Summary
Overview
Education
Skills
Accomplishments
Certification
Interests
Projects
Timeline
Generic

Pruthvi Poreddy

Intern
Hyderabad

Summary

Hardworking Student offering part-time work experience and extensive knowledge of core subject matter. Meticulous and detail-oriented with excellent observational, organizational and communication skills.

Overview

2
2
Certifications
3
3
Languages

Education

Bachelor of Technology - Artificial Intelligence And Machine Learning

B V Raju Institute of Technology
Hyderabad, India
04.2001 -

Intermediate -

SRI CHAITTANYA JUNIOR KALASALA
Hyderabad, India
04.2001 -

High School -

Sri Chaitanya Techno School
Hyderabad, India
04.2001 -

Skills

Python

Machine learning

Object-oriented programming

NumPy library

Accomplishments

Bachelor of Technology (B.Tech)
[Artificial Intelligence and Machine Learning]
[B V Raju Institute of Technology], [Narsapur]
CGPA: 8.08 (Till Date)
Year of Graduation: [2026]

Intermediate (Class XII)
[Telangana State Board of Intermediate Education]
Percentage: 93.1%
Year of Passing: [2022]

Secondary School (Class X)
[SSC]
CGPA: 10.0
Year of Passing: [2020]

Certification

Bronze Certificate - Smart Interviews Program(DSA)

Interests

Aspiring Machine Learning Engineer with a strong foundation in programming, data structures, and algorithmic problem-solving Passionate about building intelligent systems and leveraging data to solve real-world problems Actively expanding expertise in Python, ML frameworks, and model development

Projects

1. Self-Trained Panoptic Segmentation
Computer Vision | Deep Learning | Self-supervised Learning

  • Developed a self-training pipeline for panoptic segmentation combining semantic and instance segmentation tasks.
  • Utilized pre-trained models and pseudo-labeling to improve performance with limited labeled data.
  • Evaluated using standard metrics such as PQ (Panoptic Quality) on benchmark datasets.
  • Tools/Tech: Python, PyTorch, Detectron2, OpenCV

2. Bias and Fairness Mitigation in LLMs
NLP | Responsible AI | Fairness in Machine Learning

  • Investigated and implemented techniques for detecting and mitigating social bias in Large Language Models.
  • Conducted bias analysis using various fairness metrics and introduced mitigation strategies such as debiasing embeddings and fine-tuning.
  • Compared performance against existing models to highlight improvements in fairness without significant loss in utility.
  • Tools/Tech: Python, Transformers (Hugging Face), Sklearn, Fairlearn

Timeline

Deep Learning for NLP - NPTEL

01-2025

Bronze Certificate - Smart Interviews Program(DSA)

05-2024

Bachelor of Technology - Artificial Intelligence And Machine Learning

B V Raju Institute of Technology
04.2001 -

Intermediate -

SRI CHAITTANYA JUNIOR KALASALA
04.2001 -

High School -

Sri Chaitanya Techno School
04.2001 -
Pruthvi PoreddyIntern