francesca a phd candidate

Francesca Grisoni

Francesca Grisoni is an Assistant Professor at the Eindhoven University of Technology, where she leads the Molecular Machine Learning team. After receiving her Ph.D. in 2016 at the University of Milano-Bicocca (Prof. R. Todeschini) with a dissertation on machine learning for (eco)toxicology, Francesca worked as a data scientist and as a biostatistical consultant for the pharmaceutical industry. Later, she joined the University of Milano-Bicocca and the ETH Zurich as a postdoctoral researcher (Prof. G. Schneider), working on machine learning for drug discovery and de novo design. Her team’s research focuses on developing novel chemistry-centred deep learning methods to augment human intelligence in drug discovery, at the interface between computation and wet-lab experiments.

Derek van Tilborg

Derek van Tilborg is a Ph.D. candidate in the Molecular Machine Learning team. Derek holds a MSc degree in bioinformatics from Wageningen University & Research and has a background in biomedical research. He currently works on developing machine learning methods for molecular property prediction, aiming to bridge the gap between predictions and experiments in drug discovery. His research interests are focused on graph neural networks and active learning.

Rıza Özçelik

Rıza Özçelik is a Ph.D. candidate in the team. He received his MSc. degree from the Department of Computer Engineering at Boğaziçi University, Turkey, where he applied machine learning to structure-based drug-target affinity prediction. Rıza currently focuses on developing novel generative deep-learning approaches for de novo drug design.

Yves Gaetan Nana Teukam

Yves Gaetan Nana Teukam is currently a PhD candidate at IBM Research Europe – Zurich, and he is concurrently affiliated with the Eindhoven University of Technology. His academic journey began with a Bachelor’s degree in Bioinformatics, followed by a Master’s degree in Data Science. Yves’s current focus revolves around the intriguing intersection of language models and protein optimization/design/engineering. By combining data science methodologies with bioinformatics concepts, he aims to unravel the intricate patterns of protein structures, functions, and their potential for engineering. His ultimate goal is to contribute to an innovative venture that utilizes the power of artificial intelligence in the field of bioinformatics. Yves finds the potential impact of this endeavor in areas such as drug discovery and genetic diseases particularly exciting. As he navigates the world of research and development, Yves looks forward to expanding his horizons in this interdisciplinary domain.

Cristina Izquierdo Lozano

Cristina Izquierdo Lozano is from Reus, a small town in Catalonia. In 2020,  she obtained her BSc in Biotechnology and B ENG in Computer Engineering from Universitat Rovira i Virgili in Tarragona. During her time there, she joined the  Nanoscopy for Nanomedicine group at IBEC in Barcelona in 2019, where she conducted both of her  bachelor theses , utilizing Correlative Light and Electron Microscopy to characterize polymeric nanoparticles and developing a computer vision application in MATLAB, enabling automatic image correlation between two distinct microscopes . In 2021 , she moved to Eindhoven to pursue her PhD in the TU/e . In her current research,  she use s Machine Learning techniques to analyze super-resolution microscopy data , under the guidance of her supervisors Lorenzo Albertazzi (n4n) and Francesca Grisoni (molML).

Helena Brinkmann

Helena Brinkmann is a Ph.D. candidate at the Molecular Machine Learning Team. She completed her undergraduate studies in the subjects Mathematics and Chemistry at the Eberhard Karls University Tübingen in Germany. After working as a teacher for two years, she received her MSc degree in Medicinal Chemistry from the University of Gothenburg, where she first applied machine learning for drug discovery. Currently, she focuses on the encoding of chemical information to augment the capabilities of de novo molecule design and chemical space exploration.

Emanuele Criscuolo

Emanuele Criscuolo studied Chemistry at Sapienza University and Tor Vergata University, in Rome. During his master studies he spent about one year at IRBM Science Park, focusing his work on fragment-based drug discovery. In February 2023, He obtained his Ph.D. cum laude in Biochemistry and Molecular Biology, working in the Department of experimental medicine at the University of Rome Tor Vergata. During his doctoral studies, he discovered his passion for computational techniques, combining them with experimental procedures. In 2021, He has received a short-term FEBS fellowship and he was hosted at Leiden University. One year later, he joined Grisoni’s group in Eindhoven, as guest PhD student, to combine his passion for Molecular Dynamics with Machine Learning. In 2023, he joined the team as a Postdoctoral fellow. 

