PRADO, Seigfred V.

PRADO, Seigfred V.

Seigfred V. Prado boasts a rich academic journey, commencing with his attainment of a Bachelor of Science in Electronics Engineering (B.Sc. ECE) degree from the University of Santo Tomas (UST) in Manila, Philippines, in 2011. He furthered his academic pursuits with a Master of Science in Electronic Engineering (M.Sc. ELEG, with High Distinction) degree from The Hong Kong University of Science and Technology (HKUST) in Kowloon, Hong Kong, in 2015. In 2018, he earned a Master of Research in Neurotechnology (MRes NT, with High Merits) degree, followed by a Doctor of Philosophy in Bioengineering (Ph.D. BioEng; with a specialization in Neurotechnology) in 2024 from Imperial College London in England, United Kingdom. During his doctoral tenure at Imperial, Seigfred completed a distinguished research internship at Harvard Medical School, Harvard University, in collaboration with the Massachusetts General Hospital.

Beyond his academic achievements, Seigfred is a licensed Electronics Engineer and holds active memberships in various prestigious professional organizations, including the Institute of Electrical and Electronics Engineers (IEEE), where he is an elected Senior Member, the Institution of Engineering and Technology (IET), the Society for Neuroscience (SfN), the Federation of European Neuroscience Societies (FENS), the British Neuroscience Association (BNA), the Organization for Computational Neurosciences (OCNS), the Association of Biomedical Engineers, the International Society for Optics and Photonics, Asia-Pacific Chemical, Biological and Environmental Engineering Society (APCBEES), and the Institute of Electronics Engineers of the Philippines (IECEP). He is also an Associate Member of the National Research Council of the Philippines (NRCP). Recognized for his expertise, Seigfred has been invited as a plenary speaker at numerous international conferences and has contributed significantly to high-impact ISI/SCOPUS-indexed journals. His dedication to both teaching and research has garnered him multiple awards.

Seigfred’s research interests lie at the interface of signal and image processing, machine learning and artificial intelligence, biomedical photonics, neuroscience, and neurotechnology. More precisely, he desires to investigate within the topics of neural information processing and rehabilitation of neurodegenerative diseases such as Alzheimer’s disease.

Currently, Seigfred serves as the Executive Assistant for UST Santa Rosa, the Research, Innovation, and Entrepreneurship facility of the University of Santo Tomas. Additionally, he holds the position of Chair of the Faculty of Engineering Research Ethics Committee, demonstrating his commitment to upholding ethical standards in research and innovation.

Updates

Engr. Seigfred V. Prado, PhD, SMIEEE

Department of Electronics Engineering

svprado@ust.edu.ph

Academic Qualifications

Research Highlights

Research Interests

Academic Qualifications

Degrees

  • Doctor of Philosophy in Bioengineering (PhD BioEng, with a specialization in Neurotechnology), Imperial College London – England, United Kingdom
    • Doctoral Research Internship (Harvard Medical School – Harvard University and Massachusetts General Hospital, USA)
  • Master of Research in Neurotechnology (M.Res. NT with High Merits), Imperial College London – England, United Kingdom 
  • Master of Science in Electronic Engineering (M.Sc. ELEG with High Distinction), The Hong Kong University of Science and Technology – Kowloon, Hong Kong
  • Bachelor of Science in Electronics and Communications Engineering, University of Santo Tomas – Manila, Philippines  

Research Highlights

  • Neuroscience and Neurotechnology
    • Development of an In-Vivo Two-Photon Calcium Imaging Platform for the Characterization of Brain Circuit Dynamics in Neurodegenerative Diseases
    • Development of a Neuronal Source Extraction and Exploration (NeuroSEE) Tool for the Automated Analysis of Two-Photon Calcium Imaging Data
    • Hippocampal Imaging in Awake Alzheimer’s Disease Model Mice
    • Neural Manifold Analysis of Brain Circuit Dynamics in Neurodegenerative Diseases
    • Information and Graph-Theoretic Analyses of Brain Circuit Dynamics
    • Non-pharmaceutical neurorehabilitation
  • Biomedical Signal Processing
    • Characterization of EEG Signal Patterns During Visual Imageries for the Development of Brain-Computer Typing Interface for Locked-In Syndrome Patients
    • Development of an EEG-based Motor Imagery Brain-Computer Interface for Lower Limb Assistive Technologies
    • Characterization of Brain Signal During Deception
    • Characterization of EEG Signals for the Classification of the States of Stress
    • Nonlinear Signal Analysis of EEG Signals for Imagined Speech Recognition
    • Fall Detection Systems using sEMG
  • Speech Signal Processing
    • Rhinolalia Aperta Rudimentary Speech Recognition 

