Prof. Alina Nechyporenko | Healthcare Awards | Best Researcher Award

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Prof. Alina Nechyporenko | Healthcare Awards | Best Researcher Award

Prof. Alina Nechyporenko, Technische Hochschule Wildau, Germany

Dr. Alina Nechyporenko is an accomplished scientist and professor specializing in pattern recognition, biomedical signal processing, and data mining. Currently, she serves as a Scientist and Reader at the Technical University of Applied Sciences Wildau, Germany, where she works in the Department of Molecular Biotechnology and Functional Genome Analysis. She has also been a Professor at Kharkiv National University of Radio Electronics in Ukraine since 2018, contributing to the Faculty of Computer Science and the Department of Systems Engineering. Dr. Nechyporenko has over 70 publications in peer-reviewed journals and holds five patents. She is an expert evaluator for ISO/TC 276 Biotechnology and has been involved in several high-impact research projects, including Horizon2020, COST actions, and Erasmus+ initiatives. Her current research focuses on biomedical research, machine learning, and data management, with significant contributions to European life-science research and microbiome studies.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award

Alina Nechyporenko is a highly accomplished researcher in the fields of Pattern Recognition, Biomedical Signal Processing, and Machine Learning, with an extensive academic and professional background. She has demonstrated significant contributions to biomedical research, particularly in the application of data mining and computational techniques in cancer therapy, microbiome research, and deep learning. Given her work and leadership in her respective fields, she is highly suitable for the Best Researcher Award.

Education and Training

  • Expert in Evaluation Competences
    • Member of ISO/TC 276 Biotechnology, WG 2, WG 5, and national TC 166 “Clinical laboratory studies and systems for in vitro diagnostics.”
    • Technical Committee and Reviewer for the UKRCON IEEE conference.
  • Ph.D. in Computer Science
    • Specialization in Biomedical Signal Processing and Pattern Recognition
    • Thesis focused on data management and machine learning applications.
  • Publications and Patents
    • Over 70 publications in peer-reviewed scientific journals
    • Holder of 5 patents related to biomedical and computational applications.

Work Experience

2019 – Present

  • Scientist and Reader for Pattern Recognition, Biomedical Signal Processing
    • Technical University of Applied Sciences Wildau, Germany
    • Conducting research in areas such as data mining, machine learning, and data management within the Department of Molecular Biotechnology and Functional Genome Analysis.
    • Participates in Horizon2020 grant agreement ID: 654156 (RItrain – Research Infrastructures Training Programme), COST CA15110 (Harmonising standardisation strategies in European life-science research), and Erasmus + Capacity-building projects.
    • Engaged in COST CA18131 (Statistical and machine learning techniques in human microbiome studies) and DAAD “Digital Ukraine: Ensuring academic success in times of crisis” projects (2022 – 2025).

Since 2018

  • Professor
    • Kharkiv National University of Radio Electronics, Ukraine
    • Faculty of Computer Science & Department of Systems Engineering
    • Involved in teaching and research, focusing on pattern recognition, data processing, and systems engineering.

Publication top Notes:

Modeling and Computer Simulation of Nanocomplexation for Cancer Therapy

Comparison of CNN-Based Architectures for Detection of Different Object Classes

Comparison of CNN-Based Architectures for Detection of Different Object Classe

Advancing microbiome research with machine learning: key findings from the ML4Microbiome COST action

Classification of Microbiome Data from Type 2 Diabetes Mellitus Individuals with Deep Learning Image Recognition

Intelligent Decision Support System for Differential Diagnosis of Chronic Odontogenic Rhinosinusitis Based on U-Net Segmentation

Mr. Fulin Cai | Patient Monitor Award | Best Researcher Award

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Mr. Fulin Cai | Patient Monitor Award | Best Researcher Award 

Mr. Fulin Cai, Arizona State University, United States

Fulin Cai is a dedicated Ph.D. student in Computer Engineering at Arizona State University (ASU) under the supervision of Teresa Wu, with a research focus on deep learning, medical signals, and healthcare. He earned his M.S. in Computer Engineering from ASU with a GPA of 3.86/4.0 in 2023. Prior to this, he completed an M.S. in Management Science and Engineering and a B.S. in Information Management and Information System from Shenzhen University (SZU), ranking high in his class. Fulin’s research has led to numerous publications in prestigious journals such as IEEE Sensors Journal and Frontiers in Physiology, with topics ranging from radar sensing to respiratory function monitoring. He has also presented his work at notable conferences like the Institute of Industrial and Systems Engineers (IISE) Annual Conference.

Professional Profile:

ORCID

Education 🎓

  • Arizona State University (ASU), Tempe, USA
    • Ph.D. Student in Computer Engineering (08/2020 – Present)
    • Supervisor: Teresa Wu
    • Research Interests: Deep Learning, Medical Signals, Healthcare
  • Arizona State University (ASU), Tempe, USA
    • M.S. in Computer Engineering, GPA: 3.86/4.0 (05/2023)
  • Shenzhen University (SZU), Shenzhen, China
    • M.S. in Management Science and Engineering, GPA: 86/100 (Rank 3) (06/2019)
    • Supervisors: Li Li and Xianghua Chu
    • Research Interests: Meta Learning, Reinforcement Learning, Optimization
  • Shenzhen University (SZU), Shenzhen, China
    • B.S. in Information Management and Information System, GPA: 3.56/4.0 (Rank 4) (06/2016)

Teaching Experience 👨‍🏫

  • Arizona State University, Tempe, USA
    • Information Systems Engineering (Spring 2024)
  • Shenzhen University (SZU), Shenzhen, China
    • Lecturer, College of Continuing Education:
      • Management Information System Analysis and Design (03/2017-06/2017)
      • Website Construction and Management (09/2017-12/2017)
      • E-commerce Technology (03/2018-06/2018)
      • Management Information System (03/2019-06/2019)
    • TA, Online Course: Living with Etiquette (03/2017-06/2018)

Working Experience 💼

  • Arizona State University, Tempe, USA (08/2020-Present)
    • Position: Graduate Research Assistant
    • Research Topic: Enhanced representation learning for human biosensing applications
    • Responsibilities:
      • Apply computer vision models to human biosensing applications (e.g., ECG for sleep apnea, radar data for physiological measurement and motion detection).
      • Improve representation learning of DL models from time and frequency perspectives when bio signal is treated as a spectrogram (1-channel image).
  • Huawei Technologies Co., Ltd, Shenzhen, China (07/2019-07/2020)
    • Position: Algorithm Engineer
    • Responsibilities:
      • Implementation of automatic channel selection algorithm.
      • Development of channel simulation software based on NS-3.

Academic Services 📝

  • Journal Reviewer:
    • Computers in Biology and Medicine
    • Biomedical Signal Processing and Control
    • Computers & Industrial Engineering
    • International Journal of Production Research
    • Quality and Reliability Engineering International

Publication top Notes:

E-BDL: Enhanced Band-Dependent Learning Framework for Augmented Radar Sensing

Corrections to “STRIDE: Systematic Radar Intelligence Analysis for ADRD Risk Evaluation With Gait Signature Simulation and Deep Learning” [May 23 10998-11006]

STRIDE: Systematic Radar Intelligence Analysis for ADRD Risk Evaluation With Gait Signature Simulation and Deep Learning

Cross-Trained Worker Assignment Problem in Cellular Manufacturing System Using Swarm Intelligence Metaheuristics

Prof Dr. Markus Sigrist | Medical Detectors | Best Researcher Award

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Prof Dr. Markus Sigrist | Medical Detectors | Best Researcher Award

Prof Dr. Markus Sigrist, ETH Zürich, Switzerland

Markus W. Sigrist, born on September 6, 1948, in Illnau, Zurich, Switzerland, is a distinguished physicist renowned for his contributions to laser spectroscopy and sensing. He pursued his education at ETH Zurich, earning a diploma (Master) degree in physics in 1972, followed by a Ph.D. in 1977 with a thesis on laser-generated stress waves in liquids. Postdoctoral research took him to the University of California at Berkeley from 1978 to 1980. Returning to ETH Zurich, he held various academic positions, achieving his habilitation in 1985. His career included a sabbatical as a guest professor at Rice University in Houston in 1990 and later becoming an adjunct professor there from 1994 to 2013. As a professor of experimental physics at ETH Zurich from 1995 to 2013, he led the Laser Spectroscopy and Sensing Group, pioneering research in laser development and spectroscopy for diverse applications, including medical, forensic, environmental, and industrial fields. Post-retirement, he remains Professor Emeritus at ETH and has served as a guest professor in France and a foreign expert in China. Sigrist’s prolific research encompasses mid-IR laser spectroscopic sensing for medical diagnostics, environmental monitoring, and the development of advanced laser sources and detection schemes. He has mentored numerous Ph.D. and M.Sc. students, contributing significantly to the academic community through his supervision and examination of over 50 Ph.D. theses.

Professional Profile

🎓 Education:

  • Studied physics at ETH Zurich
  • Master’s degree (Diploma) in 1972
  • PhD in 1977 with the thesis “Laser-generated stress waves in liquids”

🧑‍🔬 Employment History:

  • 1978-1980: Postdoctoral Fellow at the University of California, Berkeley, USA
  • Since 1980: Various positions at ETH Zurich
  • 1985: Habilitation thesis, received docent degree (Privatdozent) at ETH Zurich
  • 1990: Sabbatical as Guest Professor at Rice University, Houston, Texas, USA
  • 1995-2013: Professor for Experimental Physics at ETH Zurich, Head of the Laser Spectroscopy and Sensing Group within the Institute for Quantum Electronics
  • 1994-2013: Adjunct Professor at Rice University
  • 2013: Retired, Professor Emeritus of ETH Zurich
  • 2003 and 2011: Guest Professor at Université du Littoral Côte d’Opale, Dunkerque, France
  • 2014-2017: Foreign Expert at the Chinese Academy of Sciences, Hefei, China

🔬 Research Activities:

  • Medical & Forensic Analysis: Mid-IR laser spectroscopic sensing for breath and surgical smoke analysis, non-invasive glucose sensing, doping agent detection in urine, drug detection in saliva
  • Environmental & Industrial Applications: Laser spectroscopic sensing for environmental, industrial, and agricultural uses
  • Laser Development: Broadly tunable narrowband infrared laser sources including CO, CO₂, semiconductor lasers (QCLs, lead salt VECSELs), optical parametric oscillators, difference frequency generation
  • Detection Schemes: Photoacoustic, photothermal, multi-pass, cavity-ringdown, fiberoptic methods for trace gases and liquids
  • Trace Gas Monitoring: Laser-spectroscopic systems
  • Laser-Interaction Studies: Interaction with solids, liquids, and gases
  • Non-Destructive Testing: Noncontact studies on adhesion strength of surface coatings

🎓 Supervision:

  • Supervised 23 PhD students and numerous MSc students at ETH Zurich
  • Acted as co-expert and examiner for over 50 PhD theses internationally

Publications Notes:📄

Stable Gaseous Isotope Measurement Method Based on Highly Sensitive Laser Absorption Spectroscopy and Its Applications

Non-dispersive sensing scheme based on mid-infrared LED and differential mode excitation photoacoustic spectroscopy

Multi-component gas measurement aliasing spectral demodulation method for interference separation in laser absorption spectroscopy

A sensitive carbon monoxide sensor for industrial process control based on laser absorption spectroscopy with a 2.3 μm distributed feedback laser

Monitoring of peroxy radicals by chemical amplification enhanced photoacoustic spectroscopy