Andrea Gardin

Andrea Gardin is a Postdoctoral Research Fellow in the Molecular Machine Learning group. He completed his MSc. in Chemistry at the University of Padua, where he focused on computational methods to study complex molecular systems. In October 2023, he earned his Ph.D. in Material Science and Technology from the Polytechnic University of Turin. During his Ph.D., Andrea primarily worked on techniques for detecting and classifying the structural features of various supramolecular materials. Since joining this research group in January 2024, he has been applying machine learning to study and optimize a wide range of supramolecular materials, with a particular focus on, but not limited to, coacervates.

Luke Rossen

Luke Rossen is a PhD Candidate in the Molecular Machine Learning team. Previously, he joined the group as a Master student at TU/e in the Biomedical Engineering department – Chemical Biology cluster, where he managed and participated in the   ‘international genetically engineered machine’   (iGEM) Competition team. His research interests are reflected in a recently completed thesis on active learning for drug discovering using graph neural networks, working at the interface between the wet lab and computational work to efficiently navigate the chemical space. Luke has pursued an internship at the Novartis Institute for Biomedical Research, Switzerland, working on generative deep learning models for molecular (scaffold) design.

Marcel Hiltscher

Marcel Hiltscher  is a PhD Candidate in the Molecular Machine learning team and at Sanofi (France).

Alaa Bessadok

Alaa Bessadok is a prospective Postdoctoral Fellow (September 2024).

Laura van Weesep

Laura van Weesep is a Master student in the Biomedical Engineering Department at TU/e. Her curiosity spans a wide range of subjects, and she is particularly enthusiastic about merging human expertise with insights from AI. Her research focuses on utilizing machine learning techniques to predict the properties of peptides. Prior to joining our team, she successfully completed her bachelor’s degree in biomedical engineering. In addition to machine learning for molecules, she finds joy in engaging in sports, with a particular passion for gymnastics.

Sarah de Ruiter

Sarah de Ruiter is a Master Student of Biomedical Engineering. She completed her Bachelor thesis on “Structured State Space Models for de novo drug design” in 2023, for which she won the Best Thesis Award of the Biomedical Engineering Department. Sarah returned to the Molecular ML group for her Master thesis in 2024. Her current research consists of applying model editing techniques to deep learning models for drug discovery.

Inge Groffen

Inge Groffen is a Master student at the TU/e pursuing Data Science and Artificial Intelligence. Prior to this, she completed a joint Bachelor’s degree in Data Science at the TU/e and Tilburg University. She has always had a strong interest in biology, and her current thesis allows to apply her knowledge in a biomedical context. Specifically, her research involves generating new molecules using target-based generative models. Aside from her studies, she enjoys playing tennis, practicing the piano, and traveling.

Ben Adams is a Master Student in the Molecular Machine Learning team.

Max Pordon is a MSc student (Biomedical Engineering) in the Molecular Machine Learning group. Max completed his BSc Biomedical Engineering at TU/e in 2023, with specialization in Chemical Biology and Computational Biology. During his BSc, he completed his bachelor thesis on  “De Novo Peptide Design for Small Extracellular Vesicle Transfection with Artificial Intelligence” in our group. He also followed an internship at 8vance where he used machine learning to predict career paths. Now, for his Master’s thesis, he is using Reinforcement Learning for Scaffold Hopping and de novo design.

Sanne van de Worst (BSc @Biomedical Engineering) Bram Boerenkamp (BSc @Biomedical Engineering) Antoine Argante (BSc @Biomedical Engineering) Hugo ter Steege (BSc @Biomedical Engineering) Vera Wentzel (BSc @Biomedical Engineering) Rebecca Birolo (guest PhD @UniTo) Sarah de Ruiter (BSc @Biomedical Engineering) Meilina Reksoprodjo (MSc @Computer Science) Francesca Mori (BSc @Chemical Engineering) Joelle Bink (BSc @Biomedical Engineering) Laura Lemmens (guest Master student @UAM) Lisa Nooren (BSc @Biomedical Engineering) Max Pordon (BSc @Biomedical Engineering) Silvia Multari (guest MSc @ University of Milano) Teo Yordanov (BSc @Chemical Engineering) Viktorija Mamula (MSc @Industrial Engineering)

Into the ocean twilight zone: how new technology is revealing the secrets of an under-researched undersea world

Professor of Marine Biology, Te Herenga Waka — Victoria University of Wellington

Lecturer in Marine Biology, Te Herenga Waka — Victoria University of Wellington

PhD Candidate in Marine Biology, Te Herenga Waka — Victoria University of Wellington

Postdoctoral Researcher, Te Herenga Waka — Victoria University of Wellington

Disclosure statement

James Bell receives funding from The George Mason Charitable Trust and the Department of Conservation

Alice Rogers, Francesca Strano, and Valerio Micaroni do not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and have disclosed no relevant affiliations beyond their academic appointment.

