Meet the 2025-2026 IDSC Fellows at the Launch Symposium 12/3 3-5PM

Name: Meet the 2025-2026 IDSC Fellows at the Launch Symposium 12/3 3-5PM
Start: 2025-12-03T15:00:00-05:00
End: 2025-12-03T17:00:00-05:00
Location: Newman Alumni Center

December 3 @ 3:00 pm - 5:00 pm

Free

The Frost Institute for Data Science and Computing (IDSC) is pleased to announce the IDSC Fellows chosen for the 2025-2026 academic year. Congratulations to undergraduate student Isaiah Wang, and graduate students Juliette Casemajor, Samuel Courtney, Ramiro Valdes Jara, Stephanie Kim, and Kayla Schwartz.

This is a prestigious designation awarded to six graduate or undergraduate students (sophomore level or above) students.

The vision of the IDSC Fellows Program is to inspire a new generation of leaders in data science to cross the traditional boundaries between disciplines. IDSC joins with University faculty to mentor the Fellows on how to best utilize the University’s cutting-edge advanced computing resources in their proposed research projects. Read more about the IDSC Fellows program.

Join us on Wednesday, December 3, 2026 from 3:00 to 5:00 PM at the Newman Alumni Center Executive Conference Room for the IDSC Fellows Launch Symposium. Hear the IDSC Fellows present their research project proposals, mingle with faculty and other researchers, and enjoy light refreshments.

Please Register (free) if you plan to attend.

Location
Newman Alumni Center | Executive Conference Room
6200 San Amaro Drive, Coral Gables, FL 33146

2025-2026 IDSC Fellows

	Juliette Casemajor 2nd year PhD Student \| Marine Biology + Ecology, Rosenstiel School of Marine, Atmospheric, and Earth Science Academic Advisor: Gabriel Reygondeau, PhD \| Associate Professor, Marine Biology + Ecology, Rosenstiel School IDSC Mentor: TBA PROJECT: “Integrating species connectivity into global species distribution modeling to improve climate-driven biodiversity forecasts” Juliette Casemajor’s research investigates how climate change is reshaping the distribution of marine species, with a particular focus on the role of connectivity. Working in the AquaX lab, she combines global species distribution models with ocean based dispersal simulations to distinguish between habitats that are climatically suitable and those that are biologycally accessible. Her work lies at the intersection of marine ecology, physical oceanography and data science, aiming to provide more ecologically accurate forecasts of climate driven range shifts. As an IDSC Fellow, she plans to leverage high performance computing tools to scale her framework to tens of thousands of species, an essentiel step toward producing global-scale biodiversity projections.
	Sam Courtney 1st year MS Student \| Music Engineering Technology, Frost School of Music Academic Advisor: Tom Collins IDSC Mentor: TBA PROJECT: TBA Sam Courtney is a graduate student in Music Engineering Technology at the University of Miami, working under the mentorship of Dr. Christopher Bennett and Dr. Tom Collins. His research interests span digital signal processing, machine learning, and acoustics. He is a member of the Music Computing & Psychology Lab and a Research Assistant and Software Engineer for the Concerts with Humans and Artificial Intelligence project. As an IDSC Fellow, Sam will investigate direct speech-to-speech translation with a focus on audio and prosodic fidelity, exploring large-scale self-supervised pretraining on raw speech by leveraging high-performance computing resources. His project aims to contribute to more expressive and higher-quality cross-lingual speech and audio technologies.
