Hi there👋🏼
I'm Chiranjeevi, a passionate software developer with a profound interest in Artificial Intelligence and Deep Learning. Currently, I am pursuing a Master's degree in Computer Science and Engineering at IIT Tirupati. My enthusiasm for technology drives me to constantly learn and innovate, and I find great joy in solving complex problems.
Socials:
You can find me on:
- LinkedIn
- Medium
- Quora
- Research Gate
- Instagram
- Leetcode
- Credly
- CodeWars.
Areas of Interest
- Deep Learning/Generative AI
- Machine Learning/Artificial Intelligence
- Legacy Modernization
- Large Language Models
- Android Development
- Parallel Computing
Education
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M.Tech-Computer Science and Engineering
IIT Tirupati, 2023-2025
Grade: 9.92/10.0
Relevant coursework: CS520L - Parallel Computing, CS519L - Machine Learning, CS518L - Deep Learning, CS514L - Artificial Intelligence, CS519P - Intelligence Systems
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B.Tech-Computer Science and Engineering
Dr. Ambedkar Institute of Technology, 2019-2023
Grade: 9.55/10.0
Relevant coursework: 18CS32 - Data Structures and Algorithms, 18CS553 - Artificial Intelligence, 18CS53 - Database Management System, 18CS62 - Machine Learning
Projects
The Reaper Bot
Description:
Developed an automated Discord bot integrated with Google's Gemini API to enhance user interactions and data analysis. The bot offers: Website Summaries, Web3 Compliance Analysis, Image Analysis, and Interactive Chat. The project utilises gemini-1.5-pro as the text model and gemini=pro-vision as the image analyser model.
Technologies Used: Discord Developer Tool, Python, Flask, Render, Google Generative AI, Prompt Engineering
Link: TheReaperBot
COBOL RuleForge
Description:
Developed a framework for extraction and summarization of Business Rules from legacy COBOL codebases. Generated dataset of COBOL codes and corresponding business rules using few-shot prompting with Google’s gemini-1.0-pro model. Fine-tuned LLMs like Gemma, Llama2, and Mistral on the generated dataset, enhancing the accuracy and quality
of the extracted business rules compared to their non-fine-tuned versions
Technologies Used: Python, Jupyter Notebook, Google Generative AI, Mistral AI, Google Gemma, Llama2, Prompt Engineering, Fine-tuning
Link: COBOL RuleForge
Susceptibility of Adversarial Attacks on Medical Image Segmentation Models
Description:
Led an investigative study into the vulnerability of popular medical image segmentation models to white box adversarial attacks like FGSM. Utilized advanced deep learning techniques to assess the robustness of segmentation algorithms against targeted adversarial manipulation. Expanded upon the existing framework by conducting experiments and investigating potential vulnerabilities using an alternative neural network architecture, increasing the attack success rate by almost 6%.
Technologies Used: Python, Jupyter Notebook, PyTorch, PIL, Autoencoders, UNET
EcoTrack
Description:
Developed a Trash Tracker mobile application with Android Studio in alignment with Sustainable Development Goal (SDG) #11 - sustainable cities and communities. Enabled the application to allow users to photograph litter or waste in their communities, geotag the locations, and report incidents along with the specific trash categories for improved local cleanliness and sustainability efforts. Leveraged Google Maps API to integrate real-time tracking and navigation functionalities within the application, enhancing user experience and facilitating efficient reporting of litter or waste incidents
Technologies Used: Android Studio, Java, Firebase, Google Maps API
Link: EcoTrack
Skills
- Programming and Scripting Languages: C/C++, Python, Java, Linux CLI, Bash, MySQL, Javascript, HTML, CSS
- Tools and Libraries: Numpy, Pandas, Scikit-learn, Pytorch, CUDA, OpenMP, Git & GitHub, Jupyter Notebbok, Vim Editor, VSCode, Latex, Markdown
- Soft Skills: Communication, creative problem-solving, time management, team coordination, leadership, team management
Experience
Intern
SGT Global Technologies India, 03/2023 - 04/2023
- Acquired expertise in configuring and managing Salesforce Cloud applications.
- Implemented innovative strategies in application design through creative inception and planning.
