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. Haixu Liu | Computer Vision | Best Researcher Award

Mr. Haixu Liu | Computer Vision | Best Researcher Award

Mr. Haixu Liu, The University of Sydney, China

Mr. Haixu Liu is a highly skilled researcher with a robust background in data science, mathematics, and integrated circuit design. He is currently pursuing a Master of Data Science at The University of Sydney, Australia, where he specializes in computational statistical methods, machine learning, and deep learning. Previously, he served as a Research Assistant at Tsinghua University, leading innovative projects in circuit simulation and medical diagnostics using advanced machine learning techniques. His expertise spans Python-based data analysis, C++ algorithm design, and cutting-edge reinforcement learning optimization. Haixu has earned prestigious accolades, including the INFORMS Data Challenge 2024 and Kaggle competitions, reflecting his exceptional problem-solving abilities. His research contributions, such as optimizing Berkeley’s BSIM lookup table models, have significantly impacted large-scale integrated circuit design. With a passion for interdisciplinary innovation, Haixu continues to excel in academia and research, driving advancements in data science and engineering.

Professional Profile

Google Scholar

Suitability for Award

Mr. Haixu Liu exemplifies the qualities of a Best Researcher Award recipient through his outstanding contributions to data science and engineering. His research, particularly in optimizing integrated circuit designs and medical diagnostics, demonstrates groundbreaking innovation and technical expertise. Haixu’s ability to lead interdisciplinary projects, such as the Tsinghua Changgeng Hospital ABR diagnostic project, showcases his leadership and problem-solving skills. His achievements, including first-place finishes in international competitions like INFORMS 2024 and Kaggle’s Skin Cancer Detection challenge, highlight his global recognition and impact. Haixu’s work in developing scalable, efficient models has not only improved computational efficiency but also set new benchmarks in machine learning applications for engineering. His dedication to advancing technology and research excellence makes him a standout candidate for this prestigious award.

Education

Mr. Haixu Liu’s academic journey is marked by excellence and versatility. He is currently pursuing a Master of Data Science at The University of Sydney, Australia, where he focuses on advanced topics like computational statistical methods, deep learning, and data mining. He previously participated in an exchange program at the University of Regina, Canada, enriching his knowledge in algorithms, data structures, and artificial intelligence. Haixu holds a Bachelor of Science in Mathematics and Applied Mathematics from Chizhou University, China, where he gained a strong foundation in mathematical modeling, optimization, and programming. His diverse educational background equips him with interdisciplinary expertise, blending theoretical knowledge with practical applications in machine learning, circuit design, and data science.

Experience

Mr. Haixu Liu has a diverse professional background spanning academia and research. As a Research Assistant at Tsinghua University, he implemented advanced algorithms for chip design and circuit simulation, optimizing performance through machine learning and reinforcement learning techniques. His innovative work reduced model sizes and improved computational accuracy, resulting in award-winning publications. Haixu also led the ABR diagnostic project at Tsinghua Changgeng Hospital, where he developed advanced neural network models for medical diagnostics. His hands-on experience with Python, C++, and Rust underscores his technical proficiency in data analysis and algorithm design. Additionally, he has contributed to federated learning frameworks and industrial deployment schemes, showcasing his ability to translate research into real-world applications.

Awards and Honors

Mr. Haixu Liu’s achievements include first place in the INFORMS 2024 Data Challenge, reflecting his expertise in data science. He earned a bronze medal in Kaggle’s MICCAI ISIC Skin Cancer Detection competition, demonstrating his skill in applying machine learning to medical imaging. Haixu was a finalist in the IISE DAIS Case Study Competition 2024, further highlighting his problem-solving capabilities. His leadership roles as a committee and corresponding author for IJCAI and CIKM AnalytiCup challenges underscore his contributions to advancing research. These accolades reflect Haixu’s commitment to excellence and his ability to address complex challenges in data science and engineering.

Research Focus

Mr. Haixu Liu’s research focuses on applying machine learning and optimization algorithms to integrated circuit design, medical diagnostics, and data science challenges. He has developed efficient neural network models for circuit simulation, significantly reducing model size and improving accuracy. Haixu’s work in medical diagnostics includes enhancing ABR signal detection using advanced deep learning frameworks, demonstrating his interdisciplinary expertise. His research also extends to federated learning and model quantization, enabling scalable and privacy-preserving solutions. Haixu’s innovative approaches to data processing and algorithm design address critical challenges in computational efficiency and accuracy, contributing to advancements in engineering and healthcare applications.