Te Herenga Waka — Victoria University of Wellington provides funding as a member of The Conversation NZ.

Te Herenga Waka—Victoria University of Wellington provides funding as a member of The Conversation AU.

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Despite New Zealanders’ close connection with the oceans, very few will have heard of “temperate mesophotic ecosystems” ( TMEs ). Even fewer will appreciate their importance for coastal fisheries, and possibly climate change mitigation.

TMEs typically occur at depths of between 30 and 150 metres – the twilight zone of our oceans, where little sunlight remains. But science is beginning to shed light on these remarkable ecosystems, and the need to protect them.

While there has been plenty of research on the deep oceans (greater than 200m) and the shallow seas (less than 30m), TMEs have received surprisingly little attention. They have only been recognised as distinct ecosystems in the past 15 years.

TMEs are beyond the reach of most scientific divers, but the recent development of relatively small and cheap remotely operated vehicles (ROVs) now allows greater access to these extraordinary undersea regions.

ROVs, such as the New Zealand-made Boxfish , can be deployed from small boats and are equipped with high-resolution cameras and robotic arms to identify organisms and collect specimens. We’re now able to regularly observe TMEs and our understanding of them is growing rapidly.

What do rocky TMEs look like?

Unlike the shallow seas, which are generally dominated by habitat-forming fleshy seaweeds, TMEs are dominated by animals.

At their shallowest, they support a mixture of seaweeds and animals, but as you descend deeper into low light conditions, encrusting algae and unique animal species begin to dominate.

Animals adapted to low light conditions include sponges , sea fans and sea squirts. Indeed, recent research from New Zealand found sponges can occupy more than 70% of the available space on rocky TMEs.

Given these ecosystems are likely to be widespread throughout temperate seas, it’s feasible that sponges might be even more abundant than algae in coastal ocean regions.

Ecological and economic importance

While we still know little about the ecology of TMEs, they’re important in several ways for wider coastal ecosystems.

The three-dimensional nature of the sponges and other animals that dominate TME habitats creates structural complexity on the sea floor. This provides a home to a range of organisms, from small and juvenile fish to crabs, that are likely to use this habitat to evade predators.

Also, many fish species migrate between shallow water and these deeper twilight ecosystems, likely looking for food and shelter.

Read more: Marie Tharp pioneered mapping the bottom of the ocean 6 decades ago – scientists are still learning about Earth's last frontier

The sponges that dominate TMEs filter large volumes of water and are able to capture dissolved carbon and transform it into detritus . Scavengers such as small crustaceans and worms can eat sponge detritus. Subsequently, these little creatures are eaten by larger organisms (like fish) higher up the food chain.

TMEs are therefore likely to be extremely important to coastal fisheries.

Our evaluation of depth-related changes in temperature suggests TMEs could also be important in the mitigation of climate change impacts, particularly marine heat waves that drive extremes in sea water temperature.

We’ve found water temperature in the depths where TMEs occur is usually several degrees lower than at the surface, which may provide a refuge for mobile fish species from shallow waters.

Furthermore, if shallower populations are damaged by human activity, then deeper water TME populations may be able to replenish them by providing larvae.

Human impacts on TMEs

While TMEs are likely to be affected by the same anthropogenic factors as surface waters, some specific stressors may have a greater impact.

The domination of TMEs by many upright (often slow-growing) tree-like forms, including sponges and sea fans, makes these ecosystems particularly vulnerable to physical disturbance.

Read more: New Zealand’s fossil record suggests more species lived in warmer waters. But the current rate of warming may break this pattern

Rocky TMEs often overlap with fisheries that use pots and traps, such as for lobsters and crabs. These fishing activities can smash and damage sponges and sea fans, which may take many years to recover.

The domination of rocky TMEs by filter-feeding organisms, and their proximity to the surface, makes them susceptible to the impacts of increased sediment in the water column, which increases turbidity and the amount of sediment settling on organisms.

Increased sediment might result from changes in land use in coastal areas, for example from construction or farm conversions, or from trawling, dredging or sea-floor mining.

Our recent analysis has shown very few of the rocky TMEs across the world’s oceans have been explored and characterised. Even fewer are protected as part of existing management and conservation frameworks.

In most places where they are protected, it’s usually a side effect of protecting shallow-water ecosystems that border TMEs.

The diverse and ecologically important communities found in TMEs need greater recognition and protection of a unique biodiversity we’re only now coming to properly understand.

• Climate change
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• sea sponges

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PhD student Francesca Morphakis features in History Today

School of History news Thursday 13 August 2020

F rancesca considers E.H. Carr's question from 1961 - 'What Is History?' - and discusses the power and purpose of studying the subject.

What Is History? is a non-fiction book on historiography written by Edward Hallett Carr in 1961.

In History Today  (Volume 70, Issue 8, August 2020)  Francesca Morphakis , PhD Candidate in History at the University of Leeds, shares her thoughts.

History is narratives. From chaos comes order. We seek to understand the past by determining and ordering ‘facts’; and from these narratives we hope to explain the decisions and processes which shape our existence. Perhaps we might even distill patterns and lessons to guide – but never to determine – our responses to the challenges faced today. 

We seek to understand the past by determining and ordering ‘facts’; and from these narratives we hope to explain the decisions and processes which shape our existence.

Yet political history has fallen out of fashion and subsequently into disrepute, wrongly demonised as stale and irrelevant. 

History’s primary purpose is to stand at the centre of diverse, tolerant, intellectually rigorous debate about our existence: our political systems, leadership, society, economy and culture. However, open and free debate – as in so many areas of life – is too often lacking and it is not difficult to locate the cause of this intolerance. 

Read the full article in History Today .

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Francesca Ferlicca

January, 2020 - March, 2020

Visiting PhD Candidate

She has already worked 5 years as an urban planner in the public sector at the Ministry of Environment and Public Space (Government of Buenos Aires City), as well as a consultant for the Laboratorio Urbano Digital (CIPPEC) and for the masterplan of the Municipality of Hurlingam (Buenos Aires Metropolitan Area). 

Research interests

Urban policies, housing policies and urban informality in the Global South, especially in Argentina. 

Research project pursued at the CEE

During her stay Francesca Ferlicca mainly plans to work with Prof. Marco Cremaschi on an article about Urban Regulation and Informality in Rome and Buenos Aires and the organization of two conferences : « Urban Informality in the Global North » and « Urban Planning in Contemporary Buenos Aires »

She also intends to colloborate with Alix Chaplain, PhD candidate at the CERI - Sciences Po, Paris - to write an article about the continuum between formal and informal, questioning the relevance of the distinction in the provision of infrastructure and housing in the Global South.

To know more

Contact: [email protected]

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Francesca Palermo

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Table of Contents

Technical skills, publications.

For an updated CV please click here

• Developed applications in PyTorch and Tensorflow of deep learning models (LSTM, Autoencoders) to time-series personalised data collected from remotely monitored environments for detecting health-related episodes in people with dementia.
• Improved the quality of the data, reducing missing data by 5% within a few weeks.
• Assisted the laboratories for Machine Learning for Neuroscience module and marked the assignments. Material available on Github .
• Delivered lectures, practical sessions and marked assignments on Machine Learning and Data Mining to classes from 30 to 200 undergraduate and postgraduate students.
• Led small group tutorials and provided one-on-one support to students, helping them to understand complex concepts and apply them in practical settings.
• Developed a Tensorflow multi-modal fusion model for object detection (Faster R-CNN), combining visual and tactile features, resulting in two publications.
• Labelled videos human-robots interactions for use in maintenance assistance robot projects.
• Developed Hololyo, an Augmented Reality environment using Unity and Microsoft Hololens, to provide visual feedback to amputees during the training of arm prostheses. Utilised IMU data from MYO bracelets to control a virtual rigged hand.
• Investigated the repeatability of hand movement recognition for the control of robotic prostheses using sEMG data and machine learning classification techniques.
• Applied image segmentation techniques to more than 2000 CT lung images for medical imaging analysis, extracting features using Matlab to identify patterns that could be used for cancer prediction.
• Collaborated with the MeganePro project team. Acquired an openly available database of sEMG data, consisting of a total of 100 acquisitions from 10 subjects.
• Applied preprocessing techniques, synchronised and filtered the data, and applied machine learning classification techniques (Random Forest).
• Published a paper in rank A conference. Finalist for the Best Student Award.

