Assoc Prof Dr. Saeed Emami | Network Optimization | Best Researcher Award

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Assoc Prof Dr. Saeed Emami | Network Optimization | Best Researcher Award

Prof Dr. Saeed Emami, Babol Noshirvani University of Technology, Iran

Dr. Saeed Emami is an Associate Professor in the Department of Industrial Engineering at Babol Noshirvani University of Technology, Iran. He received his Ph.D. in Industrial Engineering from Isfahan University of Technology in 2015, focusing on order acceptance and scheduling problems in make-to-order systems. With a strong background in optimization and uncertainty, his research interests span various areas, including robust optimization, production planning, facility planning, and supply chain management. As Vice-Chancellor of the Faculty of Materials and Industrial Engineering since January 2020, he plays a key role in academic leadership. With a wealth of teaching experience in engineering courses, he also serves as a supervisor and advisor for numerous master’s theses, addressing diverse topics such as healthcare scheduling, cloud manufacturing, and green supply chain planning. Emami’s contributions extend to the development and application of metaheuristic algorithms, simulation, and multi-criteria decision-making in industrial engineering.

🌐 Professional Profiles : 

Google Scholar

Scopus

Orcid

🎓 Education:

    • Ph.D. in Industrial Engineering, Isfahan University of Technology, Iran (2015)
    • M.S. in Industrial Engineering, Isfahan University of Technology, Iran (2008)
    • B.S. in Industrial Engineering, Isfahan University of Technology, Iran (2004)

📚 Teaching Experience:

  • Courses at Babol Noshirvani University of Technology since 2010
    • Engineering Economy, Probability theory, Statistics
    • Computer Applications in Industrial Engineering, Production planning
    • Linear algebra, Simulation, Decision analysis
    • Inventory control, Decision making in healthcare systems
    • Computer simulation, modeling, and optimization, Combinatorial optimization

🏭 Work Experience:

  • Current Position: Associate Professor at Babol Noshirvani University of Technology (since Sep 2015)
  • Supervisor of Master Theses: Diverse topics in Industrial Engineering, including nurse scheduling in the Covid-19 pandemic and integrated production and distribution planning in a green closed-loop supply chain.
  • Advisor of Master Theses: Covering areas like home health care service planning, flexible flow shop scheduling, order acceptance in make-to-order systems, and more.

🧠 Research Interests:

Dr. Saeed Emami, an accomplished Associate Professor at Babol Noshirvani University of Technology, is deeply immersed in the realms of industrial engineering. His intellectual pursuits span a diverse spectrum, from the intricacies of optimization and robust techniques to the art of decomposition algorithms like Benders and Lagrangian relaxation. With a keen focus on production planning, scheduling, and facility planning, he navigates the complexities of supply chain management, employing metaheuristic algorithms such as Nested Partition and Genetic approaches. Dr. Emami’s academic canvas is further enriched by his exploration of simulation methodologies and the nuanced landscape of multi-criteria decision making. 🌐📊

📚 Publication Impact and Citations : 

Scopus Metrics:

  • 📝 Publications: 19 documents indexed in Scopus.
  • 📊 Citations: A total of 345 citations for his publications, reflecting the widespread impact and recognition of Dr. Saeed Emami’s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 471 📖
    • h-index: 9 📊
    • i10-index: 9 🔍
  • Since 2018:
    • Citations: 417 📖
    • h-index: 8 📊
    • i10-index: 8 🔍

👨‍🏫 A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. 🌐🔬

Publications Top Notes  :

