Fellow:Sine Nitish
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Sine Nitish is an Indian AI/ML Engineer and Full-stack developer, who worked at CommandHQ from June to December 2024. He is known for his work in applying artificial intelligence to healthcare challenges, particularly in stroke prediction, and for his contributions to software development and innovation during his academic career. Nitish completed his Bachelor of Technology in Computer Science and Engineering from the Madanapalle Institute of Technology and Science in May 2024, graduating with First Class with Distinction. His research has been recognized with awards such as the Best Student Paper Award at the International Conference on Data Science and Artificial Intelligence (ICDSAI) in 2023, and he was selected as a University Innovation Fellow by Stanford University's Hasso Plattner Institute of Design (d.school).
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Early Life and Education
Nitish hails from Visakhapatnam in the state of Andhra Pradesh, India. During his schooling, he reportedly served as a school pupil leader and was involved with The Bharat Scouts and Guides. Nitish pursued a Bachelor of Technology (B.Tech) in Computer Science & Engineering at the Madanapalle Institute of Technology and Science (MITS), graduating in May 2024 with First Class with Distinction and a CGPA of 9.16/10.
While at MITS, Nitish was selected as a University Innovation Fellow (UIF), a global initiative by Stanford University's Hasso Plattner Institute of Design (d.school). This program involved intensive training in design thinking, leadership, and entrepreneurial problem-solving. As a fellow, he led campus transformation initiatives, including organizing a Rapid Design Thinking workshop that engaged over 600 students, faculty, and government school students. His contributions through the UIF program were recognized in Stanford's "Change Forward" Journal. The selection of MITS students, including Nitish, for this program garnered local media attention, highlighting the opportunity for students to engage with innovation ecosystems and leading tech environments.
Career
Nitish's career began with a series of impactful research and development internships, followed by a professional role focusing on AI/ML engineering and full-stack development. His experience demonstrates a consistent application of technical skills to create practical solutions with measurable outcomes.
Professional Experience
AI/ML Engineer & Full-Stack Developer
CommandHQ, Coimbatore, India (June 2024 – December 2024)
- Engineered a system for vehicle detection using YOLOv5 and PaddleOCR, which reportedly achieved 95% accuracy and reduced manual review processes by 70%.
- Contributed to the development of an AI-driven threat prediction system using FastAPI and AWS Lambda, achieving 90% accuracy. This system, featuring a secure Next.js user interface with Next Auth, was reportedly adopted by the Indian Army.
Internships
Research Intern, AI & Audio Processing
REDS Institute, HES-SO, Yverdon-les-Bains, Switzerland (December 2023 – May 2024)
- Focused on "Sentiment Analysis of Music using MFCC Features and RNN" under the supervision of Prof. Cédric Bornand.
- Developed a model achieving 90% accuracy in music sentiment classification.
- Improved audio processing pipeline efficiency by 30% through feature optimization.
- Gained exposure to international research practices.
Web Development Intern
NITTTR, Chennai (July 2023 – August 2023)
- Worked at the Centre for Rural and Entrepreneurship Development, under the Ministry of Education, Govt. of India.
- Developed and launched a web portal for rural entrepreneurship using React, FastAPI, and PostgreSQL, which scaled to support over 1,500 users.
- Commended for improving user experience by 40% using Tailwind CSS and implementing secure login functionalities with OAuth2 & JWT.
Deep Learning Intern
IIIT Surat (June 2022 – August 2022)
- Focused on enhancing CNN/RNN classification models.
- Applied Bayesian optimization to improve model performance by 15%.
- Used advanced data augmentation techniques to reduce overfitting by 25%.
- Recognized for punctuality, creativity, and technical skills.
Research and Projects
Nitish has been involved in several research projects and development initiatives, demonstrating an early aptitude for innovation and problem-solving.
Stroke Complication Prediction Model
Nitish engineered a neural network model based on Multi-Layer Perceptron (MLP) to predict the severity of brain stroke complications using family history and stroke data. This model achieved an accuracy of 94.32% in classifying multiclass stroke types. The research was published in the Springer Proceedings in Mathematics & Statistics as part of the ICDSAI 2023 conference. This work received the Best Student Paper Award at the 2nd International Conference on Data Science and Artificial Intelligence (ICDSAI), 2023, an event affiliated with California State University, USA.
Hybrid Telugu Emotion Classification
He designed a hybrid Machine Learning-Deep Learning (ML-DL) model for emotion classification in Telugu text. The model utilized ensemble methods on a corpus of over 35,000 entries, achieving 74.87% accuracy and a 67.44% F1-score. This research was presented at the 7th IEEE International Conference on Intelligent Computing (ICONIC 2K24) held at Panimalar Engineering College on March 22-23, 2024.
MITS CODE - Founder & Developer
During his first year of B.Tech at MITS, Nitish founded and developed MITS CODE, a campus-wide coding platform. The platform was designed to provide students with access to practice programming questions across various languages, including C, C++, Python, and Java. MITS CODE reached over 4,000 student users and was featured in Stanford University's "Change Forward" Journal for its student-driven innovation, a recognition linked to his work as a University Innovation Fellow.
SINE AI Code Generator
Nitish built a real-time AI code generation platform named SINE AI Code Generator, utilizing Sandpack. This tool was developed to reduce software development time, with an estimated 50% improvement in efficiency for certain coding tasks.
AI Multi-Agent System
He also created an AI Multi-Agent System using Langflow and Streamlit, featuring RAG-powered agents for AI task orchestration.
Publications
- Nitish, Sine; et al. (2023). "A Stroke Complication Neural Network Model to Predict the Severity of Brain Stroke Using Family History". In Lin, F.M.; Patel, A.; Kesswani, N.; Sambana, B. (eds.). Accelerating Discoveries in Data Science and Artificial Intelligence I. ICDSAI 2023. Springer Proceedings in Mathematics & Statistics. Vol. 421. Cham: Springer. doi:10.1007/978-3-031-51167-7_79. ISBN 978-3-031-51167-7.
- Nitish, Sine; et al. (2024). "Hybridized Emotion Recognition in Telugu Text: A Machine Learning Approach Integrating Multiple Modules for Enhanced Sentiment Analysis". Proceedings of the 7th IEEE International Conference on Intelligent Computing (ICONIC 2K24). Panimalar Engineering College. March 22-23, 2024.
Awards and Recognition
Nitish has received several awards and recognitions for his work in technology, innovation, and academics. These accolades highlight his contributions at both national and international levels. The consistent recognition across different domains, from research to practical innovation, underscores a multifaceted skill set. Local media coverage for his achievements further indicates the broader impact and visibility of his work.
Award/Honor | Year | Conferring Body/Event | Significance/Note |
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Best Student Paper Award | 2023 | 2nd International Conference on Data Science and Artificial Intelligence (ICDSAI) (affiliated with California State University, USA) | For paper "A Stroke Complication Neural Network Model to Predict the Severity of Brain Stroke Using Family History". This achievement was widely covered in regional newspapers. |
Smart India Hackathon Finalist | 2022 | Ministry of Education, Government of India | National finalist in the AI for Public Problem Solving domain (SIH Senior Software Edition GRAND FINALE 2022, August 25-26). |
University Innovation Fellow | 2021 (Cohort) | Stanford University, Hasso Plattner Institute of Design (d.school) | Selected for global innovation training program; led campus initiatives and featured in Stanford's "Change Forward" Journal. |
National Paper Presentation Winner, RAIDS 2023 | 2023 | MITS, National Level Technical Symposium RAIDS 23 (Dept. of Computer Science - AI & Data Science) | 1st Prize for presentation on "Stroke Prediction using AI" (April 19, 2023). |
NPTEL Course Topper - Business Analytics & Text Mining Modeling Using Python | 2023 | NPTEL, IIT Roorkee | Elite Gold certificate (91% score), ranked in Top 5% (Jul-Sep 2023 session). |
NPTEL Course Topper - Cloud Computing and Distributed Systems | 2023 | NPTEL, IIT Kanpur | Elite Gold certificate (87% score), ranked in Top 5% (Jan-Mar 2023 session). |
Featured in Newspapers | Various (2021-2023) | Multiple English & Telugu Newspapers (e.g., Sakshi, Andhra Jyothy, Eenadu, Prajasakti, Andhra Prabha, Surya, Vaartha, Kurukshetram) | Featured for AI innovations and national-level achievements, including ICDSAI award and UIF selection (reportedly 4 times in over 30 articles). |
Stanford Change Forward Journal Feature | 2021-2022 | University Innovation Fellows, Stanford University | MITS Code platform featured for student-driven innovation. |
Cultural Achievement - Short Film Contest Winner | 2022 | MITS Cultural Tech Fest (MITS Film Makers Club-Student Activity Center) | 1st Prize in Short Film Contest (December 17, 2022). |
Certifications
Nitish holds several professional certifications, demonstrating a commitment to continuous learning and skill development in various technology domains. These certifications from recognized organizations validate his expertise in areas crucial for AI/ML and software engineering.
Certification Title | Issuing Organization | Date Earned |
---|---|---|
Microsoft Certified: Power BI Data Analyst Associate | Microsoft | March 10, 2023 |
Microsoft Certified: Azure Security Engineer Associate | Microsoft | March 27, 2023 |
Google Data Analytics Professional Certificate | Google (via Coursera) | October 20, 2023 |
Business Analytics & Text Mining Modeling Using Python (Elite Gold, Top 5%, 91%) | NPTEL (IIT Roorkee) | Jul-Sep 2023 (8-week course) |
Cloud Computing and Distributed Systems (Elite Gold, Top 5%, 87%) | NPTEL (IIT Kanpur) | Jan-Mar 2023 (8-week course) |
Design Thinking | Stanford University | (Part of UIF Program, 2021 cohort) |
Digital Image Processing (Virtual Exchange Program) | Asia University, Taiwan | Spring Semester 2023 (Feb 13, 2023 - Jun 24, 2023; certificate issued June 16, 2023) |
RPA Foundation | Wipro (via FutureSkills Prime & TalentNext) | August 12, 2024 |
Technical Skills
Nitish's technical expertise encompasses a range of programming languages, frameworks, cloud platforms, databases, and AI/ML tools. These skills are demonstrated through his project work and professional experience.
- Languages: Python, Java, JavaScript, TypeScript, SQL, HTML, CSS
- Frameworks & Tools: React.js, Next.js, Node.js, FastAPI, Flask, Prisma, Tailwind CSS, GitHub Actions
- Cloud & Platforms: AWS (SageMaker, Lambda), Firebase, Docker
- Databases: PostgreSQL, MySQL, Oracle, MongoDB
- AI/ML: TensorFlow, PyTorch, Hugging Face, Scikit-learn, Keras, Pandas, NumPy, Matplotlib
Social media profiles
LinkedIn : https://www.linkedin.com/in/sine-nitish-b9b421204
Twitter : https://twitter.com/NitishSine?s=08
Facebook : https://www.facebook.com/profile.php?id=100010450815645
Instagram : https://www.instagram.com/sine_nitish?r=nametag
Github : https://github.com/SineNitish
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