Training and collaboration
Drs. Herasevich and Pickering are dedicated to training the next generation of researchers and collaborating with others on healthcare innovation.
Email us for more information.
Training opportunities
The Acute Care Informatics Laboratory offers a structured full-time research trainee experience for people interested in clinical informatics, critical care research and applied artificial intelligence (AI) in acute care settings.
Research trainees become active members of our lab and participate fully in ongoing projects, multidisciplinary meetings and platform development activities. Trainees engage in real-world research across surveillance systems, AI model development, and ICU implementation science, including AMP and CEDAR. Our lab emphasizes hands-on involvement rather than observational learning.
Each trainee is paired with faculty mentors and assigned a defined research project aligned with lab priorities. In addition to project-specific work, trainees participate in lab conferences, data review sessions, manuscript development meetings, and collaborative discussions with clinicians, engineers and data scientists.
The mentored experience includes:
- One-on-one faculty guidance.
- Training in clinical data extraction, analysis and interpretation.
- Exposure to electronic health record-based research infrastructure and real-time analytic platforms.
- Coaching in scientific writing, abstract preparation, and poster and oral presentations.
- Participation in manuscript development and peer-reviewed publication efforts.
Trainees are expected to contribute meaningfully to scholarly output. Most trainees produce multiple abstracts and manuscripts during their training period, with opportunities for first-author publications. Accepted abstracts are submitted to national and international meetings in critical care, informatics and digital health.
This program is designed for people seeking intensive research immersion before residency, fellowship, graduate training or advanced research careers.
The trainee position requires an on-site full-time commitment and is limited to one year. Start dates are flexible. Funding support isn't provided for this position. Trainees are expected to secure independent or sponsor support. Exceptional trainees may be considered for extended research fellow opportunities based on performance and project alignment.
Collaborative partnerships
We welcome inquiries from medical device, digital health and software companies interested in collaborative partnerships in AI-enabled, data-driven critical care innovation.
If your organization is developing intelligent monitoring systems, clinical decision-support tools, sensing technologies or advanced analytics platforms for acute care environments, we are interested in exploring translational research and validation opportunities.
We also encourage fellows, clinicians, engineers and data scientists interested in research training or collaborative projects in applied clinical informatics and critical care AI to contact us.
Alumni
Our lab has hosted numerous trainees. Alumni we've trained during the past decade include:
Research fellows
- Keivan Nalaie, Ph.D., 2023-2025
- Juan P. Garcia-Mendez, M.D., 2022-2024
- Aysun Tekin, M.D., M.S., 2022-2024
- Ivan Ayala, M.D., 2022-2023
- Julia Pinevich, M.D., 2018-2022
- Quan Do, Ph.D., 2019-2021
- Andrey Oleinik, M.D., 2016-2017
- Mohamed Seisa, M.D., 2016-2017
Research trainees
- Ankita Gupta, 2024-2025
- Shashank Gupta, 2024-2025
- Ivan Khapov, M.D., 2022-2023
- Hsin-Yi Wang, M.D., 2020-2021
- Elizabeth Glancova, M.D., 2019-2020
- Prabij Dhungana, M.D., 2017-2018
- Rizwan Siwani, M.D., 2016-2018
Clinical fellows
- Amos Lal, M.B.B.S., 2022-2023
Residents
- John M. Nathan, M.D., D.D.S., 2022-2024
- Matt Johnston, M.D., 2019-2020
- Kirill Lipatov, M.D., 2019-2020
- Matt Nolan, M.D., 2014-2018
Visiting scholars
- Laura Amenda, 2023-2024
- Run Zhou Ye, M.D./Ph.D., 2022-2024
- Hong Bo, M.D., 2018-2019
- Jun Guo, M.D., 2017-2018
- Bo Wang, M.D., 2016-2017