Dr. Siwei Guan | Deep Learning Award | Best Researcher Award

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Dr. Siwei Guan | Deep Learning Award | Best Researcher Award

Dr. Siwei Guan, Hangzhou Dianzi university, China

Dr. Siwei Guan, currently pursuing a Doctorate in Electronic Science and Technology at Hangzhou Dianzi University, China, stands at the forefront of groundbreaking research in anomaly detection. With a Master’s degree from the same university and a Bachelor’s from Jiangxi Normal University, his expertise shines in innovative approaches to multivariate time series data. Driven by a passion for advancement, his work, published in esteemed journals like Computer & Security and IEEE Sensors Journal, showcases pioneering techniques utilizing variational autoencoders and temporal neural networks. Supported by prestigious funding from the National Key Research and Development Program of China and the National Natural Science Foundation of China, he actively contributes to peer review activities, ensuring the quality of academic discourse. Dr. Guan’s dedication and achievements underscore his invaluable contributions to electronic science and technology, propelling the field forward with each innovative stride. 🌟

Professional Profile:

Orcid

🏫 Education:

Dr. Siwei Guan is currently pursuing a Doctorate in Electronic Science and Technology at Hangzhou Dianzi University, China, building upon his prior academic achievements. He holds a Master’s degree in Electronic Information from the same university and completed his Bachelor’s in Electronic Information Engineering at Jiangxi Normal University. His research focuses on innovative approaches to anomaly detection in multivariate time series data, as evidenced by his publications in reputable journals like Computer & Security and IEEE Sensors Journal.

💼 Work & Research:

As a Doctoral candidate, Dr. Siwei Guan is actively engaged in groundbreaking research, including the development of novel anomaly detection techniques using variational autoencoders and temporal neural networks. His work has received significant funding from prestigious institutions, including the National Key Research and Development Program of China and the National Natural Science Foundation of China. Additionally, he contributes to the academic community through peer review activities for esteemed journals such as Exper System with Application and ISA Transactions.

📊 Funding & Peer Review:

Dr. Siwei Guan has successfully secured funding to support his research endeavors, demonstrating the recognition and significance of his work in the field. Furthermore, his involvement in peer review activities reflects his commitment to advancing the scientific knowledge and contributing to the quality of research publications.

🌟 Achievements:

Dr. Siwei Guan’s contributions to the field of electronic science and technology have earned him recognition and support from prestigious funding programs and academic journals. With his dedication to innovative research and scholarly pursuits, he continues to make valuable contributions to the advancement of anomaly detection methodologies in multivariate time series data.

Publication Top Notes:

  1. Multivariate time series anomaly detection with variational autoencoder and spatial–temporal graph network
    • Published in Computers & Security, April 2024.
  2. Conditional normalizing flow for multivariate time series anomaly detection
    • Published in ISA Transactions, December 2023.
  3. TPAD: Temporal-Pattern-Based Neural Network Model for Anomaly Detection in Multivariate Time Series
    • Published in IEEE Sensors Journal, December 15, 2023.
  4. GTAD: Graph and Temporal Neural Network for Multivariate Time Series Anomaly Detection
    • Published in Entropy, May 2022.

 

 

 

 

 

Dr. Venkata Lakshmi S | AI in Networking | Women Researcher Award

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Dr. Venkata Lakshmi S | AI in Networking | Women Researcher Award

Dr. Venkata Lakshmi S, Sri Krishna College of Engineering and Technology, India

Dr. Venkata Lakshmi S, a seasoned professional with 20 years of experience, currently serves as the Professor and Head of the Department of Artificial Intelligence and Data Science at Sri Krishna College of Engineering and Technology, Coimbatore. Holding a Ph.D. in Computer Science and Engineering from Manonmaniam Sundaranar University, she has contributed significantly to academia with roles such as Assistant Professor and Head of the Department in esteemed institutions. Dr. Venkata Lakshmi has a diverse portfolio of subjects she has taught, including Data Warehousing, Cryptography, Wireless Sensor Networks, and more. Her research interests span machine learning, image processing, and AI applications in diverse fields. She has guided numerous impactful projects, ranging from agricultural crop yield prediction to breast cancer detection using advanced technologies. Apart from her academic prowess, Dr. Venkata Lakshmi actively engages with industry through MOUs, internships, and campus connect lectures. Her commitment to quality education is evident through her roles as a mentor, evaluator, and active involvement in various academic committees and initiatives.

🌐 Professional Profiles :

Google Scholar

📚 Education:

  • Ph.D. in Computer Science and Engineering from Manonmaniam Sundaranar University (2011-2018)
  • M.E. in Computer Science and Engineering from Dr.MGR Deemed University, Chennai (2003-2005)
  • B.E. in Computer Science and Engineering from The Indian Engineering College, Manonmaniam Sundaranar University, Tirunelveli (1995-1999)

👩‍💼 Professional Experience:

  • Professor and Head of the Department at Sri Krishna College of Engineering and Technology, Coimbatore (July 2020 – Present)
  • Assistant Professor Grade I at Panimalar Institute of Technology, Chennai (May 2014 – April 2020)
  • Assistant Professor at Vel Tech Dr.RR & Dr.SR Technical University, Chennai (January 2006 – May 2013)
  • Lecturer at various esteemed institutions from 1999 to 2006

