Fatemeh Shah-Mohammadi | Clinical Data Science | Best Researcher Award

Dr. Fatemeh Shah-Mohammadi | Clinical Data Science | Best Researcher Award

Dr. Fatemeh Shah-Mohammadi at University of Utah, United States

 Professional Profiles👨‍🎓

 Early Academic Pursuits 🎓

Dr. Fatemeh Shah-Mohammadi completed her Master of Science in Electrical and Communication Engineering at Birjand University of Technology, where she laid the groundwork for her expertise in engineering and technology. She then pursued her PhD at Rochester Institute of Technology, specializing in Machine Learning. Her dissertation focused on “Machine Learning-enabled Resource Allocation in Underlay Cognitive Radio Networks,” demonstrating her commitment to applying advanced technologies in innovative ways.

Professional Endeavors 💼

Dr. Shah-Mohammadi currently serves as a Research Assistant Professor of Biomedical Informatics at the University of Utah, where she applies her skills in health informatics and clinical data science. Her professional journey includes significant roles as a Biostatistician II/NLP Engineer at Mount Sinai Health System and a postdoctoral fellow at the Icahn School of Medicine. These experiences have equipped her with a robust foundation in data analysis and machine learning applications across diverse domains.

Contributions and Research Focus 🔍

Dr. Shah-Mohammadi’s research primarily centers on the intersection of health informatics and machine learning. She has developed machine learning models that leverage cross-domain datasets to improve clinical outcomes. Notable projects include NLP-assisted pipelines for clinical note analysis and differential diagnosis, highlighting her dedication to enhancing healthcare delivery through technology.

Impact and Influence 🌍

Dr. Shah-Mohammadi’s work has significant implications for health informatics, particularly in the use of natural language processing (NLP) for clinical applications. Her publications in respected journals, such as the IEEE Open Journal of the Communications Society and Studies in Health Technology and Informatics, showcase her contributions to advancing knowledge in this field. Her research efforts aim to reduce diagnostic uncertainty and improve patient care outcomes, underscoring her influence in biomedical informatics.

Academic Cites 📚

Dr. Shah-Mohammadi’s scholarly output includes multiple peer-reviewed articles that have garnered citations and recognition within the academic community. Her ORCID and Google Scholar profiles further highlight her impact, showcasing a growing body of work that contributes to the fields of health informatics and machine learning.

Technical Skills 🛠️

Dr. Shah-Mohammadi is proficient in various technical areas, including:

  • Machine Learning and Data Science
  • Natural Language Processing
  • Statistical Analysis
  • Software Development for Biomedical Applications Her expertise enables her to build and implement sophisticated models that address real-world clinical challenges.

Teaching Experience 👩‍🏫

As an instructor at the University of Utah, Dr. Shah-Mohammadi teaches courses like “Generative AI in Healthcare” and “Intro to Programming.” Her teaching philosophy emphasizes the integration of cutting-edge technology with foundational principles, preparing students for future challenges in biomedical informatics.

Grants and Funding 💰

Dr. Shah-Mohammadi has actively sought and secured funding for her research initiatives. As the Principal Investigator for a project on automated live meta-analysis of clinical outcomes using generative AI, she demonstrates leadership in advancing research in health informatics. Her involvement as a co-investigator in various projects further highlights her collaborative spirit and dedication to impactful research.

Legacy and Future Contributions 🌟

Looking ahead, Dr. Shah-Mohammadi aims to continue her work at the forefront of health informatics, leveraging machine learning and NLP to drive innovations in clinical practice. Her commitment to research, teaching, and community engagement positions her as a leading figure in the field, poised to make lasting contributions to both academia and healthcare.

