**Renalka Khan**
LinkedIn | renalka2@illinois.edu | GitHub

### EDUCATION
**University of Illinois Urbana-Champaign**
*Master’s in Computer Science (GPA: 4.00/4.00)*
Aug 2022 - May 2024
- Course Assistant: Database Systems, Spring ‘23

**Dr. APJ Abdul Kalam Technical University, Noida, India**
*Bachelor of Technology in Computer Science and Engineering (GPA: 8.76/10)*
Aug 2016 - Sep 2020
- Academic Excellence Awards 2016-17: Rank 1/128 (CSE), Rank 1/987 (All Engineering)

### WORK EXPERIENCE
**University of Illinois Urbana-Champaign**
*Teaching Assistant (Cloud Computing Applications under Prof. Reza Farivar)*
Jan 2024 - Present
- Developed automated grading solutions using Docker, Kubernetes, AWS Lambda, Lex, Glue, and Athena, reducing manual effort by 60%.
- Provided technical support for AWS services during office hours.

*Research Assistant (Gies College of Business under Prof. Yilang Feng)*
Oct 2023 - Dec 2023
- Extracted historical snapshots from 5000+ company websites using BeautifulSoup, Selenium, and Wayback Machine.
- Performed named entity recognition using spaCy, NLTK, and GPT-4 on a newspaper corpus.
- Conducted data preprocessing, EDA, and generated key competitor insights.

**Advocate Construction, Urbana-Champaign, IL**
*Data Science Intern*
Jun 2023 - Dec 2023
- Engineered Power BI dashboards tracking sales KPIs and revenue, saving 10+ hours weekly.
- Designed schemas, relationships, and advanced SQL queries for ETL pipelines.

**Tata Consultancy Services, New Delhi, India**
*Assistant System Engineer (Software Developer)*
Jan 2021 - Jul 2022
- Developed microservices using Python/Flask, reducing data migration time by 40%.
- Implemented CI/CD pipelines on Azure DevOps, increasing application uptime by 30%.

**C-DAC (Centre for Development of Advanced Computing), Noida, India**
*Machine Learning Intern*
Feb 2020 - Mar 2020
- Built a Hindi Q&A system for farmers using NLP and cosine similarity algorithms.

### RELEVANT PROJECTS
**Morbidity Identification From Clinical Notes**
- Engineered a classification system using NLP, ML, and deep learning to detect morbidities from clinical records.

**Disaster Response**
- Created a Flask web app to categorize emergency messages in real-time using SQLite and ETL pipelines.

### SKILLS
**Programming:** Python, Bash, Flask
**Data Science:** PyTorch, Scikit-Learn, Pandas, NLTK, Power BI
**Database:** SQL, MongoDB, Neo4j
**Cloud/DevOps:** AWS, Azure (AZ-900, AI-900 certified), Docker, Kubernetes, Git

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