Case Studies in AI and Biotech: Practical Tools from CSULB Faculty
Leads: Dr. Shadnaz Asgari, Dr. Deepali Bhandari, Dr. Aparna Sreenivasan
In this session, the CSULB faculty will share how they've applied AI in their biotechnology research, demonstrating the power of AI in advancing the field. Each speaker will present case studies from their work, showcasing AI-driven approaches in areas like healthcare and biomedical engineering. Following the presentations, the speakers will introduce user-friendly AI tools, such as Google AutoML, KNIME, and Teachable Machine, which require minimal coding. Finally, participants will join interactive group discussions to explore how these platforms can be used in their own research or teaching.
Date/Time: January 11, 2025, 10:15 AM - 12:00 PM
Location: Hyatt Regency Orange County, Garden Grove, CA
Speakers (alphabetical order):
- Dr. Shadnaz Asgari
- Dr. Arjang Fahim
- Dr. Ava Hedayatipour
- Dr. Derek Hu
- Dr. Sara Nourazari
Workshop Schedule:
10:15 - 10:40 AM | Research Presentations (25 minutes)
CSULB faculty will present their AI-driven research, demonstrating the integration of AI in biotechnology. Each speaker will share insights from their work, showcasing how AI and machine learning have advanced their projects.
(Approx. 5 minutes per speaker)
10:40 - 10:50 AM | Q&A Session (10 minutes)
An opportunity for participants to ask questions and engage in discussion related to the research presentations.
10:50 - 11:15 AM | AI Platform Demos (25 minutes)
Each speaker will introduce and demonstrate one user-friendly AI platform that requires minimal coding. Platforms include Google AutoML, KNIME, Teachable Machine, and others.
(5 minutes per demo)
11:15 - 11:50 AM | Group Discussions (35 minutes)
Participants will join small groups to brainstorm how the AI platforms introduced in the session can be applied to their own research or curriculum. Each group will focus on a specific platform.
11:50 AM - 12:00 PM | Sharing Results (10 minutes)
Groups will briefly share their key takeaways and potential applications of the AI tools in their respective fields.
Speaker BIOS
Dr. Shadnaz Asgari ([email protected] )
Dr. Shadnaz Asgari is a Professor in the Computer Engineering and Computer Science Department at California State University, Long Beach (CSULB). She is also a founding faculty member and the first full-term Chair of the Biomedical Engineering Department at CSULB. With 15 years of experience in patient-centered applications of artificial intelligence (AI) focused on improving diagnostics and treatment outcomes, Dr. Asgari's work advances research at the intersection of AI and healthcare, with a particular emphasis on neuro-critical care. She has authored over 37 peer-reviewed journal articles and 49 conference papers, making significant contributions to AI-driven innovations in biomedical engineering.
Dr. Arjang Fahim ([email protected] )
Dr. Arjang Fahim is a lecturer in the Computer Engineering and Computer Science Department at California State University, Long Beach. His research involves stochastic modeling and computational biology. Dr. Fahim has integrated machine learning algorithms into his research on the Probability Density Profile Analysis (PDPA) method, using AI-driven techniques to address challenges in structural genomics and enhance protein structure determination. His work on applying AI to computational biology demonstrates the potential of machine learning in advancing life sciences.
Dr. Ava Hedayatipour ([email protected] )
Dr. Ava Hedayatipour, an Assistant Professor in the Department of Electrical Engineering at California State University, Long Beach, focuses her research on analog integrated circuits, bio-implantable devices, and low-power designs. She has used machine learning algorithms to optimize designs in biomedical devices, such as bio-implantable sensors and mixed-signal VLSI designs. Dr. Hedayatipour's AI-enhanced work on the development of secure multimodal sensors for healthcare applications demonstrates how machine learning can advance innovation in biomedical devices and healthcare technologies.
Dr. Derek Hu ([email protected] )
Dr. Derek Hu is an Assistant Professor in the Biomedical Engineering and Computer Engineering and Computer Science Department at California State University, Long Beach. His research focuses on developing computational techniques for analyzing neural time-series data in subjects with epilepsy. He utilizes signal processing to identify biomarkers in electroencephalograms. Dr. Hu also incorporates machine learning models to enhance the detection and interpretation of neural biomarkers, advancing the understanding and evaluation of epilepsy and related conditions.
Dr. Sara Nourazari ([email protected] )
Dr. Sara Nourazari is an Associate Professor in the Department of Health Care Management at California State University, Long Beach. Her research focuses on healthcare systems engineering, where she leverages advanced analytics, AI, and machine learning to optimize healthcare delivery and improve operational efficiency. Dr. Nourazari's expertise includes developing predictive, diagnostic, and prescriptive analytical models that address complex challenges in healthcare operations management. Additionally, she has extensive experience in designing and implementing strategic initiatives for data-centric decision-making in healthcare.
Room Layout needs (rounds, lecture, podium, etc.)
The workshop will need 6-8 round tables with chairs (for breakout session discussion), and a podium with three chairs for the speakers.
AV needs (projector, screen, mics, etc.)
Projector and screen *with ability for participants to project slides/powerpoints, with one mic that can be shared among the presenters, and one mic below the stage for the audience questions.
We will need at least one laptop per round table to use during the breakout session – the participants will be encouraged to bring laptops or a mobile device *on program* that they can use to test the AI platforms as teams. We also need wifi capability.
Supplies needed (paper, post-its, pens, pencils etc.)
Post its and pens for notes during breakout session