Dr Andreu Massot Tarrús | Neuroscience | Best Researcher Award

Dr Andreu Massot Tarrús | Neuroscience | Best Researcher Award 🏆

Neurologist at Hospital Universitari Mútua Terrassa, Spain🎓

Andreu Massot Tarrús, MD, PhD, is a highly accomplished neurologist and epileptologist with over 20 years of experience. He earned his Medical Doctorate from the Universitat Autònoma de Barcelona in 2003 and later completed a PhD Cum Laude in Medicine, focusing on intracranial atherostenosis. He has held senior neurology positions at prestigious hospitals in Spain, including Hospital Universitari Vall d’Hebron, Jiménez Díaz Foundation, and Hospital Universitari Mútua Terrassa, where he currently serves. Dr. Massot Tarrús has specialized expertise in epilepsy, EEG, and cerebrovascular diseases and has completed advanced fellowships in Canada and the UK.

Professional Profile 

Education

Andreu Massot Tarrús earned his Medical Doctorate in August 2003 from the Universitat Autònoma de Barcelona. He went on to complete his Neurology specialization in May 2009 at the Hospital Universitari Vall d’Hebron, Barcelona. In June 2013, he was awarded a PhD Cum Laude in Medicine by the same university for his thesis on intracranial atherostenosis, supervised by Dr. Montaner Villalonga and Dr. Álvarez-Sabín. His commitment to epilepsy research led him to a Clinical and Research Fellowship in Epilepsy and EEG at Western University, Ontario, in 2014, followed by a Master in Epilepsy from the Universidad de Murcia in 2018, where he received an excellent qualification.

 Work Experience

Dr. Massot Tarrús’s medical career has spanned several prestigious institutions. Starting as a clinical observer in London (2008), he then became a Senior Neurologist in Barcelona and Madrid, working in the Neurovascular Unit at Vall d’Hebron (2009-2010) and the Epilepsy Unit at the Jiménez Díaz Foundation (2010-2011). Between 2011 and 2021, he took on various senior roles, including at Hospital del Mar and Hospital Universitario Gregorio Marañón, Madrid. Since September 2021, he has been a Senior Neurologist and Epileptologist at Hospital Universitari Mútua Terrassa, where he continues to excel in treating neurological disorders, particularly epilepsy.

 Skills 

Dr. Massot Tarrús is highly skilled in Electroencephalography (EEG) and Video-EEG monitoring. He has extensive experience in intraoperative electrocorticography, cortical stimulation mapping, and the Wada test. His expertise in cerebrovascular diseases and ultrasonography diagnostics has made him a leading lecturer at several top hospitals, including Vall d’Hebron, Hospital del Mar, and Hospital Gregorio Marañón.

Awards & Honors

He holds certifications in Electroencephalography from both the Canadian Society of Clinical Neurophysiology (2015) and the Spanish Society of Neurology (2016). He was also awarded a Cum Laude distinction for his doctoral work and has participated in advanced training like the NIH Stroke Scale Training by the National Stroke Association.

 Membership 

Dr. Massot Tarrús is an active member of the Spanish Society of Neurology and has contributed significantly to clinical neurophysiology through his memberships in various international medical bodies.

 Teaching Experience

Dr. Massot Tarrús has shared his knowledge extensively, offering lectures on epilepsy, neurovascular diseases, and ultrasonography techniques. He has taught at institutions like Jiménez Díaz Foundation, Hospital del Mar, and Western University, where his work in EEG and cerebrovascular illness has helped shape the careers of future neurologists.

 Research Focus

His research primarily focuses on epilepsy and ischemic cerebrovascular diseases. His PhD thesis, which examined markers of recurrence in intracranial atherostenosis, highlights his dedication to improving diagnostics and treatment outcomes in neurology. He continues to contribute to research on epilepsy and cerebrovascular conditions, aiming to reduce the recurrence of ischemic events in patients.

 

📖Publications : 

  • 📄 “Real-world safety and effectiveness of cenobamate in patients with focal onset seizures: Outcomes from an Expanded Access Program”
    Author: Massot-Tarrús, A.
    Journal: Epilepsia Open
    Year: 2023
    Volume: 8(3), pp. 918–929
  • 📊 “Risk factors for comorbid epilepsy in patients with psychogenic non-epileptic seizures. Dataset of a large cohort study”
    Author: Massot-Tarrús, A.
    Journal: Data in Brief
    Year: 2022
    Volume: 45, 108568
  • 🧠 “Roles of fMRI and Wada tests in the presurgical evaluation of language functions in temporal lobe epilepsy”
    Author: Massot-Tarrús, A.
    Journal: Frontiers in Neurology
    Year: 2022
    Volume: 13, 884730
  • 💊 “Perampanel as adjuvant treatment in epileptic encephalopathies: A multicenter study in routine clinical practice”
    Co-author: Massot-Tarrús, A.
    Journal: Epilepsy and Behavior
    Year: 2022
    Volume: 134, 108836
  • 📈 “Factors associated with comorbid epilepsy in patients with psychogenic nonepileptic seizures: A large cohort study”
    Author: Massot-Tarrús, A.
    Journal: Epilepsy and Behavior
    Year: 2022
    Volume: 134, 108780
  • 🧩 “Cortical myoclonus associated with coeliac disease showing a characteristic EEG pattern: A case report”
    Author: Massot-Tarrús, A.
    Journal: Seizure
    Year: 2022
    Volume: 95, pp. 81–83
  • 🚑 “Response to anakinra in new-onset refractory status epilepticus: A clinical case”
    Author: Massot-Tarrús, A.
    Journal: Seizure
    Year: 2022
    Volume: 94, pp. 92–94
  • 🦠 “Neurological complications of COVID-19 in hospitalized patients: The registry of a neurology department in the first wave of the pandemic”
    Co-author: Massot-Tarrús, A.
    Journal: European Journal of Neurology
    Year: 2021
    Volume: 28(10), pp. 3339–3347
  • 📉 “Predicting outcome of patients with psychogenic nonepileptic seizures after diagnosis in an epilepsy monitoring unit”
    Author: Massot-Tarrús, A.
    Journal: Epilepsy and Behavior
    Year: 2021
    Volume: 120, 108004
  • 🧬 “E200K familial Creutzfeldt-Jakob disease. MRI, EEG, PET and neuropathological correlation in a family”
    Co-author: Massot-Tarrús, A.
    Journal: Neurologia
    Year: 2021
    Volume: 36(5), pp. 399–401