	Ramiro Valdes Jara 2nd Year PhD Student \| Industrial + Systems Engineering, College of Engineering Academic Advisor: Adam Meyers IDSC Mentor: TBA PROJECT:“A Diffusion-Based Model for Inverse Electrocardiography (ECGI)” Ramiro is a second-year Ph.D. student in Industrial and Systems Engineering at the University of Miami’s Intelligent Complex Systems Laboratory (ICS Lab), advised by Dr. Adam Meyers. His research focuses on time-series analysis and generative modeling, with a special focus on diffusion models for imputation, forecasting and solving inverse problems. Ramiro earned his B.S. in Applied Mathematics and Computing from Universidad Carlos III de Madrid and previously worked on Indexa Capital as a Full-Stack Developer. Additionally, he has collaborated with clinicians and engineers on projects involving hypertensive phenotype analysis and circadian cardiovascular variability. His broader interests include reinforcement learning, graph neural networks and network science. As an IDSC Fellow, he plans to develop a diffusion generative prior for reconstructing heart-surface electrical activity from Body Surface Potential Mapping (BSPM) and 12-lead ECG. The goal is to deliver accurate epicardial potential maps with calibrated uncertainty, improving robustness to noise and anatomical variability. Personal Website for reference: https://ramirovaldesjara.github.io
	Stephanie Kim 2nd year PhD Student \| Human Genomics + Genetics, Miller School of Medicine Academic Advisors: Justin Taylor and Vanessa Aguiar-Pulido IDSC Mentor: TBA PROJECT: “Decoding the Intronic Signature of Cancer: Linking Intron Sybtypes, Splicing Dysregulation and Tumor Biology” Stephanie S. Kim is a second-year Ph.D. student in Human Genetics and Genomics at the University of Miami Miller School of Medicine, under the guidance of Dr. Justin Taylor and Dr. Vanessa Aguiar-Pulido. Her research focuses on developing AI-driven models to decode the dark genome with an emphasis on intronic sub-classifications and splicing vulnerabilities that contribute to tumor development and progression. Stephanie earned her M.S. in Biostatistics from the University of Southern California and her B.S. in Molecular and Cellular Biology from the University of Illinois at Urbana-Champaign, and prior to joining the University of Miami, she worked on the identification of methylation biomarkers, Gastric cancer genomics, and modeling of homologous recombination deficiency at the Precision Medicine Center of Seoul National University Bundang Hospital. Her broader interests include leveraging computational genomics, deep learning, and large-scale sequencing to advance precise and equitable cancer diagnostics and therapeutics.
	Kayla Schwartz GR3 (Year 5) \| MD Medical Scientist Training Program (MSTP) + Cancer Biology (CAB) PhD Student Academic Advisor: Oliver McDonald IDSC Mentor: TBA PROJECT: TBA Kayla Schwartz is a fifth-year MD-PhD candidate in the University of Miami’s Medical Scientist Training Program (MSTP). Her research focuses on the tumor microenvironment of pancreatic ductal adenocarcinoma (PDAC), with an emphasis on understanding how primary and metastatic PDAC differ at the molecular and cellular levels. She integrates molecular biology, single-cell genomics, and computational approaches to uncover mechanisms that drive metastatic progression. Kayla aims to leverage her dual training as a physician-scientist to advance data-driven strategies that improve outcomes for future oncology patients.
	Isaiah Wang 4th Year Undergraduate Student, BA/BSc \| Department of Computer Science/College of Arts and Sciences Academic Advisor: Mohamed Iskandarani \| Project P.I. Mariana Bif IDSC Mentor: TBA PROJECT: TBA Isaiah Wang is an undergraduate student at the University of Miami majoring in Computer Science and Marine Science, with minors in Mechanical Engineering, Mathematics, and Marine Policy. Through a broad range of interdisciplinary research experiences—spanning bioinformatic machine learning, remote sensing, and oceanographic carbon-flux analysis—he has developed a strong interest in applying computational and engineering tools to better understand and explore the ocean. After graduation, he plans to pursue graduate studies in ocean engineering, focusing on autonomous underwater vehicles, marine sensing, and intelligent exploration technologies.