- Set up diverse permission sets tailored to user roles within the organization
Publications
Abstract:
Generative Adversarial Networks (GANs) have emerged as a potent framework in the discipline of Artificial Intelligence (AI) for generating realistic synthetic data. With the increasing interest and advancements in GANs, there is obligation for a detailed comparative study to comprehend the competencies and vulnerabilities of different GAN variants. This paper sets forth a comprehensive study and comparison of various types of Generative Adversarial Networks (GANs) and their performance in generating high-quality images. GANs have gained popularity in recent years due to their capacity to generate realistic synthetic images. However, the effectiveness of GANs varies depending on the architecture and parameters employed. We have evaluated and compared the performance of different types of GANs, including DCGAN, SRGAN, and CGAN, on benchmark datasets such as CIFAR-10 and MNIST. The evaluation metrics include image quality, standard GAN loss functions and Fréchet inception distance (FID). The results demonstrate that the performance of GANs is highly dependent on the dataset and architecture used, with no single GAN type dominating across all datasets. This comparative study serves as a valuable resource for researchers and practitioners in AI, providing a foundation for selecting the appropriate GAN architecture for specific generative modeling tasks.
Publication Link: A Comparative Analysis on the Effectiveness of GAN Performance
Weather Prediction Analysis using Classifiers and Regressors in Machine Learning (01/2023)
Abstract:
Weather predictions are essential as they protect both property and human lives. Forecasts based on temperature and precipitation are critical for agriculture for merchants in the commodities markets. Humans are also closely related to weather forecast like from daily traveling to daily commuting. Utility firms use temperature projections to predict demand in the upcoming days. Machine learning is a technique that can be used to forecast many different weather patterns, including storms, hurricanes, temperature changes, cyclones, and floods. This study has compared the performance of different deep learning methods for predicting the weather and temperature, including decision tree classifier and SVR, which are rarely used for this purpose. The key variables that affect weather forecasting include air temperature, air pressure, humidity, cloud cover type, solar radiation, precipitation amount and type, and wind speed and direction. Our work focuses on implementing five different machine learning models on a classification dataset and four machine learning models on a regression dataset. Based on our experiments, the regression dataset contributes more towards accurate weather prediction using Decision Tree Regressor, which yields a regression score of 95.70%.
Publication Link: Weather Prediction Analysis using Classifiers and Regressors in Machine Learning
Positions of Responsibility
Class Representative
IIT Tirupati, 08/2023 - Present
- Currently serving as the Class Representative for my M.Tech program, acting as a bridge between students and faculty.
- Managed communication, organized class meetings, and coordinated both academic and extracurricular activities.
- Effectively resolved student concerns, fostering a positive and collaborative learning atmosphere.
Teaching Assistant for the course, CS209M & CS209L : Computer Organisation and Architecture
IIT Tirupati, 01/2024 - 05/2024
- Instructed sophomores in the basics of computer architecture, RISC-V assembly language, and how to work with the Ripes simulator
- Joined department meetings to discuss teaching methods.
- Also, graded student work and exams, giving timely feedback to help them improve.
Teaching Assistant for the course, ES103M : Introduction to Programming
IIT Tirupati, 08/2023 - 12/2023
- Taught the basics of C programming, Linux environment, and usage of Vim command line editor to freshmen.
- Supervised the labs for the course, evaluated their lab assignments, quizzes and examination papers.
Class Representative
Dr. Ambedkar Institute of Technology, 08/2019 - 06/2023
- Served as the Class Representative for my B.Tech program, acting as a liaison between students and faculty.
- Facilitated communication, organized class meetings, and coordinated academic and extracurricular activities.
- Successfully
addressed student concerns, contributing to a positive and collaborative learning environment.
Achievements
- Gold Medals (2023)
Achieved 4 gold medals for academic excellence in my B.Tech degree: Principal’s Medal for the Topper of the Institute, Best Performer of the Institute, Academic Excellence Award and M H Jayaprakash Narayan Award for Institution Topper
- Upraised Embark Fellow (2021)
Ranked among the top 2% of Embark Fellow candidates in the Upraised skill exam.
- Student of the Year (2018)
Received the Student of the Year award for excellence in academics and co-curricular activities during my intermediate/+2 studies.