 

Amit Chougule | Cognitive Neuroscience | Best Researcher Award

Mr Amit Chougule | Cognitive Neuroscience | Best Researcher Award

 

Researcher at Manentia AI, India

 

 

📚 Amit Chougule is a distinguished deep learning and AI researcher with a PhD from BITS Pilani, dedicated to advancing AI through cutting-edge research, algorithm development, and impactful industry contributions. He has over 3 years of expertise in AI and Computer Vision, having worked with esteemed organizations like Philips Research, Sony Research India, and Carleton University’s TrustCAV Research. Amit is proficient in Python and skilled in utilizing various libraries for data manipulation, statistical analysis, and machine learning. His experience includes designing end-to-end AI solutions and developing models for healthcare, autonomous vehicles, and more. 🚀🤖📊

Professional Profile:

 

🎓 Education:

  • PhD in Computer Vision & AI, BITS Pilani, Pilani (2021-2024)
    • Thesis: Artificial Intelligence Enabled Vehicular Vision and Service Provisioning for Advanced Driver Assistance Systems (ADAS)
    • Supervisors: Dr. Vinay Chamola, Dr. Pratik Narang & Prof. F. Richard Yu (IEEE Fellow)
  • M.Tech in Big Data & IoT, PES University, Bengaluru (2018-2020)
    • Specializations: IoT, Cloud Computing, Big Data & Cyber Security
  • B.Tech in Computer Engineering, Shivaji University (2013-2017)
    • Focus Areas: Computer Algorithm, Data Structure, Computer Networks & Operating System

💼 Experience:

  • Visiting Researcher, Carleton University, Canada (Dec 2022 – June 2023)
    • Developed techniques for enhancing self-driving vehicles.
    • Analyzed the impact of abnormal weather on vision-based autonomous vehicle operations.
    • Introduced a computer vision-based attention model for reliable autonomous driving in adverse weather.
  • Computer Vision Intern (PhD), Sony Research (Oct 2022 – Nov 2022)
    • Innovated a computer vision model for diagnosing diseases using biomarkers.
    • Developed an advanced pipeline for predicting diseases based on anatomical biomarkers.
  • Machine Learning Engineer, AIvolved Technologies (Aug 2020 – Dec 2020)
    • Worked on object detection, tracking, pose estimation, and web scraping for applications like gait analysis and traffic analysis.
  • Computer Vision Intern, Philips Healthcare Research (July 2019 – July 2020)
    • Conducted research on ultrasound medical imaging.
    • Developed an Anatomical Intelligent Fetal Heart Ultrasound Scanning technique.
    • Implemented an AI model for precise estimation of fetal femur length.

🔧 Skills:

  • Programming Languages: C, C++, JAVA, Python, SQL
  • Machine Learning Frameworks: PyTorch, Keras, TensorFlow
  • CI/CD Tools: Git
  • MLOps Frameworks and Tools: Docker, Kubernetes
  • Data Pipelines and Analytics Tools: Apache Spark, PySpark
  • Image Processing: OpenCV, Matplotlib, Scikit-image, SciPy, Pillow
  • Generative AI: Autoencoders, GANs, Diffusion Models
  • Computer Vision Domains: Image Classification, Object Detection, Object Tracking, Segmentation, Pose Estimation, Computational Geometry, Image Generation
  • Medical Imaging Tools: ImageJ, 3D Slicer, OsiriX, SimpleITK, ITK-SNAP, RadiAnt DICOM
  • Hardware: Arduino, Raspberry Pi, Nvidia Jetson Nano

🏆 Awards and Honors:

  1. Generative Adversarial Networks (GANs) Specialization by Coursera
  2. Deep Learning with Numpy by Udemy
  3. Getting Started with AWS Machine Learning by Amazon (Coursera)
  4. Computer Vision Basics by University at Buffalo and The State University of New York (Coursera)
  5. Digital Image Processing with OpenCV in Python by GEO University
  6. Data Science with Python by Pluralsight
  7. Pandas Foundations by Datacamp
  8. Python (Advanced Level) by HackerRank

🔬 Research Focus:

Amit Chougule is dedicated to advancing artificial intelligence through cutting-edge research, innovative algorithm development, and impactful industry contributions. He focuses on:

  • Deep Learning Technology: Solving complex real-world problems and driving societal impact.
  • Computer Vision: Enhancing autonomous vehicle capabilities, especially in adverse weather conditions.
  • Medical Imaging: Developing AI models for accurate disease diagnosis and fetal growth prediction.
  • AI Solutions: Designing end-to-end AI solutions, from data pipeline architecture to model deployment.

Publications: