Amir Lakizadeh | Bioinformatics | Best Researcher Award

Dr. Amir Lakizadeh | Bioinformatics | Best Researcher Award

Faculty Staff, University of Qom, Iran

Dr. Amir Lakizadeh is an accomplished researcher and Assistant Professor at the University of Qom, specializing in machine learning and deep learning. As the head of the AI-driven Pharma and Medicine (AIPM) lab, his work spans multimedia, medical diagnostics, and pharmaceutics. With over a decade of academic and industry experience, Dr. Lakizadeh is known for leading cutting-edge projects, mentoring future researchers, and advancing AI applications in drug discovery and healthcare. 🚀📊

Profile

Scopus

Google Scholar

Orcid

🎓 Education

Dr. Lakizadeh began his academic journey at the University of Tehran, where he earned his Bachelor’s (2001–2005) and Master’s (2005–2007) degrees in Computer Science, focusing on bioinformatics and machine learning. He later completed his Ph.D. in Computer Engineering at Tarbiat Modares University (2011–2016), with research centered on machine learning, computational systems biology, and bioinformatics. 🎓📚

💼 Experience

Since 2008, Dr. Lakizadeh has served as an Assistant Professor at the University of Qom, contributing significantly to research in AI, multimedia, and medical imaging. He has mentored over 70 postgraduate students and spearheaded 30+ research publications. As the current Head of the Computer Engineering and IT Department, he oversees 1000+ students, academic programs, and research initiatives. 🏛️🧑‍🏫

🔬 Research Interest

Dr. Lakizadeh’s research interests include deep learning, computer vision, digital pathology, drug repurposing, anticancer peptide prediction, and Alzheimer’s detection. He is passionate about creating AI-driven solutions for real-world medical and pharmaceutical challenges. His interdisciplinary work integrates data from biology, medicine, and computer science to deliver impactful innovation. 💡🧠💊

🏅 Awards

While specific honors aren’t listed, Dr. Lakizadeh’s leadership of high-impact AI projects, numerous peer-reviewed publications, and influential role in academia highlight his excellence and recognition in the fields of computer science and bioinformatics. He is a highly respected figure in interdisciplinary AI research. 🏆📘

📚 Publications

PU-GNN: A Positive-Unlabeled Learning Method for Polypharmacy Side-Effects Detection, International Journal of Intelligent Systems, 2024.
Cited by: Multiple future studies in drug safety prediction.

Drug Repurposing Using Hypergraph Embedding, Journal of Computational Biology, 2024.
Cited by: Studies in computational drug discovery.

GADNN: Graph Attention-based Drug Association Method, Informatics in Medicine Unlocked, 2024.
Cited by: Research in bioinformatics and AI.

Detection of Polypharmacy Side Effects via CNN, Molecular Diversity, 2022.
Cited by: Pharmacological safety frameworks.

Drug-Drug Interaction via GNN, Scientific Reports, 2022.
Cited by: Advanced machine learning in pharma.

ASDvit: Autism Classification using Vision Transformer, Intelligence-Based Medicine, 2025.
Cited by: Pediatric AI diagnostic tools.

Early Diagnosis of Alzheimer’s Disease via ResNet50 and FSBi-LSTM, Informatica, 2025.
Cited by: Neuroscience AI literature.

Face Hallucination via GAN, Journal of Electrical Systems, 2024.
Cited by: Vision-based AI modeling.

Power-Efficient IoT Optimization, Journal of Electrical Systems, 2024.
Cited by: Industrial Internet of Things (IIoT) research.

🏆 Conclusion

Dr. Amir Lakizadeh demonstrates all the hallmark qualities of a Best Researcher Award recipient—innovation, productivity, leadership, and real-world impact. His work seamlessly bridges foundational AI with urgent healthcare and societal applications. With a few strategic steps toward global engagement and open dissemination, his already impressive profile could set a benchmark for excellence.

