Mr. Rishik Gupta | Computer Vision | Best Researcher Award

Mr. Rishik Gupta | Computer Vision | Best Researcher Award

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 Master’s 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. 🚀📚💡

🌍 Professional Profile 

Orcid

Google Scholar

🏆 Suitability for Best Researcher Award 

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. 🧠🏅📈

🎓 Education 

Mr. Rishik Gupta is currently enrolled in the Master of Computer Science program at Texas A&M University (Aug 2024 – 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 (2020–2024). 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. 🎓🧑‍💻📖

💼 Experience 

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. 🧑‍🔬💻🤝

🏅 Awards and Honors 

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. 🥇🏆📜

🔬 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. 🤖📡🗣️📷🎶

📊 Publication Top Notes

  • ASKSQL: Enabling Cost-Effective Natural Language to SQL Conversion for Enhanced Analytics and Search

    • Year: 2025
  • Integrated Smart Attendance Tracker Using YOLOv8 and FaceNet with Spotify ANNOY

    • Year: 2024

  • Pronunciation Scoring With Goodness of Pronunciation and Dynamic Time Warping

    • Year: 2023

  • SwinAnomaly: Real-Time Video Anomaly Detection Using Video Swin Transformer and SORT

    • Year: 2023

 

 

Mr. Gang Wei | Image Recognition | Best Researcher Award

Mr. Gang Wei | Image Recognition | Best Researcher Award

Mr. Gang Wei, Tongji University, China

Mr. Gang Wei is an accomplished researcher specializing in Computer Graphics, Geographic Information Systems (GIS), and Building Information Modeling (BIM). He holds a Ph.D. in Computer Application Technology from Tongji University, Shanghai, focusing on digital city visualization. With over two decades of experience at the CAD Research Center, Tongji University, he has significantly contributed to advancements in computer-aided design (CAD), artificial intelligence, and image recognition. His research explores 3D modeling, graphical interaction, and level-of-detail techniques for smart city applications. Mr. Wei’s expertise in integrating AI with GIS and BIM has led to innovative solutions for urban planning and digital infrastructure. His groundbreaking work continues to shape the future of computational design and intelligent visualization technologies.

🌍 Professional Profile 

Scopus

🏆 Suitability for Best Researcher Award

Mr. Gang Wei’s extensive contributions to computer graphics, GIS, and AI-driven visualization make him an excellent candidate for the Best Researcher Award. His pioneering work in digital city modeling, 3D visualization, and feature-based modeling has advanced computational methods for urban development. With over 20 years of research experience, he has played a crucial role in integrating AI-driven image recognition into GIS and CAD applications. His research enhances urban planning efficiency and digital infrastructure visualization, making him a leading figure in smart city development. Recognized for his expertise in building information modeling and computational graphics, Mr. Wei’s work aligns with cutting-edge technological advancements, making him a deserving recipient of this prestigious award.

🎓 Education 

Mr. Gang Wei completed his Ph.D. in Computer Application Technology at Tongji University, Shanghai (2008). His doctoral research focused on key technologies for digital city visualization, integrating GIS and 3D modeling to enhance urban digitalization. Prior to this, he earned a Master’s degree (2000) in Computer Application Technology from the same university, specializing in 3D solid modeling and graphical user interface design. His academic training has equipped him with expertise in computer-aided design (CAD), computer graphics, and feature-based modeling. His educational background provided a strong foundation for his contributions to AI-driven urban simulation, visualization technologies, and digital infrastructure modeling, making him a leader in computational design and geographic information systems.

💼 Experience 

Mr. Gang Wei has been an Associate Research Fellow at the CAD Research Center, Tongji University, Shanghai, since 2000. His career focuses on computer graphics, AI-driven GIS applications, and CAD-based modeling. He has led research on digital city visualization, AI-driven image recognition, and building information modeling (BIM), significantly impacting smart city development. His expertise in 3D visualization, level-of-detail modeling, and graphical interactions has improved digital infrastructure design and urban planning. Over two decades, he has collaborated on projects integrating AI with geographic data systems, enhancing real-time urban simulations. His work bridges AI, spatial data analytics, and computational design, contributing to technological innovations in urban digitalization and 3D city modeling.

