Mamoona Khalid | Electrical and Information | Best Researcher Award

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Dr. Mamoona Khalid | Electrical and Information | Best Researcher Award

Lecturer at University of Engineering and Technology, Taxila, Pakistan

Dr. Mamoona Khalid is a dedicated lecturer and researcher in the Electrical Engineering Department at the University of Engineering and Technology (UET), Taxila, Pakistan, with over 15 years of teaching and research experience. She holds a Ph.D. in Electrical and Information Engineering from the University of South Australia, where her research focused on germanate waveguide lasers for infrared applications, resulting in multiple publications. An expert in photonics, optical waveguide fabrication, and laser material characterization, Dr. Khalid also serves as Director of the Photonics and Communications Lab at UET. She has been awarded prestigious scholarships, including the University President Scholarship, and has received significant research funding for lab development initiatives. Additionally, Dr. Khalid is an invited speaker and mentor, actively contributing to the academic and professional growth of her students and peers.

Profile:

Education:

Dr. Mamoona Khalid completed her Ph.D. in Electrical and Information Engineering from the University of South Australia, Adelaide, focusing on germanate waveguide lasers for shortwave to mid-infrared applications. Her Ph.D. research, guided by Prof. David G. Lancaster, culminated in the “Thesis by Publications” pathway, with four journal articles and two conference papers published during her studies. She earned her Master’s degree (MSc) in Electrical Engineering from the University of Engineering and Technology (UET), Taxila, where she was awarded a “Distinction” for her thesis on the mathematical modeling and simulation of light propagation through photonic crystal fibers, publishing four papers in HEC-recognized journals. Dr. Khalid graduated with a Bachelor’s degree (BSc) in Electrical Engineering from UET, Taxila, receiving a Gold Medal for her outstanding performance and earning a “High Distinction” with an overall grade of 83.47%.

Professional Experience:

Dr. Mamoona Khalid is a seasoned educator and researcher with over 15 years of experience in electrical engineering. Since 2008, she has served as a Lecturer in the Electrical Engineering Department at the University of Engineering and Technology (UET), Taxila, Pakistan. Her responsibilities include teaching undergraduate and postgraduate courses aligned with the Washington Accord’s Outcome-Based Education (OBE) accreditation standards. Dr. Khalid also supervises research projects for BSc, MSc, and Ph.D. students and is an HEC and Pakistan Engineering Council-approved Ph.D. supervisor. In her administrative role, she has been the Director of the Photonics and Communications Lab since 2022, and she actively mentors students while advising the UET Taxila branches of IEEE and SIEP. She also served as an AI Trainer for OpenAI in 2024, enhancing AI systems through training on large language models. Previously, she was a researcher and tutor at the University of South Australia, where she gained expertise in optical waveguide fabrication, femtosecond laser-based micromachining, and photonics labs.

Research Interests:

Dr. Mamoona Khalid’s research interests focus on advanced areas within electrical engineering, including photonics, optical communication, and laser material fabrication. Her expertise spans the fabrication and characterization of optical waveguides, femtosecond laser micromachining, and the development of fiber lasers and microchip lasers for infrared applications. She is skilled in designing optical communication links and utilizes cutting-edge techniques such as Ytterbium and Holmium doping in laser systems, absorption and fluorescence spectroscopy, and Optical Time Domain Reflectometry (OTDR) for fault detection. Dr. Khalid is also proficient in software and simulation tools including OptiSystem for optical link design, COMSOL Multiphysics, and photonic crystal fiber design using OptiFDTD, making significant contributions to laser material sciences and photonics engineering.

Skills:

Dr. Mamoona Khalid possesses a diverse set of technical skills that complement her expertise in electrical engineering and photonics. She has hands-on proficiency with lab equipment and techniques, including Ytterbium and Holmium doping in laser systems, fiber cleaving and splicing, brightfield microscopy, and optical-grade polishing of transparent materials. Her skills extend to using the Optical Time Domain Reflectometer (OTDR) for detecting faults in optical communication links, as well as designing advanced optical systems. Dr. Khalid is also adept in several specialized software tools, including OptiSystem for optical link design, RP fiber power for laser simulations, COMSOL Multiphysics, SCAPS for solar cell design, and Zemax for ray tracing. In programming, she is skilled in C++, Python, and MATLAB, enabling her to contribute robustly to both practical and computational aspects of research and development in her field.