• Collaborated with the National Centre for Nuclear Robotics for developing a multi-modal robotic surface exploration algorithm for detecting and characterising fractures in extreme environments.
• Implemented object detection algorithms (Faster R-CNN, YOLO) in Tensorflow to localise a crack in the environment using the video stream from a camera.
• Developed an OpenCV algorithm for extracting a skeleton version from an image of a crack and using a minimum spanning tree graph to calculate the shortest path for exploring the crack.
• Implemented the algorithm in Python and C++ , and used machine learning techniques (Faster R-CNN, YOLO, CNN, Random Forest) to localise the crack and classify the data acquired via a force and proximity robotic sensor.
• PhD representative for the 20 students in the Advanced Robotics Laboratory, organised biweekly meetings and mentored three master students during their final projects.
• Participated in the Google Get Ahead 2020 program, an invitation-only program.
• Presented demos and projects in outreach activities (Strategy 2030 and Open Days) to promote STEM to the public.
• Implemented machine learning techniques (feature extraction, classification) to analyse the repeatability of grasp recognition for robotic hand control based on surface electromyography data.
• Developed a mobile application for Android that allows the user to send vocal commands and control a Nao Robot, through a client-server connection.
• Developed “The Little Knight”, a videogame based on WebGL using the Javascript library (Three.js).
• Developed an algorithm for controlling the pose of a Kuka manipulator via Mutual-Information Based on Visual Servoing.
• Analysis and development of spiking neural network Izhikevich models

• Awarded first prize for the data visualisation competition.
• Awarded first prize as a member of a four-person team. Accurately estimated containers’ capacity via computer vision and machine learning techniques. Led the team in organising meetings and managing workload to complete the project.
• Awarded scholarship of 2400£ to cover expenses for three months internship at the Tokyo University of Agriculture and Technology.
• Awarded best Master Thesis on disability among a total of 15 students across all faculties at the University.
• Awarded first prize for Group Project at the VVV18 International Winter School on Humanoid Robot Programming, organised by the IIT iCub Facility and the IEEE Robotics and Automation Society.
• Awarded travel grant cover for alla expenses to participate in the International Winter School on Humanoid Robot Programming.
• Awarded scholarship of 3300CHF to cover expenses for three months internship at the HES-SO Haute école spécialisée de Suisse occidentale.

For a complete list of my projects, please refer to the projects page.

• Developed an online application for video animation using the algorithm first order motion model for image animation by Aliaksandr Siarohin et al

• Italian (Native)
• English (Advanced)
• French (Intermediate)
• Japanese (Basic)

For a full list of publications, please refer to my Google Scholar Profile .

Below a list of my most recents publications:

