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Ege Aksoy |
Ege Aksoy was born in Ankara, Turkey and have lived in Stuttgart, Germany from 2006 to 2009, gaining proficiency in German and attending kindergarten before moving permanently back to Turkey. He excelled in science and mathematics throughout his education, earning a full scholarship to one of the top private schools. He was selected for TED Ankara College High School's Scientist Research Program, where he gained early exposure to scientific research methodologies and self-directed learning. He enrolled at Bilkent University in 2022 to pursue a Bachelor's degree in Electrical and Electronics Engineering, with an expected graduation in June 2026. He developed a strong interest in data science, artificial intelligence, and machine learning. He gained hands-on experience through various internships and research roles, including working as an R&D intern at Beko Dishwasher Plant, a Candidate Engineer at TUBITAK Space Research, and a Teaching Assistant for EE102 (Digital Electronics) at Bilkent University. He currently serves as the student representative for the Electrical and Electronics Engineering department and is a member of the student council. |
Matin Beiramvand |
Matin Beiramvand (Graduate Student Member, IEEE) received B.Sc. and M.Sc. degrees in biomedical engineering from Islamic Azad University, Tehran, Iran, in 2013 and 2016, respectively. She is currently pursuing a Ph.D. with the Faculty of Information and Communication Technology at Tampere University, Pori, Finland. Since 2022, she has been a researcher at Tampere University, where she conducts research on mental states such as mental workload, stress, and flow state detection using consumer-oriented devices. Her research interests include applying biomedical signal processing and machine learning methods to medical wearable consumer-oriented equipment for real-life applications. |
Aurelia Brazeal |
Aurelia Brazeal is a dedicated Research Medical Doctor with a strong passion for improving cardiovascular health through innovative AI-driven solutions. She currently works at the KEMRI-Wellcome Trust Research Programme in Kilifi, Kenya, where she leads initiatives in cardiovascular diagnostics. Her focus is on the use of AI applications in cardiology, including predictive modeling and machine learning, to enhance disease detection and risk stratification. Additionally, she is interested in AI governance and the ethical use of AI in the global south, advocating for equitable, transparent, and inclusive technological advancements that benefit low-resource communities. |
Rowena Erika Chin |
Rowena Erika Chin is originally from the sunny island city-state of Singapore. She is a graduating Ph.D. candidate in Neuroscience at Yale University. Following graduation, she is poised to commence a postdoctoral position at the Department of Psychiatry and Human Behavior at Brown University. Broadly, her research focuses on applying and integrating a combination of cross-modal techniques in neuroimaging, genomics and transcriptomics, to study brain structure and function within large-scale biobanks with the goal of furthering current understanding of brain and behavioral changes in old age and disease. She is excited to continue pursuing work that leverage novel computational methods and data-driven approaches to facilitate analyses of complex biological systems and to enable personalized approaches in precision medicine. Rowena is also a current NUS Young Fellow and was recently awarded the National University of Singapore Development Grant to support her in the next stage of her academic career. Outside of research, she enjoys a book over a good cup of coffee, good music, and occasionally uncovering vintage gems at the local flea market. |
Samantha Couper |
Samantha Couper is a doctoral student at the University of Canterbury in New Zealand, currently in the first year of my Bioengineering PhD. Having always been fascinated and motivated by understanding how things work, she quickly realised her passion for Engineering. Throughout her undergraduate degree, she developed a keen interest in Bioengineering and began pursuing opportunities in this field, both academically and in industry. She has a particular focus on areas of health and medicine, aiming to better help those who are currently under-served. Her PhD is focussed on improving a non-invasive, alternative breast cancer screening system. She finds it extremely rewarding working with technology with immense potential to help others, which has sparked her passion further. Outside of this, she loves getting outdoors: cycling, running, hiking, and playing sport. She is also a keen crafter and am often embroidering and crocheting in her spare time. Another passion of hers, is connecting with others, both friends and strangers. We can all learn from each other, our differences, and work together to make the world a better place. |
Skyler Van Cruyningen |
Skyler Van Cruyningen is a first year graduate student at UCSD pursuing a two-year thesis based Masters of Science in Bioengineering. His research focuses on the intersection of imaging and histopathology, exploring diagnosis of rectal cancer on MRI during his undergraduate and presently modeling the heart’s response to pulmonary arterial hypertension. He enjoys connecting the dots: be it ideas from different disciplines, people from different teams, or applications from different industries. |