  1. Multi-objective Fuzzy Robust Optimization Approach to Sustainable Closed-Loop Supply Chain Network Design
    • Authors: S Nayeri, MM Paydar, E Asadi-Gangeraj, S Emami
    • Published Year: 2020
    • Journal: Computers & Industrial Engineering
    • Cited By: 141
  2. Managing a new multi-objective model for the dynamic facility layout problem
    • Authors: S Emami, AS Nookabadi
    • Published Year: 2013
    • Journal: International Journal of Advanced Manufacturing Technology
    • Cited By: 82
  3. Wheat sustainable supply chain network design with forecasted demand by simulation
    • Authors: F Motevalli-Taher, MM Paydar, S Emami
    • Published Year: 2020
    • Journal: Computers and Electronics in Agriculture
    • Cited By: 55
  4. A Benders decomposition approach for order acceptance and scheduling problem: a robust optimization approach
    • Authors: S Emami, G Moslehi, M Sabbagh
    • Published Year: 2017
    • Journal: Computational and Applied Mathematics
    • Cited By: 37
  5. Metaheuristic algorithms to allocate and schedule of the rescue units in the natural disaster with fatigue effect
    • Authors: S Nayeri, E Asadi-Gangraj, S Emami
    • Published Year: 2019
    • Journal: Neural Computing and Applications
    • Cited By: 30

 

 

 

 

 

 

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”

 

 

 

 

 

Mrs. Mahdieh Ghasemlou | Network Optimization | Best Researcher Award

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Mrs. Mahdieh Ghasemlou | Network Optimization | Best Researcher Award

Mrs. Mahdieh Ghasemlou, University of Birjand, Iran

👩‍🎓 Mrs. Mahdieh Ghasemlou is a Ph.D. student in Electrical Engineering-Communications Technology at the University of Birjand, Iran, embarking on a scholarly journey with a focus on “NOMA multi-user transceivers for 5G mobile communication networks.” 🌐 Under the guidance of mentors Dr. Nasser Neda and Dr. Jalil Seifali Harsini, her dedication to advancing knowledge in electrical engineering is evident. 🚀 Prior to her Ph.D., Mahdieh achieved a Master of Science in Electrical Engineering-Communications from the Islamic Azad University Tehran South branch in Tehran, Iran. 📚 Her academic commitment extends to cutting-edge areas like NOMA and 5G communication networks. 💡 As a devoted researcher, Mahdieh explores a diverse spectrum of wireless communications, including ultra-wideband (UWB) techniques for ranging and localization, signal processing innovations, and resource management strategies in NOMA systems. 📡 Her multifaceted expertise significantly contributes to the dynamic evolution of wireless technologies. 🌟

🎓 Education : 

🎓 Mrs. Mahdieh Ghasemlou is currently on a scholarly pursuit as a Ph.D. student in Electrical Engineering-Communications Technology at the University of Birjand, Iran. 🌐 Her doctoral thesis, titled “NOMA multi-user transceivers for 5G mobile communication networks,” is under the supervision of esteemed mentors Dr. Nasser Neda and Dr. Jalil Seifali Harsini. 📚 Prior to her Ph.D., Mahdieh earned a Master of Science in Electrical Engineering-Communications from the Islamic Azad University Tehran South branch in Tehran, Iran, in February 2013. 🚀 Her academic journey reflects a deep commitment to advancing knowledge in the field of electrical engineering, particularly in cutting-edge areas like NOMA and 5G communication networks. 📡💡

🌐 Professional Profiles : 

Google Scholar

🧠 Research Interests 🔬🌐 :

📡 Mrs. Mahdieh Ghasemlou is a dedicated researcher with a broad spectrum of interests spanning the dynamic field of wireless communications. 🌐 Her expertise encompasses ultra-wideband (UWB) communications, where she explores advanced techniques for ranging and localization. 📶💬 Mahdieh’s proficiency extends to signal processing, delving into innovative approaches to enhance communication systems. 💡 Moreover, her research interests include NOMA systems (Non-Orthogonal Multiple Access), focusing on optimizing resource management strategies for improved efficiency and performance. 🚀 With a diverse range of interests, Mahdieh contributes significantly to the evolving landscape of wireless technologies and signal processing. 🌟

Publications Top Notes  :

1.  An improved method for TOA estimation in TH-UWB system considering multipath effects and interference

Publication Source: JOURNAL OF INFORMATION SYSTEMS AND TELECOMMUNICATION (JIST) 2 (15), 23-29

Year: 2014, Cited By: 2

2.  A New Method of TOA Estimation in TH_UWB Systems with Multipath Channel and in the Presence of interference

Publication Source: IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING 21, 1-6

Year: 2013, Cited By: 1