• Capstick, A., Palermo, F., & Barnaghi, P. (2022). Loss Adapted Plasticity in Deep Neural Networks to Learn from Data with Unreliable Sources. arXiv preprint arXiv:2212.02895 .
• Palermo, F. (2022). Robotic surface exploration with vision and tactile sensing for cracks detection and characterisation. .
• Omarali, B., Palermo, F., Althoefer, K., Valle, M., & Farkhatdinov, I. (2022). Tactile Classification of Object Materials for Virtual Reality based Robot Teleoperation. 2022 International Conference on Robotics and Automation (ICRA) .
• Xompero, A., Donaher, S., Iashin, V., Palermo, F., Solak, G., Coppola, C., Ishikawa, R., Nagao, Y., Hachiuma, R., & Liu, Q. (2022). The CORSMAL benchmark for the prediction of the properties of containers. IEEE Access .
• Palermo, F., Li, H., Capstick, A., Fletcher-Lloyd, N., Zhao, Y., Kouchaki, S., Nilforooshan, R., Sharp, D., & Barnaghi, P. (2021). Designing A Clinically Applicable Deep Recurrent Model to Identify Neuropsychiatric Symptoms in People Living with Dementia Using In-Home Monitoring Data. Research2Clinics WS @ NeurIPS 2021, arXiv preprint arXiv:2110.09868 .
• Vitanov, I., Farkhatdinov, I., Denoun, B., Palermo, F., Otaran, A., Brown, J., Omarali, B., Abrar, T., Hansard, M., & Oh, C. (2021). A suite of robotic solutions for nuclear waste decommissioning. Robotics .
• Palermo, F., Rincon-Ardila, L., Oh, C., Althoefer, K., Poslad, S., Venture, G., & Farkhatdinov, I. (2021). Multi-modal robotic visual-tactile localisation and detection of surface cracks. 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) .
• Xompero, A., Donaher, S., Iashin, V., Palermo, F., Solak, G., Coppola, C., Ishikawa, R., Nagao, Y., Hachiuma, R., & Liu, Q. (2021). Multi-modal estimation of the properties of containers and their content: survey and evaluation. IEEE TRANSACTIONS ON MULTIMEDIA .
• Palermo, F., Oh, C., Althoefer, K., Poslad, S., & Farkhatdinov, I. (2021). Investigation of images of cracks via graph theory for developing an optimal exploration algorithm for a robotic manipulator. .
• Iashin, V., Palermo, F., Solak, G., & Coppola, C. (2021). Top-1 CORSMAL challenge 2020 submission: Filling mass estimation using multi-modal observations of human-robot handovers. Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10-15, 2021, Proceedings, Part VIII .
• Palermo, F., Konstantinova, J., Althoefer, K., Poslad, S., & Farkhatdinov, I. (2020). Automatic fracture characterization using tactile and proximity optical sensing. Frontiers in Robotics and AI .
• Palermo, F., Konstantinova, J., Althoefer, K., Poslad, S., & Farkhatdinov, I. (2020). Implementing tactile and proximity sensing for crack detection. 2020 IEEE international conference on robotics and automation (ICRA) .
• Omarali, B., Palermo, F., Valle, M., Poslad, S., Althoefer, K., & Farkhatdinov, I. (2019). Position and velocity control for telemanipulation with interoperability protocol. Towards Autonomous Robotic Systems: 20th Annual Conference, TAROS 2019, London, UK, July 3–5, 2019, Proceedings, Part I 20 .
• Palermo, F., Cognolato, M., Eggel, I., Atzori, M., & Müller, H. (2019). An augmented reality environment to provide visual feedback to amputees during sEMG Data Acquisitions. Towards Autonomous Robotic Systems: 20th Annual Conference, TAROS 2019, London, UK, July 3–5, 2019, Proceedings, Part II 20 .
• Palermo, F., Cognolato, M., Gijsberts, A., Müller, H., Caputo, B., & Atzori, M. (2017). Repeatability of grasp recognition for robotic hand prosthesis control based on sEMG data. 2017 International Conference on Rehabilitation Robotics (ICORR) .

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Dr Francesca Brencio PhD

School of Psychology Teaching Fellow

Contact details

Dr. Francesca Brencio is Teaching Fellow in Mental Health at the Institute for Mental Health, at the School of Psychology of the University of Birmingham. Her current interests include: phenomenological psychopathology, philosophy of psychiatry, qualitative research and Heidegger Studies.

Qualifications

• Executive Committee Member of The Royal College of Psychiatrists - Special Interest Group in Philosophy (UK)
• Member of the Phenomenology and Mental Health Network at The Collaborating Centre for Values-Based Practice in Health and Social Care at the St Catherine’s College, University of Oxford (UK)

BA in Theology, Theological Institute in Assisi associated to Pontificia Universitas Lateranensis (PUL), Italy

PhD in Philosophy and Human Sciences, Università degli Studi di Perugia, Italy

BA (Hons. – 5 years degree course) in Philosophy, Università degli Studi di Perugia, Italy

Dr. Brencio joined the University of Birmingham in 2024 as Teaching Fellow in Mental Health. She studied Philosophy at University of Perugia (Italy) and Theology at the Theological Institute in Assisi associated to Pontificia Universitas Lateranensis (Vatican City).

She was a post-doctoral researcher at the Western Sydney University (Australia) and the Albert-Ludwigs-Universität Freiburg (Germany). For the Winter Semester 2017 she was Visiting Professor in the USA at the Hillsdale College (Michigan), Wisconsin University, and The SUNY in Buffalo. From 2018 to 2024 she was Associate Researcher in Philosophy in the frame of the Research Group “Filosofía Aplicada: Sujeto, Sufrimiento, Sociedad” at the University of Seville (Spain). In 2021

Dr. Brencio was awarded The Seal of Excellence by the European Commission, as the institution managing Horizon 2020, in the frame of EU Programme for Research and Innovation 2014-2020. In January 2022 she joined the Philosophy of Psychiatry Educators Network, of the International Network for Philosophy and Psychiatry. She is the Director of the PhenoLab - A theoretical laboratory on Phenomenology and Mental Health.