Anna Czarna |
Anna Czarna is currently a medical student at the University of Silesia. She received her PhD degree in 2009 at the Max-Planck-Institute in Munich in the laboratory of Nobel Prize winner Prof. Robert Huber, in Prof. Holak's research group, where she characterized inhibitors of proteins important in tumorigenesis. Her first postdoctoral training took place at MPI and LMU, in the group of Prof. E. Wolf, where she worked on the understanding of the mechanisms of light regulation of the circadian clock. The work describing the structural analyses of critical circadian clock proteins was published as author's in Cell. Another post-doc was held at Harvard Medical School in Boston, USA where she successfully analysed stem cell applications in regenerative medicine, vascular disease and diabetes. She continued her research in regenerative medicine as a staff member at Cardiocentro Ticino in Lugano, Swiss Institute for Regenerative Medicine, where she studied the regenerative potential and formation of new functional cell structures in heart and lungs. The results of these studies became a valuable clinical guideline for the treatment of patients with heart failure of ischemic origin. In 2015, she moved to the Arctic University in Tromso, Norway, to combine structural studies with kinase signaling to identify molecular targets for lung and breast cancer therapy. There she obtained her first major research grant. In 2018, she joined Prof. J. Wang's group at South China University of Technology (SCUT) in Guangzhou, China where she learned about cutting-edge developments in nanotechnology and biomaterials for combined personalized therapies using own organoid platform. In 2020, Dr. Czarna was awarded a prestigious National Agency for Academic Exchange (NAWA) installation grant which allowed her later to establish a research group at the Malopolska Centre of Biotechnology at Jagiellonian University. She is currently combining her scientific experience, supported by multiple national and external funding, with international contacts in interdisciplinary research on the use of regenerative medicine advances, structural biology and Artificial Intelligence modelling. |
Reema Dawar |
Reema Dawar is a rising junior studying Biomedical Engineering at Columbia University's School of Engineering and Applied Sciences. At Columbia, she's involved in the Myers Soft Tissue Lab, using AI to better understand and predict preterm birth. In addition, she's contributed to research at UCLA Medicine understanding current trends in radiology, including the potential of using AI in diagnostics. She's particularly interested in the intersection of technology and women's health. Outside of research, she enjoys playing chess. |
Santiago Enriquez |
Santiago Enriquez is a Master student in Biomedical Engineering at Brown University. His undergraduate thesis focused on the use of V-nets and Transformers for 3D automatic segmentation of HIFU (high intensity focal ultrasound) made lesions on thalamic regions to treat essential tremor symptoms. Currently, he is working on hierarchical learning of the still-in-development AI made by the Numenta team using the Thousand Brain Theory. This AI explicitly uses the human brain structure to try to replicate how the brain learns and interacts with the world. Outside of research, he enjoys boxing, tennis, F1, rugby, traveling, cooking, and films and series. |
Kalman Fabian |
Kalman Fabian is currently a 5th year medical student at the University of Pecs, Medical School. He plans to continue his studies as a radiologist or as an aerospace physician. Getting a PhD is also on his to do list. He is a part of multiple research groups, in different fields, so he has experience in the topics of cutting edge MRI techniques to analyze traumatic brain injuries, MALDI-TOF mass spectrometry in IVF research, and multiple space exploration projects. Also working on a startup with his co-founders. He is passionate about space exploration, innovation and often praises curiosity as one of the best qualities of humans. |
Alvaro Franco |
Alvaro Franco received his B.Eng. in Biomedical Engineering from Universidad Carlos III de Madrid in 2023. His Bachelor Thesis project involved creating a smartphone compatible application for AR-enhanced visualization of delivered radiation during IORT procedures and 3D Slicer module to calculate the dose-volume histogram from the procedure. He is now completing a Sc.M. in Biomedical Engineering at Brown University, working in deep learning assistance for kidney tumor image-guided thermal ablation. His research interests cover imaging acquisition physics, cardiology, fluid mechanics and deep learning applied to medicine. Outside of academics, he enjoys sports, reading, and outside activities. |
Valentina Gigy |