Conclusion:

Dr. Mamoona Khalid’s extensive teaching and research experience, academic accomplishments, technical expertise, and contributions to photonics and AI make her a suitable candidate for the Best Researcher Award. Her dedication to research, education, and professional development demonstrates a commitment to advancing the field of Electrical Engineering and supporting the next generation of engineers.

Publication Top Noted:

  • Spectroscopic analysis and laser simulations of Yb³⁺/Ho³⁺ co-doped lead-germanate glass
    Authors: M Khalid, DG Lancaster, H Ebendorff-Heidepriem
    Journal: Optical Materials Express, Vol. 10, Issue 11, Pages 2819-2833
    Year: 2020
    Cited by: 17
  • Femtosecond laser induced low propagation loss waveguides in a lead-germanate glass for efficient lasing in near to mid-IR
    Authors: M Khalid, GY Chen, H Ebendorff-Heidepreim, DG Lancaster
    Journal: Scientific Reports, Vol. 11, Article 10742
    Year: 2021
    Cited by: 13
  • Microchip and ultra-fast laser inscribed waveguide lasers in Yb³⁺ germanate glass
    Authors: M Khalid, GY Chen, J Bei, H Ebendorff-Heidepriem, DG Lancaster
    Journal: Optical Materials Express, Vol. 9, Issue 8, Pages 3557-3564
    Year: 2019
    Cited by: 12
  • Germanate glass for laser applications in ∼ 2.1 μm spectral region: A review
    Authors: M Khalid, M Usman, I Arshad
    Journal: Heliyon, Vol. 9, Issue 1
    Year: 2023
    Cited by: 6
  • Long-range distributed vibration sensing using phase-sensitive forward optical transmission
    Authors: GY Chen, K Liu, X Rao, Y Wang, M Khalid, J He, Y Wang
    Journal: Optics Letters, Vol. 48, Issue 18, Pages 4825-4828
    Year: 2023
    Cited by: 4
  • Design and simulation of photonic crystal fibers to evaluate dispersion and confinement loss for wavelength division multiplexing systems
    Authors: M Khalid, I Arshad, M Zafarullah
    Journal: The Nucleus, Vol. 51, Issue 2, Pages 249-258
    Year: 2014
    Cited by: 3
  • Long-range distributed vibration sensing using phase-sensitive forward optical transmission: publisher’s note
    Authors: GY Chen, K Liu, X Rao, Y Wang, M Khalid, J He, Y Wang
    Journal: Optics Letters, Vol. 48, Issue 22, Page 5967
    Year: 2023
    Cited by: 2
  • Recent advancements in femtosecond laser inscribed waveguides in germanate glass for ∼ 2.1 µm laser applications
    Authors: M Khalid, M Usman, MA Nasir, I Arshad
    Journal: Optik, Vol. 273, Article 170462
    Year: 2023
    Cited by: 2
  • Estimation of low loss and dispersion of hollow core photonic crystal fiber designs for WDM systems
    Authors: M Khalid, I Arshad
    Journal: Electrical Engineering, Vol. 1, Issue 2, Page 1
    Year: 2014
    Cited by: 2

Elson Cibaku | Power Systems | Best Researcher Award

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Mr. Elson Cibaku | Power Systems | Best Researcher Award

Elson Cibaku at New Jersey Institute of Technology, United States

Summary:

Mr. Elson Cibaku is a dedicated researcher and PhD candidate in Industrial Engineering at the New Jersey Institute of Technology (NJIT), maintaining a perfect GPA of 4.0. He holds both a MSc and a BSc in Computer Science from the University of Tirana, Albania. At NJIT, Mr. Cibaku contributes to groundbreaking research in power systems, vaccine distribution, and optimization problems through advanced machine learning and deep learning methodologies, resulting in several impactful publications. His professional experience includes a role as Lead Software Engineer at Impala Digital in Tirana, Albania, where he significantly improved system performance and led the adoption of advanced technologies. Prior to that, he was a Senior Software Engineer at Facilization, where he led critical projects and received the Innovation Award in 2018 for his outstanding contributions to software development. Mr. Cibaku has also served as a lecturer at the University of Tirana, where he taught various computer science courses and engaged in collaborative research. Proficient in multiple programming languages and advanced technologies, Mr. Cibaku’s skills span machine learning, data processing, web development, and cloud services. His certifications include SQL business intelligence development and data modeling. Mr. Cibaku’s extensive academic and professional background highlights his expertise and commitment to advancing technology and data science.

