Research Opportunities
2023 Research Opportunities
Dr. Christopher Tignanelli - Clinical Decision Support (CDS)
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Research Description:
Clinical Decision Support (CDS), implementation science, multi-modal (computer vision/NLP/structured data) AI-enabled CDS, federated learning, surgical automationFinancial Compensation: Yes
Students Should Have Experience In:
Other desired skills: Robotics or computer vision, Clinical Data Standards
Dr. Sisi Ma - Clinical Causal / Predictive Analysis
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Email: sisima@umn.edu
Research Description:
Applications of causal and predictive analysis in medicineFinancial Compensation: Yes
Students Should Have Experience In:
Other desired skills: N/a
Dr. Peter B. Kang - Genomics / Epidemiological Study of Muscular Dystrophy
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Email: pkang@umn.edu
Research Description:
My laboratory works on a longstanding genomics project that seeks to solve genetically undiagnosed cases of muscular dystrophy, primarily using long read genome sequencing. There are exciting opportunities to develop new pipelines for long read genome sequence analysis on the Oxford Nanopore system, and to work on specific sequence datasets for mutation analysis and to answer other genetic questions.Financial Compensation: Yes
Students Should Have Experience In:
Other desired skills: Enthusiasm and a potential interest in learning about genetics
Dr. Steven Johnson - Secondary Use of EHR / CDS / Data Quality
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Research Description:
Secondary Use of EHR Data, Data Quality, Clinical Decision SupportFinancial Compensation: Yes
Students Should Have Experience In:
Other desired skills: Ability to write proper documentation
Dr. Juan Carlos Rivera-Mulia - Modeling Gene Regulatory Networks
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Research Description:
The Rivera-Mulia Lab (https://sites.google.com/umn.edu/rivera-mulialab) focuses on understanding DNA replication timing, large-scale chromosome organization and their regulation and remodeling during development and evolution. We are also interested in understanding how alterations in nuclear architecture disrupt gene function in human disease and aging. To address these questions, we exploit multi-omics approaches, and are developing integrative models of gene regulatory networks.Financial Compensation: Yes
Students Should Have Experience In:
Other desired skills: SAMTools, BEDTools
Thomas Byrd IV, MD, MS - Evaluation/Implementation of AI-Based CDS
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Research Description:
Evaluation and implementation of AI-based clinical decision support models in healthcareFinancial Compensation: No
Students Should Have Experience In:
Other desired skills: N/a
Serguei Pakhomov, PhD - NLP: Conversational Agents
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Research Description:
Artificial Intelligence; Natural Language and Speech Processing, Conversational Agents; wearable sensors; effects of neurodegenerative disorders and medications on cognitionFinancial Compensation: Yes
Students Should Have Experience In:
Other desired skills: Interest in language modeling; familiarity with deep learning and ability to use standard deep learning libraries (e.g. pytorch, Huggingface, tensorflow))
Terrence Adam, RPh, PhD, MD - Medication Safety, Perioperative Medicine and Clinical outcomes
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Terrence Adam, RPh, PhD, MD
Email: adamx004@umn.edu
Research Description:
My current research covers work related to medication safety, perioperative medicine and clinical outcomes using large clinical data sets and EMR data. I have particular interests around adverse drug events (in a general sense) and clinical outcomes associated with cardiovascular medications.Financial Compensation: No
Students Should Have Experience In:
Other desired skills: Database (SQL) and either R or SAS for statistical work
Lisiane Pruinelli, PhD, RN - Disease Progression Health Outcome Prediction
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Lisiane Pruinelli, PhD, RN
Email: lisianepruinelli@ufl.edu
Research Description:
My research focus is in applying data science methods to clinical data (mostly EHR and some registry) to determine disease progression predictive of multiple health outcomes. I apply multiple methods to incorporate time variance, longitudinal data, and determine the effect of interventions to change/delay certain problems/disease that predict worse health conditions. Currently I am working on different datasets (available in the UMN CTSI data shelter): liver transplantation (EHR and registry), kidney transplantation (EHR) and pain/opioids (EHR).Financial Compensation: No
Students Should Have Experience In:
Other desired skills: N/a
Rui Zhang , PhD FAMIA - Novel NLP Methods for Biomedical Big Data
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Rui Zhang , PhD FAMIA
Email: zhan1386@umn.edu
Research Description:
Our research lab focuses on the development of novel AI specifically natural language processing (NLP) methods to analyze biomedical big data, including published biomedical literature, electronic health records (EHRs), patient-generated data from millions of patients. This research include: i) the secondly analysis of EHR data for patient care, ii) pharmacovigilance knowledge discovery through mining biomedical literature and iii) creation of knowledge base through database integration, terminology and ontology. Our lab is supported by several NIH funds, and are looking for talent informatics graduate students to join our lab. See details at https://ruizhang.umn.eduFinancial Compensation: Yes
Students Should Have Experience In:
Other desired skills: N/a
Erich Kummerfeld, PhD - Data Science and Causal Modeling
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Erich Kummerfeld, PhD
Email: erichk@umn.edu
Research Description:
I have a mixed bag of research, all of which heavily leans on data science and causal modeling, as those are my areas of expertise. Many but not all projects are broadly in psychiatry/psychology/neuroscience. Data types include: clinical data, survey data, fMRI data, EEG data (external and internal), LFP data, EMA data, and gene expression data. Subject matter includes: alcohol use disorder, schizophrenia and psychosis, bipolar disorder, smoking, aging (mostly cellular senescence), health and educational outcomes for school children (especially disparities of marginalized subpopulations). I do a mixture of methods development, best practices research, and applications to solve real world problems. The latter is always done in collaboration with subject matter experts from the appropriate field.Financial Compensation: Yes
Students Should Have Experience In:
Other desired skills: Depends on project
Don Casey, MD, MPH, MBA, MACP, FAHA, CPE, DFAAPL, DFACMQ - Hypertension, Heart Failure, and Sepsis
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Don Casey, MD, MPH, MBA, MACP, FAHA, CPE, DFAAPL, DFACMQ
Email: don.casey@ipo4health.com
Research Description:
Hypertension, Heart Failure and SepsisFinancial Compensation: No
Students Should Have Experience In:
Other desired skills: Evidence-Based Guidelines
David Largaespada, PhD - Functional Genomics for Cancer Gene/Pathway Discovery
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David Largaespada, PhD
Email: larga002@umn.edu
Research Description:
Dr. Largaespada's laboratory is working to exploit functional genomics strategies for cancer gene/pathway discovery and to find therapeutic vulnerabilities. The Largaespada lab has heavilyinvested in the use of a vertebrate-active transposon system, called Sleeping Beauty (SB), for insertional mutagenesis-based, forward genetic screens in mouse somatic cells. Cancer genesand pathways involved in sarcomas, mammary tumors, and brain tumors have been carried out. Ongoing work uses SB to discover factors that drive treatment resistance, metastasis and T celltumor exclusion. Another major focus of the lab is to study peripheral nerve sheath tumors that develop in patients with Neurofibromatosis Type 1 (NF1) syndrome. NF1 is a common andimportant cancer predisposition syndrome. The peripheral nerve sheath tumors these patients develop originate in the Schwann cell lineage. The lab is using synthetic lethal genetic screening, high throughput drug screens, genetically engineered mouse models, and human induced pluripotent stem cell-based models to test new hypotheses about pathogenesis and new treatment approaches. A final area of interest is using RNA sequencing and mass spectrometry-based discovery of human leukocyte antigen (HLA) class I bound peptides to find vaccine targets for cancer. Most of these projects require extensive RNA and/or DNA sequence analyses, sometimes with novel bioinformatic scripting.The Largaespada lab has trained twenty-seven Ph.D. students and twenty-seven postdoctoral fellows. Sixteen of these former trainees have become faculty members. This was madepossible by providing training in rigorous and careful experimental design, analysis and reporting of experiments and research data. He provides a supportive and inclusive laboratory for a diverse set of students and staff. Dr. Largaespada has participated in many training, outreach and education activities – and encourages his trainees to do the same.
https://cancer.umn.edu/staff/david-largaespada
Financial Compensation: Yes
Students Should Have Experience In:
Other desired skills: N/a
Jessica Nielson, PhD - Computational Modeling of Neuropsychiatric Disorders
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Jessica Nielson, PhD
Email: jnielson@umn.edu
Research Description:
Work in my lab focuses on computational modeling of neuropsychiatric disorders, as well as prospectively testing neurological mechanisms of novel treatments being considered for neuropsychiatric disorders.Financial Compensation: No
Students Should Have Experience In:
Other desired skills: N/a