Valentina Gigy is a Biomedical Engineer from the National University of Cordoba (UNC), Argentina. Her academic interests are focused on the intersection of neuroscience, brain-computer interfaces and artificial intelligence with a strong passion for project management and leadership to drive innovation and collaboration in multidisciplinary teams. Her undergraduate thesis was focused on epileptogenic pattern detection in thalamic iEEG signals, integrating deep learning architectures with dynamic spatial filtering techniques to enhance detection accuracy in patients with drug-resistant epilepsy. Beyond her thesis work, she has collaborated with the Computational Neuroengineering Laboratory at the Institute of Applied Mathematics of the Littoral (CONICET-UNL). She also participated in an academic exchange at Pompeu Fabra University in Barcelona. In her free time, she enjoys spending time with family and friends, going out to eat, going to soccer games with her sister and dad, and exploring her passion for fashion. |
Kay Igwe |
Kay Igwe is currently a PhD candidate in Biomedical Engineering in the Heffner Biomedical Imaging Lab (HBIL) under the supervision of Dr. Andrew Laine and is co-mentored by Dr. Jia Guo (Cortex Lab). She earned her Master's degree in Electrical Engineering from Columbia University and her Bachelor's degree in Electrical Engineering with a minor in Mathematics from Texas Tech University. Her research focuses on integrating imaging, spectroscopy, and artificial intelligence to identify biomarkers associated with various biological processes. |
Eugenia Ipar |
Eugenia Ipar is an Electronic Engineer and a third-year PhD candidate at Universidad Tecnologica Nacional, Facultad Regional Buenos Aires. She specializes in cardiovascular signal processing and artificial intelligence, focusing on non-invasive methods to predict cardiovascular health and vascular age through photoplethysmography (PPG) signals. Her research, which emphasizes nonlinear biomarkers, explores innovative deep learning architectures for hardware implementation in clinical decision support systems. Funded by a CONICET scholarship, her work has been published in peer-reviewed journals and conferences. Additionally, Eugenia serves as a Teaching Assistant for "Signals and Systems Analysis" at UTN. |
Vikrant Jaltare |
Vikrant Jaltare is a Ph.D. candidate in the Department of Bioengineering at UC San Diego. He is co-advised by Dr. Gert Cauwenberghs and Dr. Terrence Sejnowski. His research involves developing brain inspired learning rules specifically for probabilistic models in deep learning and AI. He is interested in using biological stochasticity as a feature to develop robust predictive and causal models in healthcare and public health research. He is also passionate about making STEM education more accessible and developing techniques to gauge student engagement and perceptions in interdisciplinary fields like Bioengineering and Computational Neuroscience. When not in the lab, you can find him hiking the beautiful hills of Southern California, learning new recipes or playing guitar. |
Sree Kuntamukkala |
Sree Kuntamukkala is a first-year Biomedical Graduate student at Columbia University with a strong research focus on biomedical imaging, artificial intelligence, and deep learning for medical applications. She earned her bachelor's degree in Chemical Engineering from BITS Pilani. Her work spans tumor segmentation, single-cell RNA sequencing analysis of glioblastoma, and the application of AI-driven methodologies for disease detection. Currently, she is working in the Heffner Biomedical Imaging Lab under the guidance of Professor Andrew Laine on pancreatic tumor segmentation in ultrasound images of mice. She is particularly interested in leveraging artificial intelligence to enhance diagnostic accuracy and improve clinical decision-making. Passionate about Biomedical Imaging and AI, she aims to pursue a PhD in Biomedical Imaging and contribute to high-impact industry advancements. Outside of research, she enjoys playing chess. |
Zhijie Li |
Zhijie Li is currently a first-year PhD candidate in Biomedical Engineering at the National University of Singapore (NUS), specializing in interdisciplinary research that combines mechanical control design, Artificial Intelligence (AI), and wearable sensors for innovative healthcare solutions. His research focuses on developing AI-driven systems for real-time tactile feedback transfer, with applications in surgical robotics, VR medical training, and telemedicine. He earned his master's degree at SUSTech, where his research focused on AI for Science, including Machine Learning, Data-driven approaches, and Computational Fluid Dynamics. Passionate about the transformative potential of AI in healthcare, he is eager to contribute to the ongoing advancement of AI applications in healthcare and biomedical engineering, striving to make a meaningful impact in these fields. |
Judith Anna Miskei |
Judith Anna Miskei, MD is currently a PhD student and a maxillofacial surgery resident at the University of Pecs, Hungary. She graduated from medical school in 2023, and has since combined clinical practice with research. Born in the UK and raised in a multicultural environment, she developed an early interest in human biology and the molecular mechanisms of disease. During medical school, she conducted research on lung cancer diagnostic markers and presented her findings at several international conferences. Currently, her primary focus is on medication-related osteonecrosis of the jaw (MRONJ), which she plans to explore further in her upcoming PhD. She is passionate about bridging clinical insight with scientific inquiry, and she looks forward to deepening her interdisciplinary perspective at the Biocomplexity Summer Academy. |