Profile:

Education:

Mr. Elson Cibaku is currently pursuing a PhD in Industrial Engineering at the New Jersey Institute of Technology (NJIT), where he has achieved a perfect GPA of 4.0. His PhD coursework includes advanced topics such as Stochastic Programming, Machine Learning, Deep Learning, Reinforcement Learning, Statistical Methods in Data Science, Optimization Techniques for Data Engineering, Advanced Topics in Operations Research, Data Mining, and Supply Chain Engineering. Prior to his doctoral studies, he earned a MSc in Computer Science from the University of Tirana, Albania, with coursework in Parallel Programming, Coding Theory and Cryptographies, Advanced Operating Systems, Algorithmic, Object-Oriented Programming, Software Engineering, and Artificial Intelligence. Mr. Cibaku also holds a BSc in Computer Science from the University of Tirana, where he laid the foundation for his technical expertise and research skills.

Professional Experience:

Mr. Elson Cibaku has amassed extensive professional experience in both academic and industry settings. Currently, he serves as a Research Assistant at the New Jersey Institute of Technology (NJIT), where he collaborates on cutting-edge research projects, resulting in impactful papers on topics such as power systems, vaccine distribution, and optimization problems. From September 2021 to May 2023, he also worked as a Teaching Assistant at NJIT, where he developed instructional materials and conducted grading and assessment activities for various engineering courses. Prior to his time at NJIT, Mr. Cibaku was a Lead Software Engineer at Impala Digital in Tirana, Albania, from February 2021 to August 2021. In this role, he orchestrated tech stack adoption, led cross-functional teams, and developed a C# cache library that significantly improved system performance. Before that, he served as a Senior Software Engineer at Facilization from September 2013 to February 2021, where he led critical projects, such as developing a scalable backend for Virtual IBAN and optimizing SQL queries for the Bank of Albania’s Credit Registry, earning the Innovation Award in 2018. Additionally, Mr. Cibaku has experience as a Lecturer at the University of Tirana from October 2016 to August 2021, where he taught various computer science courses and supervised master and undergraduate students. His diverse professional background highlights his expertise in software engineering, research, and teaching, underscoring his commitment to advancing technology and data science.

Research Interests:

Mr. Elson Cibaku’s research interests lie at the intersection of industrial engineering, computer science, and data science. His current research focuses on leveraging advanced machine learning and deep learning methodologies to enhance efficiency in power systems, optimize vaccine distribution, and solve complex multi-pickup and delivery problems. He is particularly interested in the applications of graph attention networks, distributed optimization, and reinforcement learning in these domains. Additionally, Mr. Cibaku’s work encompasses statistical methods in data science, stochastic programming, optimization techniques for data engineering, and advanced topics in operations research. His diverse research portfolio reflects a strong commitment to addressing real-world challenges through innovative technological solutions.

Skills:

Mr. Elson Cibaku possesses a diverse and comprehensive skill set, underpinned by his proficiency in multiple programming languages including Python, C#, and Java. His expertise in machine learning spans supervised learning (regression and classification), deep learning (neural networks, transformers, generative models, transfer learning, and NLP models), unsupervised learning (clustering, dimensionality reduction, and anomaly detection), reinforcement learning (policy gradient methods, deep Q-learning, PPO, and TD learning), and generative adversarial networks. In data processing and visualization, Mr. Cibaku is adept with tools such as Tableau, Matplotlib, Looker Studio, and Power BI. His knowledge in data technologies encompasses data mining, the big data life cycle, Google Big Query, data warehousing, and data structures. In the realm of web development, he is skilled in .NET Core, ASP.NET Web API, and CQRS. His database management capabilities include working with relational databases (SQL Server, Oracle Database, and PostgreSQL), indexing strategies, data modeling, performance tuning, optimization, and NoSQL databases (MongoDB). Additionally, he is proficient in cloud services such as Microsoft Azure, Google Cloud Platform, and Amazon Web Services, and has experience with application servers including Keycloak, WildFly, NGINX, and Microsoft IIS. Other tools in his repertoire include Redis and DevExpress XAF. Mr. Cibaku holds several certifications, including MCSA: SQL 2016 Business Intelligence Development, MCPS: Microsoft Certified Professional, and certifications in implementing and developing data warehouses with Microsoft SQL Server. This extensive skill set positions him as a versatile and knowledgeable professional in the fields of computer science and data engineering.

Publications:

Boosting Efficiency in State Estimation of Power Systems by Leveraging Attention Mechanism

  • Authors: E. Cibaku, F. Gama, S. W. Park
  • Journal: Energy and AI
  • Volume: 16
  • Article Number: 100369