Dr Brencio is involved in teaching activities for the MSc Mental Health for on-campus and distance-learning students.

Scholar of the German tradition of phenomenology, especially of Martin Heidegger, her works are aimed to the exploration of the methodological and epistemological contributions that phenomenology and hermeneutics provide to psychiatry, in order to achieve a better understanding of mental health.

Dr. Brencio works primarily in the field of phenomenological psychopathology and philosophy of psychiatry, with a focus on themes such as perception, attention, emotions (individual and social emotions), affective life, and the role of the body. The aim of her research is mainly related to eliciting the subjective dimension of some psychopathological experiences, i.e., depression and schizophrenia, using phenomenological informed interviews. She is among the editors of the Handbook of Phenomenology, Values-based Practice and Shared Decision-Making in Personalised Mental Health Care: Contemporary Approaches and Challenges (Springer-Nature, Cham, expected for 2025), and she is among the contributors of The Oxford Handbook of Phenomenological Psychopathology (Oxford University Press, Oxford 2019), Storia della Fenomenologia Clinica (UTET, Torino 2020), and APA Handbook of Humanistic and Existential Psychology (American Philosophical Association Press, in press).

Francesca Baldacchino

Physical geographer, victoria university of wellington, phd candidate.

Francesca Baldacchino is a PhD Candidate. Her research interests are remote sensing and GIS applications within the cryosphere and biosphere.

In the Antarctic Science Platform, Francesca will use remote sensing to understand cryosphere dynamics.

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Elizabeth Davis, '21

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Jasmine Sahu-Hough, '21

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Introduction to Ecology & Levels of the ...

6th -  8th  , 12.4k plays, earth's early history, punnett squares, what is engineering, 34.7k plays, kg -  2nd  , ellington criteria and constraints, 8th -  10th  , genetic engineering, solving multistep equations, 9th -  11th  .

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9th - 12th grade.

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Francesca, a PhD candidate, conducts extensive research on aluminum corrosion. When finished, she will submit her research data and conclusions in a report to a scientific journal for peer review. What are three benefits of peer review? Select three answer choices.

Peer review guarantees that the results of the research or experimentation are accurate and relevant.

Peer review allows other scientists the chance to try to replicate the experimental results.

Peer review can lead to new ideas and further study.

Peer review helps check for mistakes, bias, or fraud in a set of experimental work.

Society expects scientists to follow ethical practices and meet many ethical standards. Which is an example of one of these ethical standards?

Investigate only the events that affect people's lives or livelihoods.

Analyze data that was truly observed, and not data that was expected or desired.

Publish experimental results only if they agree with current theories or public opinion.

Continue the procedure of an experiment or investigation under all circumstances.

Scientists are often faced with ethical questions, or questions of right and wrong. Which of the following are examples?

I. May wants to include a hypothesis in her report, and she asks if she must give credit to the scientist who first proposed it.

II. Alex is planning an experiment on gerbils, and he asks how large the cages should be.

III. Pam is developing a new technique for mining fossil fuels, and she asks if the technique must avoid polluting the environment.

I. and II. only

II. and III. only

I., II., and III.

Maya is generating a computer simulation to model the rate of recovery of a certain endangered bird species. The population decreased significantly due to loss of habitat. In her model, she correlates the expected habitat regrowth to an increase in the bird population.

Maya's simulation generates a chart of predicted growth of the bird population.

Study the bar chart. Select the year in which Maya’s model can MOST accurately predict bird population recovery.

a date in the distant future

Identify the step, as either scientific inquiry or engineering design.

Brainstorm hypotheses and choose one.

scientific inquiry

engineering design

Build projects

Colleagues or personal motivation and/or planned or chance observations generate a question

Colleagues and/or clients present a problem to be solved by a new construction

Brainstorm design solutions and choose one

Publish papers

Conduct a test of the prototype; gather and evaluate performance data

Conduct experiment; gather and analyse data.

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About francesca.

Francesca Dansereau is a PhD candidate in Human Development at McGill University.

She worked as an integration technology specialist, an adaptive technology trainer for Microcomputer Science and as an RDI certified consultant in private practice. The research she has conducted in the field focuses on neurodevelopmental disabilities (down syndrome, autism spectrum disorder and intellectual disabilities), quality of life and education technology.

