Mr. Rishik Gupta, Texas A&M University, United States
Mr. Rishik Gupta is an emerging talent in the field of Computer Science, currently pursuing his Masterโs degree at Texas A&M University, USA. With a strong foundation built at Maharaja Surajmal Institute of Technology and the Indian Institute of Technology Madras, he has shown exceptional promise in machine learning, natural language processing, computer vision, and audio signal processing. His professional experience includes impactful roles at the Defence Research and Development Organization (DRDO), AI Shala Technologies, and Growna EdTech, where he demonstrated his ability to develop high-performance AI systems. Rishik has authored research papers, developed NLP models with over 95% accuracy, and created scalable software solutions. His academic journey is marked by dedication, innovation, and cross-disciplinary collaboration. ๐๐๐ก
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๐ Suitability for Best Researcher Awardย
Mr. Rishik Gupta is highly deserving of the Best Researcher Award due to his outstanding contributions to applied machine learning, natural language processing, and intelligent systems. His work at DRDO led to the development of high-accuracy traffic classification models, while at AI Shala, he designed an NLP model achieving 95%+ accuracy in distinguishing AI-generated text. Rishik demonstrates not only technical skill but innovation and academic rigor, reflected in his publications and custom dataset designs. He bridges academia and industry with real-world applications and research, and his custom GPT model and smart attendance system further showcase his creativity and problem-solving ability. Rishik represents the next generation of researchers pushing the frontier of AI and computer science. ๐ง ๐
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๐ Educationย
Mr. Rishik Gupta is currently enrolled in the Master of Computer Science program at Texas A&M University (Aug 2024 โ May 2026), where he continues to deepen his expertise in artificial intelligence and software systems. He completed his Bachelor of Technology in Computer Science and Engineering from Maharaja Surajmal Institute of Technology, Delhi (2020โ2024). Simultaneously, he studied at the Indian Institute of Technology Madras from Sep 2021 to Dec 2023, gaining exposure to advanced courses and research environments. His academic journey reflects a strategic blend of technical depth, cross-institutional learning, and interdisciplinary exploration in AI, machine learning, and computer vision. ๐๐งโ๐ป๐
๐ผ Experienceย
Rishik has amassed hands-on research and development experience across prominent organizations. At DRDO, he built advanced machine learning models for network traffic classification, collaborating with senior scientists to improve accuracy and efficiency. At AI Shala Technologies, he designed an innovative NLP model capable of detecting AI-generated content, integrating BERT and perplexity-based analysis. His tenure at Growna EdTech showcased his software engineering skills, where he developed a scalable Android application with significant business impact. Each role highlights his interdisciplinary talent in ML, NLP, software development, and project execution, bridging theoretical knowledge with practical application. ๐งโ๐ฌ๐ป๐ค
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Awards and Honorsย
While still early in his academic and professional career, Rishik has been recognized for his high-impact work through collaborative research publications, top internship selections, and notable project contributions. His model at DRDO surpassed standard benchmarks with over 90% accuracy, and his AI Shala project achieved 95% accuracy, both earning internal commendation. His software at Growna EdTech played a pivotal role in securing a major client, boosting revenue by 60%, a rare feat for an intern-led project. His academic excellence has also earned him admission to the prestigious Texas A&M University and IIT Madras programs. More accolades are expected as his promising career progresses. ๐ฅ๐๐
๐ฌ Research Focus
Mr. Gupta’s research is focused on the intersection of Machine Learning, Efficient Search & Retrieval, Natural Language Processing, Computer Vision, and Audio Signal Processing. His work involves both theoretical exploration and real-world implementation of AI systems, including generative models, transformer architectures, semantic analysis, and facial recognition systems. He emphasizes the creation of scalable, high-performance solutions such as smart attendance tracking using facial recognition and custom GPT-style language models. His interest in audio signal processing and text classification expands his multidisciplinary relevance, while his projects reflect innovation, practical utility, and algorithmic efficiency. He seeks to create AI tools that are impactful, interpretable, and adaptable to varied use cases. ๐ค๐ก๐ฃ๏ธ๐ท๐ถ
๐ย Publication Top Notes
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ASKSQL: Enabling Cost-Effective Natural Language to SQL Conversion for Enhanced Analytics and Search
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Integrated Smart Attendance Tracker Using YOLOv8 and FaceNet with Spotify ANNOY
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Pronunciation Scoring With Goodness of Pronunciation and Dynamic Time Warping
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SwinAnomaly: Real-Time Video Anomaly Detection Using Video Swin Transformer and SORT