Research Interests

  • Neuroscience and Neurotechnology
    • Neural Coding
    • Neurological Disorders
      • Neurodegenerative Diseases (Alzheimer’s Disease, etc.)
      • Neurodevelopmental Disorders (Autism, ADHD, etc.)
      • Neuropsychiatric Disorders
    • Neurorehabilitation
  • Biomedical Signal Processing
    • Analysis of electrophysiological signals, e.g., EEG, ECG, EoG, EMG, etc.
    • Medical Image Analysis
  • Artificial Intelligence and Machine Learning
    • Artificial Neural Networks and Reinforcement Learning 

Courses Handled

Major Recognitions

Professional Activities

Courses Handled

  • Biomedical Imaging and Instrumentation
  • Digital Signal Processing
  • Engineering Data Analysis 
  • Probability Theory and Stochastic Processes
  • Digital Communications 
  • Embedded Systems and Automation
  • Electronic Devices and Circuit Theory
  • Logic Circuits and Switching Theory
  • Computer Systems Architecture

Major Recognitions

  • Teaching Excellence Award (Top 4), UST Faculty of Engineering, 2024
  • Special Citation Award, Magsaysay Future Engineers and Technologists Awards 2021, National Academy of Science and Technology (NAST)
  • IEEE Senior Member Award, Institute of Electrical and Electronics Engineers (IEEE)
  • Best Project of the Year Award, Bank of the Philippine Islands – Department of Science and Technology (BPI-DOST) Science Awards 2019
  • Best in Innovation Award, Bank of the Philippine Islands – Department of Science and Technology (BPI-DOST) Science Awards 2019
  • Best Presenter Award, 5-minute PhD Research Pitch Competition 2019, Imperial College London
  • High Merits Award, Master of Research in Neurotechnology, Imperial College London, 2019
  • Albertus Magnus Award for Outstanding Research, University of Santo Tomas, 2018
  • Best Paper Award, 9th IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, 2017
  • Benavides Outstanding Achievement Award, University of Santo Tomas, 2017
  • Albertus Magnus Award for Outstanding Research, University of Santo Tomas, 2017
  • Best Research Award, National Computer Research and Engineering Symposium, 2017
  • High Academic Distinction Award, Master of Science in Electronic Engineering, The Hong Kong University of Science and Technology, 2015
  • Top 1 Instructor Award, University of Santo Tomas, Office for Faculty Evaluation and Development, 2014 

Professional Activities

  • Executive Assistant, Assistant to the Rector for UST Santa Rosa (2022-present)
  • Senior Member, Institute of Electrical and Electronics Engineers (IEEE), IEEE Brain Society, IEEE Signal Processing Society, IEEE Engineering in Medicine and Biology Society, IEEE Life Sciences Community, IEEE Young Professionals
  • Associate Member, National Research Council of the Philippines (NRCP)
  • Professional Member, Institution of Engineering and Technology (IET)
  • Professional Member, Society for Neuroscience (SfN)
  • Professional Member, Federation of European Neuroscience Societies (FENS)
  • Professional Member, British Neuroscience Association (BNA)
  • Professional Member, Organization for Computational Neurosciences (OCNS)
  • Professional Member, Association of Biomedical Engineers
  • Professional Member, International Society for Optics and Photonics
  • Professional Member, Asia-Pacific Chemical, Biological and Environmental Engineering Society (APCBEES)
  • Professional Member, Institute of Electronics Engineers of the Philippines (IECEP) 