Details

Date: December 3
Time:
3:00 pm - 5:00 pm
Cost: Free
Event Category: IDSC Fellows
Event Tags:Juliette Casemajor, Kayla Schwartz, Ramiro Valdes Jara, Samuel Courtney, Stephanie Kim

Organizer

Frost Institute for Data Science and Computing
Phone 305-243-4962
Email idsc@miami.edu
View Organizer Website

Venue

Newman Alumni Center
6200 San Amaro Drive
Coral Gables, FL 33146 United States + Google Map
Phone 305-284-1934
View Venue Website

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	Juliette Casemajor 2nd year PhD Student \| Marine Biology + Ecology, Rosenstiel School of Marine, Atmospheric, and Earth Science Academic Advisor: Gabriel Reygondeau, PhD \| Associate Professor, Marine Biology + Ecology, Rosenstiel School IDSC Mentor: TBA PROJECT: “Integrating species connectivity into global species distribution modeling to improve climate-driven biodiversity forecasts” Juliette Casemajor’s research investigates how climate change is reshaping the distribution of marine species, with a particular focus on the role of connectivity. Working in the AquaX lab, she combines global species distribution models with ocean based dispersal simulations to distinguish between habitats that are climatically suitable and those that are biologycally accessible. Her work lies at the intersection of marine ecology, physical oceanography and data science, aiming to provide more ecologically accurate forecasts of climate driven range shifts. As an IDSC Fellow, she plans to leverage high performance computing tools to scale her framework to tens of thousands of species, an essentiel step toward producing global-scale biodiversity projections.
	Sam Courtney 1st year MS Student \| Music Engineering Technology, Frost School of Music Academic Advisor: Tom Collins IDSC Mentor: TBA PROJECT: TBA Sam Courtney is a graduate student in Music Engineering Technology at the University of Miami, working under the mentorship of Dr. Christopher Bennett and Dr. Tom Collins. His research interests span digital signal processing, machine learning, and acoustics. He is a member of the Music Computing & Psychology Lab and a Research Assistant and Software Engineer for the Concerts with Humans and Artificial Intelligence project. As an IDSC Fellow, Sam will investigate direct speech-to-speech translation with a focus on audio and prosodic fidelity, exploring large-scale self-supervised pretraining on raw speech by leveraging high-performance computing resources. His project aims to contribute to more expressive and higher-quality cross-lingual speech and audio technologies.
	Ramiro Valdes Jara 2nd Year PhD Student \| Industrial + Systems Engineering, College of Engineering Academic Advisor: Adam Meyers IDSC Mentor: TBA PROJECT:“A Diffusion-Based Model for Inverse Electrocardiography (ECGI)” Ramiro is a second-year Ph.D. student in Industrial and Systems Engineering at the University of Miami’s Intelligent Complex Systems Laboratory (ICS Lab), advised by Dr. Adam Meyers. His research focuses on time-series analysis and generative modeling, with a special focus on diffusion models for imputation, forecasting and solving inverse problems. Ramiro earned his B.S. in Applied Mathematics and Computing from Universidad Carlos III de Madrid and previously worked on Indexa Capital as a Full-Stack Developer. Additionally, he has collaborated with clinicians and engineers on projects involving hypertensive phenotype analysis and circadian cardiovascular variability. His broader interests include reinforcement learning, graph neural networks and network science. As an IDSC Fellow, he plans to develop a diffusion generative prior for reconstructing heart-surface electrical activity from Body Surface Potential Mapping (BSPM) and 12-lead ECG. The goal is to deliver accurate epicardial potential maps with calibrated uncertainty, improving robustness to noise and anatomical variability. Personal Website for reference: https://ramirovaldesjara.github.io
	Stephanie Kim 2nd year PhD Student \| Human Genomics + Genetics, Miller School of Medicine Academic Advisors: Justin Taylor and Vanessa Aguiar-Pulido IDSC Mentor: TBA PROJECT: “Decoding the Intronic Signature of Cancer: Linking Intron Sybtypes, Splicing Dysregulation and Tumor Biology” Stephanie S. Kim is a second-year Ph.D. student in Human Genetics and Genomics at the University of Miami Miller School of Medicine, under the guidance of Dr. Justin Taylor and Dr. Vanessa Aguiar-Pulido. Her research focuses on developing AI-driven models to decode the dark genome with an emphasis on intronic sub-classifications and splicing vulnerabilities that contribute to tumor development and progression. Stephanie earned her M.S. in Biostatistics from the University of Southern California and her B.S. in Molecular and Cellular Biology from the University of Illinois at Urbana-Champaign, and prior to joining the University of Miami, she worked on the identification of methylation biomarkers, Gastric cancer genomics, and modeling of homologous recombination deficiency at the Precision Medicine Center of Seoul National University Bundang Hospital. Her broader interests include leveraging computational genomics, deep learning, and large-scale sequencing to advance precise and equitable cancer diagnostics and therapeutics.
	Kayla Schwartz GR3 (Year 5) \| MD Medical Scientist Training Program (MSTP) + Cancer Biology (CAB) PhD Student Academic Advisor: Oliver McDonald IDSC Mentor: TBA PROJECT: TBA Kayla Schwartz is a fifth-year MD-PhD candidate in the University of Miami’s Medical Scientist Training Program (MSTP). Her research focuses on the tumor microenvironment of pancreatic ductal adenocarcinoma (PDAC), with an emphasis on understanding how primary and metastatic PDAC differ at the molecular and cellular levels. She integrates molecular biology, single-cell genomics, and computational approaches to uncover mechanisms that drive metastatic progression. Kayla aims to leverage her dual training as a physician-scientist to advance data-driven strategies that improve outcomes for future oncology patients.
	Isaiah Wang 4th Year Undergraduate Student, BA/BSc \| Department of Computer Science/College of Arts and Sciences Academic Advisor: Mohamed Iskandarani \| Project P.I. Mariana Bif IDSC Mentor: TBA PROJECT: TBA Isaiah Wang is an undergraduate student at the University of Miami majoring in Computer Science and Marine Science, with minors in Mechanical Engineering, Mathematics, and Marine Policy. Through a broad range of interdisciplinary research experiences—spanning bioinformatic machine learning, remote sensing, and oceanographic carbon-flux analysis—he has developed a strong interest in applying computational and engineering tools to better understand and explore the ocean. After graduation, he plans to pursue graduate studies in ocean engineering, focusing on autonomous underwater vehicles, marine sensing, and intelligent exploration technologies.