🔬 Research Focus 

Mr. Gang Wei’s research focuses on AI-driven computer graphics, image recognition, and GIS-based digital city modeling. His work integrates machine learning with 3D visualization, improving real-time urban simulations. He specializes in feature-based modeling, level-of-detail (LoD) techniques, and CAD applications, enhancing smart city development. His expertise in AI-driven BIM has revolutionized building data management and infrastructure planning. He explores graphical interaction methods and spatial data integration, improving geospatial analytics. His research also includes automated 3D city reconstruction and real-time visualization algorithms, optimizing digital urban planning. Through AI-enhanced computational design and GIS modeling, Mr. Wei’s innovations contribute to smarter, more efficient urban digitalization and intelligent geospatial data analysis.

📊 Publication Top Note

AttenPoint: Exploring Point Cloud Segmentation Through Attention-Based Modules

 

Tayfun Abut | Methods and Algorithms | Best Researcher Award

Assist Prof. Tayfun Abut | Methods and Algorithms | Best Researcher Award

Assist Prof Dr. Tayfun Abut, Mus Alparslan University, Turkey

Dr. Tayfun Abut is an Assistant Professor of Mechanical Engineering at Mus Alparslan University. He earned his Doctoral and Master’s degrees from Firat University, where he also completed his Bachelor’s degree. Dr. Abut has held various academic and leadership positions, including Vice Dean and Head of Major Department, contributing significantly to his institution’s academic and administrative functions. His research focuses on control systems, haptic teleoperation, and dynamic analysis of mechanical systems, with numerous publications in reputable journals. Dr. Abut’s work has earned him several honors, including the Highly Commended Paper Award from Emerald Publishing and TÜBİTAK’s Publication Incentive Awards. He is dedicated to continuous learning, actively participating in workshops and training to further his expertise.

🌍 Professional Profile:

ORCID 
Scopus

🎓 Educational Background:

Dr. Tayfun Abut earned his Doctoral degree from Firat University’s Institute of Science on March 10, 2022. He previously obtained a Master’s degree (Thesis) from the same institution on August 27, 2015, and completed his Bachelor’s degree on June 15, 2012. His academic journey has been rooted in Firat University, where he has built a strong foundation in Mechanical Engineering.

💼 Experience:

Dr. Abut has a diverse range of academic positions. He started as a Research Assistant at Firat University’s Faculty of Engineering, specializing in Mechanical Theory and Dynamics. He continued his career at Mus Alparslan University, serving as a Research Assistant in the Department of Mechanical Engineering, focusing on System Dynamics and Control. Since August 5, 2022, Dr. Abut has been an Assistant Professor at Mus Alparslan University in the Department of Mechanical Engineering.

📚 Workshops and Training:

Dr. Abut’s work has been recognized with several honors and awards. Notably, he received the Highly Commended Paper Award from Emerald Publishing in 2020. He has also been awarded Publication Incentive Awards from TÜBİTAK in 2016 and 2017, highlighting his contributions to research and academic excellence.

🏅 Honors and Awards:

She has received several accolades, including the Outstanding Graduate Award from the School of International Education, Dalian University of Technology (2024), the DUT International Students Presidential Scholarship (full scholarship), and the Youth Star Award (2022). She also earned the Best Teacher Award for the 2018-2019 session from Sir Syed School, Wah Cantt, Pakistan, and a merit scholarship for her top performance in her MS and BS programs.

Publication Top Notes:

  • Real-time control and application with self-tuning PID-type fuzzy adaptive controller of an inverted pendulum
    • Year: 2019
    • Citations: 31
  • Haptic industrial robot control and bilateral teleoperation by using a virtual visual interface | Sanal bir görsel arayüz kullanarak haptik endüstriyel robot kontrolü ve iki yönlü teleoperasyon
    • Year: 2018
    • Citations: 6
  • Real-time control of bilateral teleoperation system with adaptive computed torque method
    • Year: 2017
    • Citations: 10
  • Haptic industrial robot control with variable time delayed bilateral teleoperation
    • Year: 2016
    • Citations: 18
  • Motion control in virtual reality based teleoperation system | Sanal Gerçeklik Tabanlı Teleoperasyon Sisteminde Hareket Kontrolü
    • Year: 2015
    • Citations: 2