Hajar Hakkoum | Machine learning | Best Scholar Award

Posted on 12/03/2024 by ScienceFather

Dr. Hajar Hakkoum | Machine learning |Best Scholar Award

Profile Summary

In my current role as a Postdoctoral Researcher at INRAE in Versailles, France, I specialize in plant cell cycle dynamics through image analysis and compressed fluorescence acquisition. As a Software Engineer at IS Technologies, Courbevoie, France, I contributed to robust server-side components, integrated AI APIs, and enhanced search engine recommendation systems. My Ph.D. in Machine Learning Interpretability from ENSIAS, UM5*, Rabat, involved groundbreaking research in medical AI, including mentoring fellow researchers and contributing to peer-reviewed journals. Proficient in Python, data mining, and deep learning, I possess strengths in scientific writing and presentation skills. Fluent in Arabic, English, French, Spanish, and German, I hold a C1 IELTS certification and received the Best Poster Award at the 15th International Conference on Health Informatics in 2022. Beyond my professional endeavors, I nurture a keen interest in languages, reading, and running. My educational background includes a Software Engineering Degree (Web & Mobile) from ENSIAS, UM5*, Rabat, and completion of Engineering Preparatory Classes at CPGE Salmane Al Faressi in Salé, Morocco.

Professional Profiles

Scopus Profile

📚 Education:

Software Engineering Degree (Web & Mobile): ENSIAS, UM5*, Rabat, MAR (2016-2019). Engineering Preparatory Classes: CPGE Salmane Al Faressi, Salé, MAR (2014-2016)

🔍 Professional Experience:

Postdoctoral Researcher INRAE, Versailles, FR (March 2024 – Present) Conducting image analysis of plant cell cycle dynamics. Implementing compressed fluorescence acquisition techniques.. Software Engineer IS Technologies, Courbevoie, FR (October 2022 – February 2024) Developing robust server-side components using ASP.NET and PostgreSQL. Analyzing and integrating AI APIs for text translation, camera filters, and ChatGPT. Enhancing search engine recommendation systems and assessing employee/user satisfaction using Python. PhD in Machine Learning Interpretability in Medicine ENSIAS, UM5, Rabat, MAR (January 2020 – April 2023) Conducting a systematic literature review on interpretability techniques in medicine. Quantitatively evaluating the interpretability of ML black-box models in medicine. Assessing the impact of categorical feature encoding on ML interpretability techniques in medicine. Guiding two new PhD students in research projects on ML interpretability in Biodiversity and Cybersecurity. Publishing research papers in reputable peer-reviewed journals and conferences emphasizing the significance of interpretability in medical AI. Contributing to the peer-review process within the medical AI domain as a reviewer for the Scientific African journal (Q2 with IF: 2.9). PhD Internship (ERASMUS) Facultad de Informática, Murcia, SP (January – June 2022) Investigating the impact of categorical data on interpretability techniques. Participating in interdisciplinary discussions to bridge the gap between ML and domain experts’ needs. Projects and Internships: Final Degree Project – Research Initiation: Interpretability of ANNs for breast cancer diagnosis (Python). Third Year Project – Handwritten Digits and French Numbers Image Recognition using CNNs and collected images (Python). Second Year Internship – ChatBot development for Banks Q/A (.NET). First Year Internship – Checks Amounts Validation for Banks (C#, Azure APIs).

🏆 Certificates:

IELTS: C1 (8.5 Reading & Listening, 7.5 Speaking, and 6.5 Writing). Best Poster Award: 15th International Conference on Health Informatics (2022)

🎯 Interests:

Languages: “A different language is a different vision of life.” Reading: “A reader lives a thousand lives before he dies.” Running: “Exercise is a tribute to the heart.”

📚Top Noted Publication

“Interpretability in the medical field: A systematic mapping and review study” (2022, Applied Soft Computing):
- This paper likely serves as a comprehensive review and mapping study on the topic of interpretability in the medical field, possibly summarizing existing research and identifying trends or gaps in the literature.

“Assessing and comparing interpretability techniques for artificial neural networks breast cancer classification” (2021, Computer Methods in Biomechanics and Biomedical Engineering):
- The focus here is on assessing and comparing interpretability techniques specifically applied to artificial neural networks for breast cancer classification. The paper likely delves into the methods used to make these complex models interpretable.

“Ensemble blood glucose prediction in diabetes mellitus: A review” (2022, Computers in Biology and Medicine):
- This study appears to be a review on ensemble methods for predicting blood glucose levels in the context of diabetes mellitus, exploring the various techniques employed in aggregating predictions for improved accuracy.

“Artificial neural networks interpretation using LIME for breast cancer diagnosis” (2020, Trends and Innovations in Information Systems and Technologies):
- This paper seems to focus on the interpretability of artificial neural networks for breast cancer diagnosis, specifically using the Local Interpretable Model-agnostic Explanations (LIME) technique.

“A Systematic Map of Interpretability in Medicine” (2022, HEALTHINF):
- This paper likely provides a systematic map, possibly a visual representation, of interpretability in medicine. It could outline the landscape of interpretability techniques, their applications, and potential challenges in the medical field.

“Global and local interpretability techniques of supervised machine learning black box models for numerical medical data” (2024, Engineering Applications of Artificial Intelligence):
- This study seems to explore both global and local interpretability techniques applied to supervised machine learning models for numerical medical data. The emphasis is likely on making black-box models more understandable and transparent.

“Evaluating Interpretability of Multilayer Perceptron and Support Vector Machines for Breast Cancer Classification” (2022 IEEE/ACS 19th International Conference on Computer Systems and…):
- This paper likely evaluates the interpretability of two different machine learning models, Multilayer Perceptron and Support Vector Machines, in the context of breast cancer classification.