Inga Christina Miadowicz | Computer Science and Artificial Intelligence | Best Researcher Award

Inga Christina Miadowicz | Computer Science and Artificial Intelligence | Best Researcher Award

Mrs Inga Christina Miadowicz, Deutsches Zentrum für Luft- und Raumfahrt, Germany

Dr. Inga Christina Miadowicz is a dedicated researcher specializing in IT management, industrial autonomy, and solar energy systems. She holds a Master’s in IT-Management from FOM Mannheim and a Bachelor’s in Applied Computer Science from DHBW Mannheim. Currently a Research Assistant at Deutsches Zentrum für Luft- und Raumfahrt (DLR), she leads projects in autonomous solar power plants and cyber-physical system infrastructures. Her expertise spans software engineering, distributed systems, and performance optimization. As a university lecturer at DHBW Mannheim, she teaches advanced software engineering and distributed systems. Her contributions to solar power plant digitization, industrial autonomy, and energy management have been published in renowned journals and conferences. She is an active participant in cutting-edge research on 5G communication for solar plants. With a strong foundation in IT architecture, cloud computing, and SAP technologies, she continues to drive innovation in the field of renewable energy and digital transformation. 🔬☀️🚀

Publication Profile

Orcid

Education

Dr. Inga Christina Miadowicz has a solid academic background in IT management and applied computer science. She earned her Master of Science in IT-Management (2018-2021) from Fachhochschule für Oekonomie und Management (FOM), Mannheim, where she specialized in enterprise IT strategies and digital transformation. Her Bachelor of Science in Applied Computer Science (2013-2016) from Duale Hochschule Baden-Württemberg (DHBW), Mannheim, provided her with hands-on experience in software development, system architecture, and distributed computing. She completed her Abitur (2004-2013) at Theodor-Fliedner-Gymnasium, Düsseldorf, establishing a strong foundation in STEM disciplines. Her commitment to continuous learning is reflected in multiple professional certifications, including Certified Business Professional and Certified Solution Professional (FICO), as well as specialized training in Apache Kafka, SAP HANA, SAPUI5, and OData services. Through her graduate program at DLR (since 2022), she continues to enhance her expertise in advanced IT solutions for industrial applications. 📚💡

Experience

Dr. Inga Christina Miadowicz has extensive experience in IT research, software development, and teaching. Since April 2022, she has been a Research Assistant at DLR (Cologne, Germany), leading projects on autonomous solar power plants and industrial autonomy. She has also served as a university lecturer at DHBW Mannheim (since 2018), teaching distributed systems and software engineering. Previously, she was a Lead Developer at FICO (2019-2022), where she developed anti-money laundering software and optimized performance engineering tools. As a Development Consultant at Slenderiser GmbH (2018-2019), she contributed to SAP S/4HANA transformations. Her tenure at SAP SE (2016-2018) focused on cloud and on-premise solutions for consumer industries. She also gained experience as a Dual Studies developer at ALDI SÜD (2013-2016), working on web and cloud computing solutions. Her diverse expertise in cyber-physical systems, SAP development, and IT architecture makes her a leading researcher in the field. 🚀🌞

Awards and Honors

Dr. Inga Christina Miadowicz has been recognized for her contributions to IT management, software engineering, and renewable energy research. She was awarded the Chinese Government Scholarship for her exceptional academic achievements. Her graduate program at DLR is a testament to her dedication to cutting-edge industrial research. She has received multiple professional certifications, including Certified Business Professional and Certified Solution Professional (FICO), as well as specialized SAP certifications like C_FIORIDEV_20. Her work on autonomous solar power plants and 5G communication for solar plants has been featured at prestigious conferences like SolarPACES. Her performance engineering contributions at FICO helped optimize anti-money laundering software, earning industry recognition. As a university lecturer, she has mentored numerous students in software development and distributed systems. Her commitment to research, education, and technological advancement positions her as a strong candidate for the Best Researcher Award. 🎖️📡☀️

Research Focus

Dr. Inga Christina Miadowicz focuses on industrial autonomy, digital transformation, and renewable energy optimization. At DLR, she leads research on autonomous solar power plants, developing cyber-physical systems and AI-driven automation for power plant operations. Her work integrates 5G communication networks with solar tower plants, enhancing real-time data processing and remote control capabilities. She specializes in distributed systems, software engineering, and cloud-based industrial solutions, particularly in SAP S/4HANA, Fiori applications, and performance engineering. Her research extends to data-driven hardware sizing tools, automation frameworks, and performance optimization for large-scale infrastructure. Her expertise in cybersecurity, IT architecture, and advanced analytics enables her to drive innovation in industrial digitalization. Through her publications in Solar Energy Advances and SolarPACES Conference Proceedings, she contributes to the advancement of solar energy integration and digital infrastructure for smart grids. Her work bridges the gap between IT, industrial automation, and sustainable energy solutions. 🌞📊💡