Publication Top Notes:

  • DC-Model: A New Method for Assisting the Analog Circuit Optimization
    • Year: 2023
  • Automatic Recognition of Auditory Brainstem Response Waveforms Using a Deep Learning‐Based Framework
    • Year: 2024
  • Deep Neural Networks-Based Direct-Current Operation Prediction and Circuit Migration Design
    • Year: 2023
  • Topology Generic DC-Model for Accelerating Analog Circuit Optimization
    • Year: 2023
  • Probabilistic Calibration and Genetic Algorithm-Based Bank Credit Strategies for MSMEs and Enlightenment to Tobacco Enterprise Management
    • Year: 2021

 

Dr. Jiangning Zhang | Computer Vision | Best Researcher Award

Dr. Jiangning Zhang | Computer Vision | Best Researcher Award

Dr. Jiangning Zhang, Zhejiang University, China

Dr. Jiangning Zhang, a Principal Researcher at YouTu Lab, Tencent in Shanghai, holds a Ph.D. in Control Science and Engineering and an M.D. from Zhejiang University, as well as a B.S. in Electronic Information from Wuhan University. He leads the Industry Perception and AIGC teams, focusing on neural architecture design, particularly transformer-based and lightweight vision models. Dr. Zhang’s research spans multi-modal AIGC, including image and video generation, human-centric editing, and virtual digital human technologies, and extends to 3D scene segmentation with foundation models for visual anomaly classification. His work drives advancements in cutting-edge technologies and applications in artificial intelligence and computer vision.

Professional Profile:

Google Scholar

Suitability for the Award

Dr. Jiangning Zhang is highly suitable for the Best Researcher Award for the following reasons:

  1. Innovative Research Contributions:
    • Dr. Zhang’s work in neural architecture design and multi-modal generative models has advanced the field of computer vision and AI. His research on transformer-based architectures and lightweight vision models contributes to the efficiency and effectiveness of AI systems.
    • His involvement in developing multi-modal GANs, VAEs, and diffusion models for various applications, including 2D/3D digital human generation and motion generation, demonstrates significant innovation and impact in the field.
  2. High-Impact Publications:
    • Dr. Zhang has published influential papers in top-tier conferences such as ICCV and TIP, showcasing his contributions to cutting-edge research. His work on efficient attention-based models and anomaly detection reflects his expertise and impact on the academic community.
  3. Leadership and Influence:
    • As a Principal Researcher at Tencent’s YouTu Lab, Dr. Zhang leads teams working on industry perception and advanced AI-generated content, indicating his role in shaping future technologies and influencing both academic and industrial research.
  4. Relevance and Application:
    • Dr. Zhang’s research addresses practical and emerging challenges in AI, such as image/video generation, digital human reconstruction, and scene segmentation. His work has practical applications in various industries, enhancing its relevance and impact.

Educational Background 

Dr. Zhang earned his Ph.D. in Control Science and Engineering from Zhejiang University, Hangzhou, China, under the guidance of Prof. Yong Liu. He pursued his M.D. at the same institution and obtained his B.S. in Electronic Information from Wuhan University.

Current Position

Dr. Jiangning Zhang is a Principal Researcher leading the Industry Perception and AIGC teams at YouTu Lab, Tencent, Shanghai.

Research Interests 

  • Neural Architecture Design: Specializing in transformer-based architectures and lightweight vision models.
  • Multi-modal AIGC Research: Investigating image and video generation, human-centric editing, and 2D/3D virtual digital human technologies, including reconstruction and animation.
  • 3D Scene Segmentation: Utilizing foundation models for visual anomaly classification and segmentation.