Selected Publications

Selected Publications

  • Cruz, J.A., Marquez, J.C., Mendoza, A.M., Reyes, J.I. and Prado, S.V., 2023, June. EEG-based Characterization and Classification of Severity for the Diagnosis of Post-Traumatic Stress Disorder (PTSD). In 2023 5th International Conference on Bio-engineering for Smart Technologies (BioSMART) (pp. 1-7). IEEE., https://doi.org/10.1109/BioSMART58455.2023.10162084
  • Calub, G.I.A., Elefante, E.N., Galisanao, J.C.A., Iguid, S.L.B.G., Salise, J.C. and Prado, S.V., 2023, June. EEG-Based Classification of Stages of Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI). In 2023 5th International Conference on Bio-engineering for Smart Technologies (BioSMART) (pp. 1-6). IEEE., https://doi.org/10.1109/BioSMART58455.2023.10162117
  • Prado, S., Mitchell-Heggs, R., Gava, G.P., Go, M.A. and Schultz, S.R., 2023. Neural manifold analysis of brain circuit dynamics in health and disease. Journal of Computational Neuroscience, 51(1), pp.1-21., https://doi.org/10.1007/s10827-022-00839-3
  • Go, M.A., Prado, S., Rogers, J., Gava, G.P., Davey, C.E., Liu, Y. and Schultz, S.R., 2021. Place cells in head-fixed mice navigating a floating real-world environment. Frontiers in cellular neuroscience, 15, p.19.,  https://doi.org/10.3389/fncel.2021.618658
  • Nieles, J.P.M., Magdaluyo, V.D.P., Mallari, L.B.A., Paliza, R.A.C., Salcedo, J.C.P. and Prado, S.V., 2018. Characterization of EEG Signal Patterns During Visual Imageries of Basic Structures for the Development of Brain-Computer Typing Interface for Locked-In Syndrome Patients. In 2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) (pp. 1-6). IEEE., DOI: 10.1109/HNICEM.2018.8666333
  • Castro, A.J.F., Cruzit, J.N.P., De Guzman, J.J.C., Pajarillo, J.J.T., Rilloraza, A.M.M., Nieles, J.P.M. and Prado, S.V., 2020, February. Development of a Deep Learning-Based Brain-Computer Interface for Visual Imagery Recognition. In 2020 16th IEEE International Colloquium on Signal Processing & Its Applications (CSPA) (pp. 166-170). IEEE., DOI: 10.1109/CSPA48992.2020.9068713
  • Ocampo, J.P.F.E., Dizon, J.A.T., Reyes, C.V.I., Capitulo, J.J.C., Tapang, J.K.G. and Prado, S.V., 2017, September. Evaluation of muscle fatigue degree using surface electromyography and accelerometer signals in fall detection systems. In 2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA) (pp. 21-26). IEEE., DOI: 10.1109/ICSIPA.2017.8120573
  • Berbano, A.E.U., Pengson, H.N.V., Razon, C.G.V., Tungcul, K.C.G. and Prado, S.V., 2017, September. Classification of stress into emotional, mental, physical and no stress using electroencephalogram signal analysis. In 2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA) (pp. 11-14). IEEE., DOI: 10.1109/ICSIPA.2017.8120571
  • Aguila, M.J., Basilio, H.D.V., Suarez, P.V.C., Dueñas, J.P.E. and Prado, S.V., 2017, January. Comparative study of linear and nonlinear features used in imagined vowels classification using a backpropagation neural network classifier. In Proceedings of the 7th International Conference on Bioscience, Biochemistry and Bioinformatics (pp. 7-11)., https://doi.org/10.1145/3051166.3051175
  • Von Gwayneth, B.A., Dungca, C.J.N., Lazam, S.A., Pereira, M.N.L., Tan, J.R.O. and Prado, S.V., Development of an EEG-based Motor Imagery Brain-Computer Interface System for Lower Limb Assistive Technologies. In 2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) (pp. 1-6). IEEE., DOI: 10.1109/HNICEM.2018.8666350
  • Marcelo, C.A.G., Pasquin, Z.R.B., Pichay, A.D.T., Tan, M.L.D., Simon, M.F.K.N., Prado, S.V., San Buenaventura, C.V. and Nicasio, M.S., 2017, December. Characterization and comparison of brain wave signals during deception. In 2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM) (pp. 1-6). IEEE., DOI: 10.1109/HNICEM.2017.8269508