Narges Norouzi

Assistant Teaching Professor at EECS Berkeley

Bio: Narges Norouzi received her MS and Ph.D. from the University of Toronto, in 2014 and 2017, respectively, focusing on applied deep learning. She has since been involved in working on applied machine learning projects with a focus on biology and education. Her CS education research focuses on using artificial intelligence in the classroom through building AI-based educational technology. She also leads student-centered programs that promote equity and access. Her work has been supported by Defense Advanced Research Projects Agency (DARPA), National Science Foundation (NSF), and industry.

Recent news:

[March 2024] Highlights of my students' work at SIGCSE 2024:

[February 2024] AAAI 2024 - RetLLM-E: Retrieval-Prompt Strategy for Question-Answering on Student Discussion Forums.

[December 2023] NeurIPS-GAIED 2023 - Conversational programming with llm-powered interactive support in an introductory computer science course.

[October 2023] Received an award for Proficiency-Based Learning for Programming from Google ($75K).

[September 2023] Received an award for inclusion research from Google ($60K).

[August 2023] Received an award from California Learning Lab for Building Inclusive and Collaborative Foundations in Data Science ($450K).

[April, 2023] UC Berkeley EECS News coverage of NSF IUSE awards.

[April, 2023] Our project "CUE-P: Establishing Servingness in Computing through Baskin Engineering Excellence Scholars Program" has received a $1.93M award from the National Science Foundation. Project duration: 06/2023 - 05/2028.

[December 28, 2022] Our project "Transforming Introductory Computer Science Instruction with an AI-Driven Classroom Assistant" as a collaboration between UC Berkeley and North Carolina State University has received a $2M award from the National Science Foundation. Project duration: 05/2023 - 04/2027.

Education.

  • 2014-2017

    Ph.D. in Computer Engineering, University of Toronto

    Thesis: “Time­-Frequency Analysis of Alcohol Withdrawal Tremors”
    Supervisor: Prof. Parham Aarabi

  • 2012-2014

    MASc in Computer Engineering, University of Toronto

    Thesis: “Multi-Modal Heartbeat Estimation on an iPhone”
    Supervisor: Prof. Parham Aarabi

  • 2008-2012

    BSc in Computer Engineering, Sharif University of Technology

    Thesis: “Dress Mapping on Query’s Body from 4 Points of View Using 3D Computer Vision”

Research.

Selected Publications.

  • "RetLLM-E: Retrieval-Prompt Strategy for Question-Answering on Student Discussion Forums" M. Miroyan, C. Mitra, R. Jain, V. Kumud, G. Ranade, and N. Norouzi, Proceedings of the AAAI Conference on Artificial Intelligence, 2024.
  • "EIT: Earnest Insight Toolkit for Evaluating Students’ Earnestness in Interactive Lecture Participation Exercises M. Miroyan, S. Weng, R. Shah, L. Yan, and N. Norouzi, Proceedings of the 55th ACM Technical Symposium on Computer Science Education, 2024.
  • "Towards Attention-Based Automatic Misconception Identification in Introductory Programming Courses" M. Hoq, J. Vandenberg, B. Mott, J. Lester, N. Norouzi, and B. Akram, Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 2, 2024.
  • "Elevating Learning Experiences: Leveraging Large Language Models as Student-Facing Assistants in Discussion Forums" C. Mitra, M. Miroyan, R. Jain, V. Kumud, G. Ranade, and N. Norouzi, Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 2, 2024.
  • "Conversational Programming with LLM-Powered Interactive Support in an Introductory Computer Science Course" J. Zamfirescu-Pereira, L. Qi, B. Hartmann, J. DeNero, and N. Norouzi, NeurIPS’23 Workshop: Generative AI for Education (GAIED), 2024.
  • "Programmable Delivery of Fluoxetine via Wearable Bioelectronics for Wound Healing in Vivo H. Li, H.-y. Yang, N. Asefifeyzabadi, P. Baniya, K. Zlobina, H.-C. Hsieh, T. Nguyen, C. Hernandez, H. Carrion, M. Tebyani, H. Carrión, J. Selberg, L. Luo, M. Alhamo, A. Soulika, M. Levin, N. Norouzi, M. Gomez, M. Zhao, M. Teodorescu, R. R. Isseroff, and M. Rolandi, Advanced Materials Technology, 2023.
  • "FEDD-Fair, Efficient, and Diverse Diffusion-Based Lesion Segmentation and Malignancy Classification" H. Carrión and N. Norouzi, International Conference on Medical Image Computing and Computer-Assisted Intervention, 2023.
Google Scholar

Teaching.

Contact.

norouzi [at] berkeley [dot] edu
  • 775, Soda Hall Building,
  • Berkeley, CA, 94709