MOHAMMAD LAHEB ASHISH PASHA

Computer Science (AI & ML) Student

Hyderabad, IN.

About

Highly motivated Computer Science (AIML) undergraduate with a strong foundation in deep learning, NLP, and robotics, seeking an entry-level AI/ML engineering or data-driven software development role. Proven ability to design and implement advanced AI systems, including a graph-enhanced text-correction system for aviation and a VR-based imitation learning pipeline for robotics. Leverages proficiency in Python, SQL, and generative AI tools to deliver innovative solutions and drive impactful technological advancements.

Education

Avanthi's Scientific Technological Research Academy

Hyderabad, Telangana, India
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B.Tech Computer Science (AIML) Grade: 8.2/10 CGPA

Alphores Junior College

Mancherial, Telangana, India
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Intermediate MPC Grade: 75%

Trinity High School

Mancherial, Telangana, India
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SSC General Studies Grade: 93%

Languages

English

Certificates

YUVA AI — IndianAI

GUVI

ChatGPT: Complete Generative AI & Prompt Engineering Course

Not Specified

Build & Deploy AI Apps with Google AI Studio: Multilingual AI Speech App Development

Not Specified

Affiliate Marketing — Growth Addicted

Not Specified

Skills

AI / ML

Machine Learning, Deep Learning, Natural Language Processing (NLP), Artificial Intelligence, Imitation Learning, ChatGPT Prompting, Google AI Studio, Vibe Coding.

Programming Languages

C, Python, Java.

Database

SQL.

Tools

Git (Basic), Debugging & Problem Solving.

Core CS Concepts

Data Structures, Computer Networks, Software Testing, Cloud Computing.

Web & Automation

WordPress, Responsive Web Design, N8N (workflow automation).

Soft Skills

Logical Thinking, Quick Learning, Team Collaboration, Adaptability.

Interests

Building AI Agents

Programming & Problem Solving

Vibe Coding

Exploring New Technologies

API Development

Projects

Graph-Enhanced Deep Learning for Automated NOTAM Correction in Aviation Systems

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Summary

Designed and implemented an automated NOTAM (Notice to Airmen) text-correction system to detect and fix aviation notice errors, leveraging advanced deep learning architectures.

VR-Based Imitation Learning for Household Robotics

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Summary

Developed a VR-based data collection pipeline to generate training data for robot imitation learning, exploring applications in next-gen AI video production.