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MS Computer Science student at CU Boulder specializing in NLP, interpretable AI, and responsible machine learning research.
Basics
| Name | Obed Junias |
| Label | Computer Science Graduate Student & NLP Researcher |
| [email protected] | |
| Phone | 720-266-0046 |
| Url | https://linkedin.com/in/obed-junias |
| Summary | I am a graduate researcher exploring Commonsense Reasoning, Neuro-symbolic NLP, and Responsible ML. My research focuses on developing reasoning frameworks that integrate structured logic with neural representations, with the goal of improving the interpretability, factual consistency, and fairness of LLMs. I aspire to contribute to foundational AI research at the intersection of cognition, reasoning, and ethical deployment. |
Work
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2021.08 - 2024.08 Senior Member of Technical Staff
Oracle Corporation
Architected and implemented TestNG and BATS automation frameworks for Oracle Rest Data Services and SQLcL, reducing manual effort by 95%. Engineered Python-based migration framework for Oracle APEX applications supporting 200+ employees.
- Reduced manual testing effort by 95%
- Led 15-member team for DB Tools feature validation
- Automated Oracle APEX application migrations
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2021.02 - 2021.07 Machine Learning Engineer Intern
Hewlett Packard Enterprise
Built intelligent automation solution with Groovy and Workfusion OCR, optimizing data workflows and integrating text extraction into software robots, increasing speed by 40% and reducing errors by 80%.
- Increased automation speed by 40%
- Reduced errors by 80%
- Delivered PoC on Intelligent Business Process Management
Education
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2024.08 - 2026.05 Boulder, Colorado
Master of Science
University of Colorado Boulder
Computer Science
- Machine Learning
- Data Center Scale Computing
- NLP and Deep NLU
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2017.08 - 2021.08 Bangalore, India
Bachelor of Engineering
BMS College of Engineering
Computer Science
- Algorithms
- Databases
- Operating Systems
- Computer Networks
Skills
| Programming Languages | |
| Python | |
| C++ | |
| Java | |
| Rust | |
| SQL |
| AI/ML Frameworks | |
| PyTorch | |
| TensorFlow | |
| Keras | |
| Transformers | |
| LangChain | |
| Scikit-Learn |
| Cloud Technologies | |
| GCP | |
| Oracle Cloud (OCI) | |
| AWS | |
| CI/CD |
Languages
| English | |
| Fluent |
Interests
| Machine Learning & AI | |
| Natural Language Processing | |
| Responsible AI | |
| Large Language Models | |
| Bias and Fairness | |
| Computer Vision | |
| Deep Learning |
Projects
- 2024.01 - 2024.12
Medical Ethics Assessment of LLMs
Systematic assessment of ethical reasoning capabilities of large language models in clinical contexts using RAG pipeline and controlled evaluation with curated multiple-choice questions.
- RAG Pipeline Implementation
- Ethical Reasoning Evaluation
- 2024.01 - 2024.06
Lost in Plot: Contrastive Learning for Movie Retrieval
Dense retrieval system using fine-tuned BERT encoder with contrastive learning for tip-of-the-tongue movie retrieval, outperforming GPT-4 baseline on 100K+ movie corpus.
- Contrastive Learning
- BERT Fine-tuning
- Dense Retrieval
- 2024.06 - 2024.12
Resource-Efficient LLM Fine-tuning for Mental Health Support
Applied parameter-efficient fine-tuning with QLoRA to adapt Falcon 7B model for mental health conversations with limited computational resources.
- QLoRA Implementation
- Mental Health NLP
- 2024.03 - 2024.08
Multi-stage RAG System
Robust RAG system with FAISS indexing and Scikit-Learn context filtering for enhanced factual grounding of LLM responses over research paper corpus.
- FAISS Integration
- Multi-stage Retrieval