Aldoushy Mahdy | Aquatic Ecology | Best Researcher Award

Posted on 04/01/202404/01/2024 by ScienceFather

Dr. Aldoushy Mahdy | Aquatic Ecology| Best Researcher Award

doctorate at Faculty of Science

👨‍🏫 Aldoushy Mahdy possesses a rich academic background rooted in Aquatic Ecology and Marine Biology, showcasing a trajectory of scholarly commitment and expertise. Having embarked on their educational journey from Al-Azhar University, they earned their B.Sc. in Marine Biology, excelling in their field. This was followed by an M.Sc. delving into taxonomical and ecological studies on marine zooplankton of the Red Sea, and eventually, culminated in a Ph.D. from Free University Berlin, Germany, exploring the intricate food webs in shallow lakes.🐠

With an illustrious teaching career spanning years, ranging from General Zoology to Marine Ecology, their expertise extends beyond academia. Dr. Mahdy’s research interests encompass various facets of Aquatic Ecology, including marine invertebrate natural products, lake trophic systems, echinoderm communities, and coral habitat preservation, all crucial for understanding and conserving aquatic ecosystems.🌿

Beyond their research and teaching, Dr. Mahdy has been actively involved in academic governance, quality assurance, and scientific management within their department and the broader scientific community. Their extensive fieldwork and regular visits to diverse marine habitats underscore their commitment to studying and preserving Egypt’s aquatic biodiversity. 🌍🔬

🌐 Professional Profiles

👨‍🎓 Education

PhD (2014) Free University Berlin, Germany. Research thesis: “Top-down and bottom-up effects in shallow lake food webs with special emphasis on periphyton”. M.Sc. (2005) Marine Biology Branch, Zoology Department, Faculty of Science, Al-Azhar University, Assiut, Egypt. Research thesis: “Taxonomical and ecological studies on marine zooplankton of the Red Sea, Egypt”. B.Sc. (1999) Marine Biology Branch, Zoology Department, Faculty of Science, Al-Azhar University, Assiut, Egypt (Excellent).

📚 Workshops, Training, and Conferences

July 26–29, 2019: Polyoxygenated Steroids from the Soft Coral Sinularia polydactyla Collected in the Egyptian Red Sea. MARINE DRUGS. Fourth International Conference on New Horizons in Basic and Applied Science (ICNHBAS 2019), Hurghada, Egypt. First aid and Medical Skills Workshop, Faculty of Science, Al-Azhar University, Assiut, Egypt. Chemical investigation of marine invertebrates and algae from the Red Sea. Natural compounds in cancer prevention and therapy, Naples, Italy. Marine Environment of the Red Sea: Problem and Solutions, Hurghada, Red Sea, Egypt. The role of Scientific Research in the Development of the Red Sea Fisheries and Environmental, Suez, Egypt. PACJA (Pan Africa Climate Justice Alliance) meeting, Addis Ababa, Ethiopia. Steroids from the Egyptian Red Sea soft coral Sinularia polydactyla. 10th European Conference on Marine Natural Products, Kolymbari, Crete, Greece. Environment and Fisheries of the Red Sea between reality and expectation, Hurghada, Egypt. Dugong dugong (Muller 1776) status, distribution and conservation with special emphasis on the Red Sea coast of Egypt. Third International Conference on New Horizons in Basic and Applied Science (ICNHBAS 2017), Hurghada, Egypt. Biodiversity of the river Nile and Lake Nasser, Egypt and how to make the fish stock assessment, management and their conservation, Al-Azhar University, Assiut Branch, Egypt. Fundamental of Remote Sensing, Faculty of Science, Al-Azhar University, Assiut Branch, Egypt. Ecological studies on zooplankton communities located off Megacities of the Red Sea, Egypt. Second International Conference on New Horizons in Basic and Applied Science (ICNHBAS2015), Hurghada, Egypt.

🏆 Fellowships and Research Grants Received

2018: Completed a Project Funded by the Ministry of Environmental Affair Agency (Project ID 00071131:3668). Covered topics: Coral Reef, Bird nesting, Bird winter survey, Sea dugong, Mangrove, Seagrass, Marine Turtle, and Spinner dolphin. 2009-2014: Awarded Post Graduate Scholarship by the Egyptian Government for a full PhD scholarship at Free University of Berlin, Germany, studying Aquatic Ecology.

🔍 Current Research Focus

Ecological studies of Aquatic Ecosystems focusing on physico-chemical parameters related to Biota, Marine Invertebrate natural products, Lake Trophic Systems, Survey of Echinoderm communities in Egypt’s marine waters, Role of protected areas in sustaining different coral habitats, Seagrass-associated communities, Marine zooplankton of the Red Sea

📚 Teaching Experiences

Taught courses including General Zoology, Invertebrate Zoology, Environmental Biology, Marine Benthos, Environmental Toxicology, Water Pollution and Toxicology, Marine Zooplankton, Oceanography, Marine Ecology, and Fauna.

🎓 Academic Activities

Member of the Department of Zoology council. Member of the Unit of Quality Assurance and Accreditation of Education. Management of scientific activities in the faculty of Science. Supervision of zoological museum and laboratories. Member of the Postgraduate committee in the Faculty. Member of the grants and mission committee in the Faculty.

🌍 Field Activities

Conducted expeditions to the Red Sea, Mediterranean Sea, and freshwater Lakes for ecological and biological studies of fauna. Regular visits to the Southern Red Sea and exploration of Egyptian habitats with the Youth Love Egypt Foundation.

💻 Technical and Practical Skills

Proficient in Word, Excel, Access, PowerPoint, Internet, statistical packages, SPSS, and holds Open Water Diver and Advanced Open Water Diver Certificates from PADI England.