Expanding her expertise, her dissertation focuses on career development and autism spectrum disorder for which she founded The Social Tree Foundation in 2017 to open an integration employment and career program in the Montreal area.

Through her private practice work, she received a contract part of the Cree Health Board in 2018 as part of the Neurodevelopmental Diagnostic and Intervention Clinic. She administers various academic assessments and supports the neurodiagnositic team for fetal alcohol syndrome disorders.

In 2020 she became Coordinator of the NEAT clinic where she supports families through the harmonization and management of their therapeutic services offered at the clinic.

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(Photo courtesy of Michaela Gross)

USF PhD candidate stresses need for malaria chemoprevention programs

• September 5, 2024
• Research & Innovation

Michaela Gross is like most young researchers at USF’s College of Public Health : She thinks big.

Big as in dreaming of a world free of many diseases, including the lethal and elusive scourge known as malaria. A PhD candidate focusing on epidemiology , Gross recently traveled to Africa, where she gave a talk at the Multilateral Initiative on Malaria Society Conference in Cameroon. Making the trip possible were funds from the college’s Student Honorary Award for Research.

Her presentation, “A systematic review of non-malarial effects of malaria chemoprevention programs,” reviewed the existing literature available on potential non-malarial effects of these programs. 

“The conference was a fantastic opportunity for national malaria programs, researchers, and global stakeholders to meet and discuss both challenges and successes in the goal of eliminating malaria,’’ Gross said. 

The trip allowed the 35-year-old to learn more about what’s happening through intervention programs, and to better understand their complexities and challenges.

“What I find fascinating about public health is that it’s not just any one thing, it’s all of them intertwined together into the greater ecology,’’ she said.

Malaria chemoprevention is recommended by the World Health Organization (WHO). It works by routinely giving medications to vulnerable groups − including pregnant women and young children – but also offers benefits beyond the disease, such as increasing infant birth weight.

Malaria is most feared in Africa, where more than 600,000 people die each year from Plasmodium falciparum, a protozoan parasite that lives in the Anopheles mosquito. About 95 percent of its victims are children under age 5.

“It’s a real tragedy and elusive is a great word to describe malaria eradication,’’ Gross added. “Part of the challenge is the complexity of the transmission system and tackling malaria really needs an interdisciplinary approach.’’

Conquering malaria has challenged scientists for decades, and it wasn’t until 2021 that WHO recommended the first vaccine − called Mosquirix − for global use. Although this vaccine has shown high public health impact and has greatly reduced cases, mortality, and hospitalizations for severe malaria, it only provides partial protection and the WHO recommends using a combination of different control strategies. 

The parasite’s ability to adapt to its environment, as well as the variables of a person’s immune system, make it a challenging foe for health care officials. “It has a complex life cycle,’’ Gross said, “and genetically it’s a very diverse parasite.’’

Gross doesn’t specialize in vaccines but focuses on better understanding the malarial and non-malarial effects of chemoprevention and how it might lead to new avenues for research. Although scientists have a toolbox of control interventions, health systems tend to be weak where transmission is highest, and the data available to inform decision-making is often lacking.

“It’s a constant battle to stay ahead of the parasite to ensure that the tools we have in our arsenal are effective,’’ she said.

If health officials can find ways to better control malaria, or even to eradicate it as they did with polio, the impact would resonate beyond the remote hospitals and clinics where the disease is most deadly. 

“Malaria exacerbates poverty and inequality,’’ Gross said of its economic effects. “Supporting control and prevention efforts directly supports the goal of global health equity, so there is a moral and ethical imperative … since malaria exacts a heavy economic cost, its prevention benefits the global economy.’’

Supporting her dissertation project has been Dr. Gillian Stresman , associateistant professor of epidemiology at USF who this year received COPH’s Excellence in Teaching Award for her contributions to student development and quality of education within their department.

 “She’s been an incredible source of knowledge and a fantastic supervisor,’’ Gross said.

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Welcome to the USF COPH news page. Our marketing and communications team is entrusted with storytelling. Through written stories, photography, video and social media we highlight alumni, faculty, staff and students who are committed to passionately solving problems and creating conditions that allow every person the universal right to health and well-being. These are our stories.

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Phd candidate iván ruiz-hernández wins fulbright-hays fellowship.

PhD Candidate Iván Ruiz-Hernández was awarded the Fulbright-Hays Doctoral Dissertation Research Abroad . The Fellowship will support Iván’s dissertation research in Mexico. Congratulations, Iván!