Publication Top Notes:

  • Title: Omni-Frequency Channel-Selection Representations for Unsupervised Anomaly Detection
    • Year: 2023
    • Cited by: 96
  • Title: Rethinking Mobile Block for Efficient Attention-Based Models
    • Year: 2023
    • Cited by: 78
  • Title: Towards Open Vocabulary Learning: A Survey
    • Year: 2024
    • Cited by: 71
  • Title: Multimodal Industrial Anomaly Detection via Hybrid Fusion
    • Year: 2023
    • Cited by: 64
  • Title: Region-Aware Face Swapping
    • Year: 2022
    • Cited by: 56

 

 

Prof Dr. Chih-Hsien Hsia | AI in Computer Vision | Best Researcher Award

Prof Dr. Chih-Hsien Hsia | AI in Computer Vision | Best Researcher Award

Prof Dr. Chih-Hsien Hsia, National Ilan University, Taiwan

Prof. Dr. Hsia, a Distinguished Professor and Chairperson at National Ilan University’s Department of Computer Science and Information Engineering, holds dual Ph.D. degrees in Electrical and Computer Engineering from Tamkang University and National Cheng Kung University. His extensive career includes roles as a Postdoctoral Research Fellow, Assistant Professor, and Associate Professor, as well as Director of the Research Planning Division at NIU. Dr. Hsia’s research focuses on AI, multimedia processing, and DSP IC design, with significant contributions to foreground detection and background subtraction. His influential work is published in IEEE Transactions on Circuits and Systems for Video Technology. He has received the Outstanding Young Scholar Award and serves on editorial boards and advisory panels, underscoring his leadership and impact in the field.

Professional Profile:

Orcid
Scopus
Google Scholar

Suitability for the Award

Prof. Dr. Chih-Hsien Hsia is exceptionally suitable for the Research for Best Researcher Award due to his dual doctoral qualifications, impactful research in AI, multimedia, and DSP IC design, leadership in academic and professional organizations, and numerous honors recognizing his contributions to engineering and technology. His work bridges critical areas of modern technology, making significant strides in multimedia processing and cognitive engineering, which are essential in today’s digital and AI-driven world.

Academic Background:

Prof. Dr. Hsia holds dual Ph.D. degrees in Electrical and Computer Engineering from Tamkang University and National Cheng Kung University. His advanced education underscores his deep expertise and commitment to advancing knowledge in his field.

Professional Experience:

Dr. Hsia’s diverse professional experience includes roles as a Postdoctoral Research Fellow, Assistant Professor, and Associate Professor. He has held significant positions such as Director of the Research Planning Division at National Ilan University (NIU) and is currently a Distinguished Professor and Chairperson at NIU’s Department of Computer Science and Information Engineering. His roles reflect a robust career in both academic and research leadership.

Research Contributions:

His research interests span AI and General AI (GAI) in multimedia, DSP IC design, and cognitive engineering. Prof. Dr. Hsia has made notable contributions to foreground detection and background subtraction using advanced models, as evidenced by his influential papers in IEEE Transactions on Circuits and Systems for Video Technology. His work in hierarchical methods and multi-layer codebook models for moving object detection is particularly impactful, showcasing his expertise in multimedia processing and AI applications.

Awards and Honors:

Dr. Hsia has received prestigious awards such as the Outstanding Young Scholar Award from the Taiwan Association of Systems Science and Engineering and the Computer Society of the Republic of China. These accolades recognize his significant contributions to the field and his role as a leading researcher.

Editorial and Leadership Roles:

His service on various editorial boards and advisory panels, including roles as Associate Editor for Sensors and the Journal of Intelligent Communication, and as Chapter Chair of the IEEE Young Professionals Group, highlights his leadership and influence in the research community.

Publication Top Notes:

  • Title: Hierarchical Method for Foreground Detection Using Codebook Model
    • Year: 2011
    • Cited by: 135
  • Title: Fast Background Subtraction Based on a Multi-Layer CodeBook Model for Moving Object Detection
    • Year: 2013
    • Cited by: 119
  • Title: Enhancing Computational Thinking Capability of Preschool Children by Game-Based Smart Toys
    • Year: 2020
    • Cited by: 86
  • Title: Contact-Free Hand Geometry-Based Identification System
    • Year: 2012
    • Cited by: 86
  • Title: Memory-Efficient Hardware Architecture of 2-D Dual-Mode Lifting-Based Discrete Wavelet Transform
    • Year: 2012
    • Cited by: 84