Yogesh Movendane |
Yogesh Movendane, a recipient of ASTAR Singapore International Graduate Award scholarship, is pursuing his PhD in Biomedical Engineering at the National University of Singapore. He received his Master's by Research in the field of Discovery Neuroscience from the University of Edinburgh. His research focuses on developing multicomponent modules with specific interests in sensors, microfluidic and acoustic modules for lab-on-chip applications to study miR potential in brain cancer prognostication. He is also interested in developing microsystem models to study mechanobiological interactions in cell-to-cell communication. |
Anirudh Natarajan |
Anirudh Natarajan is a first year Biomedical Engineering Ph.D. candidate at Columbia University, focusing on neuroengineering under the guidance of Dr. Paul Sajda. His research interests lie at the intersection of brain-computer interfaces, neuromodulation, and closed-loop systems. He holds dual degrees in Computer Science and Cognitive Science from UC Berkeley, where his research spanned hyperdimensional computing, deep learning, and computational neuroscience. His work has been presented at major conferences like ICRA, emphasizing neuro-inspired computing and multimodal sensor fusion. Anirudh has also worked at Apple and Amazon, implementing machine learning solutions at scale. He hopes to advance the field of neurotechnology by developing novel brain-computer interfaces, potentially leading to breakthrough applications in medical diagnostics and assistive technologies. |
Jade Pinkenburg |
Jade Pinkenburg is a third-year PhD student in the Electrical Engineering & Computer Sciences Department at UC Berkeley, advised by Prof. Rikky Muller. Broadly, his research aims to harness advances in semiconductor technology and scientific discoveries in neuroscience and biology to develop implantable devices that can effectively diagnose and treat medical conditions, as well as to enable doctors and scientists to more easily understand the nervous system and its interactions with disease. He is a recipient of the NSF Graduate Research Fellowship and the Berkeley Fellowship, and holds a B.S. in Electrical & Computer Engineering from Cornell University. When he's not in the lab, he maximizes his time outside and enjoys hiking, surfing, playing musical instruments, and traveling. |
Bhavyansh Sabharwal |
Bhavyansh Sabharwal is a Computer Science major at Columbia University. He works as a BME Software Research Assistant at the Heffner Biomedical Imaging Lab, focusing on biomedical imaging and AI applications. Previously, he conducted theoretical physics research at IUPUI, where he explored nonlinear dynamics and computational modeling. Bhavyansh is also the co-founder of the Homebrew Computer Club (HCC.NYC), a Columbia-based organization dedicated to independent experimentation and rapid prototyping. He has completed software engineering internships at Telly and Standard Partners, where he worked on AI-driven applications and automated data extraction. Additionally, he has extensive robotics experience, having led his VEX Robotics team to the World Championships and developed advanced control algorithms for autonomous navigation. |
Swetha Saravanan |
Swetha Saravanan is a BS/MD student majoring in Biomedical Engineering and minoring in Medicine and Society from the University of Houston and Baylor College of Medicine. She is an undergraduate research assistant who works on the treatment of glioblastoma multiforme (GBM). She has published two review papers in the journals of Health and Technology and Global Biosecurity. She is also working with her peers on developing a machine learning (ML) model using 12 classifiers, focusing on CTG analysis using ML as a cost-effective and accessible approach for facilitated identification of fetal hypoxia. Upon graduation, she will be attending Baylor College of Medicine as a medical student in the summer of 2025. |
Jessica Sewell |
Jessica Sewell is currently pursuing a PhD after receiving her BE(Hons) in Mechanical Engineering, with a minor in Biomedical Engineering, from the University of Canterbury in New Zealand in 2023. Her research focuses on understanding and improving athletic health, particularly addressing the high rates of Anterior Cruciate Ligament (ACL) injuries among female football players. By developing innovative models and simple digital twins, she aims to create accessible diagnostics for effective athlete monitoring, ultimately enhancing performance and safety. She is dedicated to fostering a culture of injury prevention in sports, ensuring that everyone, especially women, can maintain their health and vitality throughout their lives. Her passion for movement motivates her involvement in outdoor activities, including running, biking, paddling, and hiking. |
Isabel Agreda Sobrino |
Isabel Agreda Sobrino is a seventh-semester Biomedical Engineering student with a strong commitment to innovation in healthcare and the development of cutting-edge medical technologies. She was awarded the UPC First-Place Scholarship, recognizing her academic excellence and leadership in the field. Her work has been internationally recognized, achieving second place in a prestigious bootcamp that honors the best research in Latin America and the Caribbean. Additionally, she has published two Scopus-indexed scientific articles, focusing on hypertension and the development of innovative biosensors for the early detection of Alzheimer's disease. She has hands-on experience in laboratory research and currently works at Siemens Healthineers, where she is responsible for the maintenance and management of high-complexity medical equipment. Her goal is to continue driving technological advancements in healthcare by combining science, engineering, and innovation to improve people's quality of life. |
Katharina Steeg |
Katharina Steeg is a translational doctoral researcher at the University Hospital Giessen, Germany, specializing in medical informatics and signal processing. With a background in biomedicine and bioinformatics, her research focuses on developing an AI-driven diagnostic tool to provide real-time feedback on anatomical integrity and structure for augmented navigation during minimally invasive procedures. Her work bridges disciplines to address the challenges of translating innovative technologies into real-world clinical workflows. She collaborates with scientific laboratories, healthcare providers, and industry partners to explore how AI and digital health solutions can enhance surgical precision, optimize workflows, and improve patient care. Katharina is particularly interested in making healthcare systems more adaptable to technological advancements while ensuring compatibility in clinical practice. |
Tran Van |
Tran Van is a second-year PhD candidate in Biomedical Engineering at the National University of Singapore, focusing on developing biosensors, microfluidic systems, and organ-on-a-chip platforms for healthcare applications. Her research aims to advance early diagnostics and therapeutic solutions by integrating engineering, biology, and medicine. Van holds a Bachelor of Physics from Vietnam National University - Hanoi, where she was the department valedictorian and published several research papers. She has received multiple scholarships and awards for her academic achievements. Currently, her PhD project focuses on developing a point-of-care device for tear analysis to aid ocular surface disease patients, with an interest in integrating AI for improved diagnostics and patient care. |
Jemimah Wambui |
Jemimah Wambui is a passionate biomedical engineering student at Kenyatta University, dedicated to leveraging technology and data science to revolutionize healthcare. She plans to pursue a Master's in Biomedical Informatics and Data Science to deepen her expertise in health informatics, data-driven decision-making, and AI applications in medicine. Building on this, she aims to earn a PhD in Artificial Intelligence in Healthcare, specializing in machine learning, natural language processing, and predictive analytics for clinical advancements. Jemimah is also driving innovation through an interdisciplinary approach, with a keen research focus on the application of Digital Twin technology in personalized medicine. Beyond engineering, she leads MedTech Hub, a collaborative platform that fosters multidisciplinary solutions to biomedical challenges, bringing together experts from diverse fields to advance medical technology. |
Shaunna Wang |
Shaunna Wang is a graduate student in the Bio-Medical Informatics and Bio-Imaging Laboratory (Bio-MIBLab) at Georgia Institute of Technology. She received her B.S. in Life Sciences from National Taiwan University (NTU) and is pursuing an M.S. in Biomedical Engineering. Her research focuses on AI-driven medical imaging, including echocardiographic video analysis for cardiac function assessment and deep learning-based segmentation for scoliosis diagnosis. She has also worked on ECG-based myocardial infarction detection for wearable health monitoring. Her broader interests lie in bridging AI, medical imaging, and computational modeling to enhance clinical decision-making. Outside of research, she enjoys badminton, music, and cooking. |
Paulina Wojcik |
Paulina Wojcik is a third-year medical student at the Academy of Silesia. She aspires to become a child and adolescent psychiatrist and has a strong interest in medical technology and AI-driven healthcare. Before pursuing medicine, she earned a Bachelor's degree in English Philology from the University of Silesia, developing strong communication skills that complement her work in healthcare. As the President of the Student Scientific Association of Clinical Psychology, she leads initiatives at the intersection of medicine, mental health, and technology. She is also an active member of IFMSA and the Interdisciplinary Scientific Association of Histology and Clinical Engineering. Beyond academics, she engages in volunteering and medical outreach, participating in hospital initiatives, educational events, and public health campaigns. She is committed to integrating innovation into medicine to advance diagnostics and treatment. |
Shuang Zeng |
Shuang Zeng is currently he is a 4th-year joint Ph.D. student in biomedical engineering of Georgia Institute of Technology - Emory. Shuang is affiliated with the Bio-Medical Informatics and Bio-Imaging Laboratory (Bio-MIBLab) at Georgia Tech. His research interests mainly focus on self-supervised contrastive learning, explainable AI, vision-language models and medical image processing. He is actively welcome to seek potential cooperation and communication from any researchers. |