📖 Top Noted Publications 

 Addressing Semantic Variability in Clinical Outcome Reporting Using Large Language Models

Authors: Fatemeh Shah-Mohammadi, Joseph Finkelstein
Journal: BioMedInformatics
Year: 2024

 Extraction of Substance Use Information From Clinical Notes: Generative Pretrained Transformer–Based Investigation

Authors: Fatemeh Shah-Mohammadi, Joseph Finkelstein
Journal: JMIR Medical Informatics
Year: 2024

Accuracy Evaluation of GPT-Assisted Differential Diagnosis in Emergency Department

Authors: Fatemeh Shah-Mohammadi, Joseph Finkelstein
Journal: Diagnostics
Year: 2024

Neural Network Cognitive Engine for Autonomous and Distributed Underlay Dynamic Spectrum Access

Authors: Fatemeh Shah-Mohammadi, Hatem Hussein Enaami, Andres Kwasinski
Journal: IEEE Open Journal of the Communications Society
Year: 2021

 NLP-Assisted Differential Diagnosis of Chronic Obstructive Pulmonary Disease Exacerbation

Authors: Fatemeh Shah-Mohammadi, Joseph Finkelstein
Journal: Studies in Health Technology and Informatics
Year: 2024

Using Electronic Medical Records and Clinical Notes to Predict the Outcome of Opioid Treatment Program

Authors: W Cui, Fatemeh Shah-Mohammadi, Joseph Finkelstein
Journal: Healthcare Transformation with Informatics and Artificial Intelligence
Year: 2023

Milla Vehviläinen | Data collection | Best Researcher Award

Ms. Milla Vehviläinen | Data collection | Best Researcher Award

Ms. Milla Vehviläinen at VTT Technical Research Centre of Finland, Finland

👨‍🎓 Profile

📜 Summary

Milla Vehviläinen is a dedicated research scientist specializing in electromobility. She has extensive experience in computational modeling and simulation of electromechanical powertrains, contributing to both academic research and practical applications in electrical engineering.

🎓 Education

Milla is pursuing a D.Sc. (Tech) at Aalto University in Espoo, Finland, expected to complete in Q4/2025, focusing on computational modeling with a GPA of 4.6/5.0. She earned her M.Sc. (Tech) in Mechatronic System Design from LUT University, Lappeenranta, in 2020, with a GPA of 4.2/5.0. Her academic journey began with a B.Sc. (Tech) in Mechanical Engineering from LUT University, where she graduated in 2018 with a GPA of 3.1/5.0.

💼 Professional Experience

Currently, Milla works as a Research Scientist at VTT in Espoo (since 09/2020), focusing on computational modeling and simulation of electromechanical systems. Previously, she was a Research Trainee at VTT (07/2020 – 09/2020), where she developed a simulation toolbox for smart electric vehicle systems. Milla also has experience as an R&D Engineer Trainee at ABB Oy in Helsinki, working on product development for wind generators (05/2018 – 04/2020), and as a Sales Engineer Trainee in spare parts sales (05/2017 – 04/2018). She started her career as a trainee at Way Structural Technology Oy, contributing to 3D design projects for power plants (05/2016 – 06/2016).

📚 Academic Citations

Milla has authored several peer-reviewed publications, including: “Adapting geometry-based polygonal contacts for simulating faulty rolling bearing dynamics” in Mechanism and Machines Theory (2024) and “Simulation-Based Comparative Assessment of a Multi-Speed Transmission for an E-Retrofitted Heavy-Duty Truck” in Energies (2022).

⚙️ Technical Skills

Milla is skilled in MBS dynamics, 3D CAD, and condition monitoring. She is proficient in programming languages such as Python and VBA, and she has experience with software tools like Siemens NX, Teamcenter, SAP, and Tekla.

🔬 Research Interests

Milla’s research interests include electromechanical systems, electromobility, and fault detection and monitoring in electrical systems.

📖 Top Noted Publications 

Adapting geometry-based polygonal contacts for simulating faulty rolling bearing dynamics
  • Authors: Milla Vehviläinen, Pekka Rahkola, Janne Keränen, Jari Halme, Jussi Sopanen, Olli Liukkonen, Antti Holopainen, Kari Tammi, Anouar Belahcen
  • Journal: Mechanism and Machine Theory
  • Year: 2024
Simulation-Based Comparative Assessment of a Multi-Speed Transmission for an E-Retrofitted Heavy-Duty Truck
  • Authors: Milla Vehviläinen, Pekka Rahkola, Janne Keränen, Jenni Pippuri-Mäkeläinen, Marko Paakkinen, Jukka Pellinen, Kari Tammi, Anouar Belahcen
  • Journal: Energies
  • Year: 2022