Publication Top Notes

📄 An Action Research Study on the Digital Transformation of Concentrated Solar Thermal PlantsSolar Energy Advances (2025)
📄 An Action Research Study on the Digital Transformation of Concentrated Solar Thermal PlantsSolar Energy Advances (2024-11-19)
📄 5G as Communication Platform for Solar Tower PlantsSolarPACES Conference Proceedings (2024-07-24)
📄 5G as Communication Platform for Solar Tower PlantsSolarPACES Conference Proceedings (2024-07-24, DOI: 10.52825/solarpaces.v2i.858)
📄 5G as Communication Platform for Solar Tower Plants29th International Conference on Concentrating Solar Power and Chemical Energy Systems, SolarPACES 2023

Ali Othman Albaji | Computer Science and Artificial Intelligence | Best Researcher Award

Ali Othman Albaji | Computer Science and Artificial Intelligence | Best Researcher Award

Dr Ali Othman Albaji, Libyan Authority for Scientific Research, Libya

With a Bachelor’s in Electrical Engineering and a Master’s in Electronics & Telecommunications from Universiti Teknologi Malaysia, this accomplished professional has extensive experience in academia and industry. Currently an Assistant Professor at the Higher College of Science and Technology in Libya, they also lead CR Technology System in the MENA region. Their research interests include optical wireless technologies and machine learning applications in environmental monitoring. Fluent in Arabic and English, with a diploma in Italian, they are also the President of the Postgraduate Student Society at UTM. 📡🎓🌍✍️

Publication profile

google scholar

Academic Background 

With a diverse academic journey, the individual holds a Master’s in Public Management and Leadership from the London School of Economics (LSE), UK, completed in 2010. They further pursued a Master in Electronics and Telecommunications at the University Technology Malaysia from 2019 to 2023. Their foundational education includes a Bachelor’s degree in Electrical Engineering, specializing in General Communications, from the Civil Aviation Higher College in Tripoli, Libya, earned in 2007. Additionally, they completed a Diploma in the Italian language during the 2011/2012 academic year. 🎓📡

Experience

Dr. Ali Othman Albaji boasts a diverse work history across reputable organizations. He started as a Sales Advisor at Akida Company (LG) and ZTE/Telecom China, honing his expertise in the telecommunications field. His academic journey includes significant roles as an Assistant Professor and lecturer in Electronics and Telecommunications. In addition to his teaching, he has demonstrated leadership as the Chairman of CR Technology System (CRTS Group) and the President of the Postgraduate Student Society at Universiti Teknologi Malaysia. Dr. Albaji’s commitment to both academia and industry underscores his dedication to advancing technology and education. 📡🎓💼🌟

Main Hard Skills 

Dr. Albaji possesses a robust set of technical skills, including proficiency in CAD Design, MATLAB Simulation Analysis, Python, and data visualization tools like Tableau. His capabilities extend to qualitative and quantitative analysis, SCADA systems, and programming languages like Verilog and HTML. These skills enable him to tackle complex research problems and contribute innovatively to his field. 

Languages 

Fluent in Arabic and English, with an IELTS Band Score of 8.5, Dr. Albaji also has a very good command of Italian. This linguistic proficiency allows him to collaborate with international researchers and disseminate his work to a broader audience. 

Research focus

Ali Othman Albaji’s research focus centers on machine learning applications in environmental noise classification, emphasizing smart cities and mobile communications. His work includes developing algorithms for monitoring and classifying noise pollution using MATLAB, contributing to urban planning and public health. He has also explored traffic noise impacts on residential areas and mobile telecommunications in Libya. His diverse research interests extend to the design and implementation of communication systems, highlighting the integration of technology in environmental studies. Through these contributions, Albaji aims to enhance noise management and promote sustainable urban environments. 🌍📊🔊📡

Publication top notes

Investigation on Machine Learning Approaches for Environmental Noise Classifications

A Machine Learning for Environmental Noise Monitoring and Classification Using Matlab

Machine Learning for Environmental Noise Classification in Smart Cities

Designing the Global System for Mobile Communications GSM-900 Cellular Network up to the Nominal Cell Plan in Tripoli, Libya

Conclusion and Recommendations

A Review of Traffic Highway Noise Towards Residential Area

NOISE POLLUTION DATA REPORTING AND WAREHOUSING USING TABLEAU SOFTWARE

Designing and Implementing a Signed Multiplier Radix-2 Using Booth’s Algorithm