieval-Augmented Generation) and Agentic AI pipeline, it automates responses for donor, healthcare, and general domains in English, Urdu, and Roman Urdu. The system utilizes multilingual-e5-base embeddings and pgvector for semantic search, with OpenAI and Alif for generation. To ensure accuracy, it employs a domain classification and confidence scoring engine that fuses retrieval quality with token probability. Key benefits include 24/7 accessibility for underserved communities, reduced staff workload, and automatic human-agent escalation for complex queries. Moreover, there is a dedicated admin dashboard to view LLM analytics and update the RAG Knowledge Base.
Project Pictures