🔍 Projects:

  • Voice and Video Conferencing Security
  • Agricultural Crop Yield Prediction
  • Bitcoin Prognosis
  • Secure Visual Authentication using QR Code

🎓 Guided Projects:

  • Machine Learning for Agricultural Crop Yield Prediction
  • Linear Support Vector Machine for Chronic Kidney Disease
  • Sentiment Analysis using Contextual Based Approaches

📜 Certifications:

  • “A Crash Course in Data Science” – Coursera
  • “Data Science for Engineers” – NPTEL
  • “Data Warehousing and Business Intelligence” – Coursera
  • “AI for Everyone” – Coursera
  • “Oracle Cloud Infrastructure Foundations 2021 certified Associate” – Oracle

💻 Programming Languages:

  • C, C++
  • VB, .NET, MS-Access, SQL Server

🤝 Industry Interaction:

  • MoU with Payoda
  • Internships for students with Payoda and DeepVisionTech.AI
  • Campus Connect Lectures with DeepVisionTech.AI

🌐 Additional Responsibilities:

  • Social and Media Coordinator for Toycathon
  • Chief Editor of Magazine BUZZ
  • Incharge of NAAC criteria 3
  • Question Paper Setter for premier institutions
  • Coordinator for various committees, including ECell and Quality Improvement Cell

🌟 Achievements:

  • Recognized as a mentor and expert in various national initiatives
  • Actively involved in enhancing student learning experiences through industry collaborations and innovative projects.

Publications Top Notes  :

  1. “A Review study of E-waste management in India”
  2. “Query optimization using clustering and genetic algorithm for distributed databases”
  3. “Combined effect of biopriming and polymer coating on chemical constituents of root exudation in chilli (Capsicum annuum L.) cv. K 2 seedlings”
  4. “Micropropagation and in vitro flowering of an ornamental aquarium plant Lindernia antipoda (L.) Alston”
  5. “Sinonasal schwannoma with secondary changes”

 

 

 

 

 

Farshad Bolouri | Artificial Intelligence | Best Researcher Award

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Mr Farshad Bolouri: Artificial Intelligence | Best Researcher Award

Research Associate at Texas Tech University, United States

Farshad Bolouri is an accomplished researcher with a Master’s degree in Electrical Engineering from Texas Tech University, specializing in Computer Vision, Machine Learning, Robotic Perception, and Remote Sensing. His research interests focus on Agricultural Robotics, Precision Farming, and Machine Learning in Digital Agriculture.

🌐 Professional Profiles:

🎓 Education : 

Farshad Bolouri, a mastermind in Electrical Engineering, graduated with a Master of Science from Texas Tech University in August ’23 🎓. His stellar GPA of 3.86 reflects his dedication to his studies, with a focus on cutting-edge fields like Computer Vision, Machine Learning, Robotic Perception, and Remote Sensing 🌐🤖.

Prior to his master’s journey, Farshad excelled in his Bachelor’s in Computer Engineering, graduating Summa Cum Laude with a perfect GPA of 4.0 in May ’21 🏆. He added a touch of diversity with a minor in Mathematics and Computer Science, earning accolades such as the Highest Ranking Graduate from the College of Engineering and the ‘Outstanding Design Project’ award from ECE 🏅🔧.

Farshad’s academic journey is not just about grades; it’s a testament to his passion for pushing boundaries and achieving excellence in the realm of technology and engineering 🚀.

🔍 Research Interests : 

Farshad Bolouri’s research interests are a captivating blend of technology and agriculture 🌾. In the realm of Agricultural Robotics and Precision Farming, he’s delving into the development of custom robotic solutions. His focus lies on intelligent multi-sensor integration, aiming to optimize in-field plant phenotyping specifically for specialty crops 🤖🌱. Venturing into the realm of Machine Learning in Digital Agriculture, Farshad applies cutting-edge AI/ML techniques for data interpretation. His goal is to enable accurate high-throughput phenotyping and precise yield estimation, revolutionizing the way we approach modern farming practices 📊🌾. In the domain of 3D Computer Vision for Field Mapping, Farshad employs advanced techniques for accurate and real-time field mapping. By integrating 3D computer vision, he aims to enhance the precision and efficiency of agricultural decision-making processes 🌐🚜.

Research Focus:

Farshad Bolouri’s research focus spans across Agricultural Robotics and Precision Farming 🌾, as evident in his groundbreaking work on “CottonSense.” This High-Throughput Field Phenotyping System leverages intelligent multi-sensor integration for optimized cotton fruit segmentation and enumeration on edge devices, revolutionizing cotton farming practices 🤖🌱. Additionally, his contribution to improving short-term multiphase production forecasts in unconventional tight oil reservoirs showcases a keen interest in merging technology with geoenergy science and engineering ⛽🔍. Farshad’s commitment to advancing phenotyping for flower abortion in soybeans through image analysis and machine learning demonstrates a versatile expertise in the intersection of agriculture, computer vision, and AI 🌺🔬.

Publications Top Notes  :
  • CottonSense: A high-throughput field phenotyping system for cotton fruit segmentation and enumeration on edge devices