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--- 2026-27:fall [2026/06/19 13:30] – [Dialect bias in LLMs] smaqsood
+++ 2026-27:fall [2026/08/12 17:11] (current) – vashistp
@@ Line 34: / Line 34: @@
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+==== AI for medical imaging ====
+**[added 2026-06-19]**
+**Course:**  {EECS4080/EECS4088/4070 (only if the student also takes 4080 or 4088 with Prof. Laleh)}
+**Supervisor:**  Laleh Seyyed-Kalantari
+**Supervisor's email address:**  lsk@yorku.ca
+**Project Description:**
+We are developing deep learning models for medical image diagnostics and evaluating their biases.
+**Required skills:**
+  - Machine learning courses
+  - Programing in Python and PyTorch
+  - Experience in deep learning and LLMs
+  - GPA in A, A+ range or demonstration of existing successful projects in machine learning. GPA below B+ will not be considered.
+I encourage students who are motivated for real, impactful research to apply. Those who may be willing to take the project and continue it to get to the publication stage. Upon successful research experience, students will be considered for NSERC USRA/LURA and Vector Institute Master Award nomination and Connected Minds graduate scholarship (in case they apply for the Master's program at York). So far, our team have had 100% award acceptance rate in diverse program for graduate students.
+**Recommended skills:**
+  - Experience in computer vision
+**Instructions:**
+If you would like to apply, please complete the [[https://docs.google.com/forms/d/e/1FAIpQLSdQk7ChC59SqY-dVYmNPfzkAJWWLpeugXmYrU-NK9-EN0GH8g/viewform | Responsible AI Lab's undergraduate research project form]].
+[[https://responsibleai.eecs.yorku.ca/index.html | Learn more about the Responsible AI lab]].
+==== Bias in Vision Language Models ====
+**[added 2026-06-19]**
+**Course:**  {EECS4080/EECS4088/4070 (only if the student also takes 4080 or 4088 with Prof. Laleh)}
+**Supervisor:**  Laleh Seyyed-Kalantari
+**Supervisor's email address:**  lsk@yorku.ca
+**Project Description:**
+ If you give a Vision Language Model to interpret a neutral image, the interpretation varies by the demographic that we mentioned in the image description. For example, if you ask it to interpret an image related to Western country, it focuses on the positive side, while for the same image, it describes the negative side if you say the image belongs to an African country. Similarly, we want to develop benchmarks to evaluate the bias of VLMs in multi-lingual settings, i.e., if the language is Persian, vs English or Chinese, etc., how will the biases change? We can adjust the project based on the native language of students who take the project.
+Required Skills: Looking for highly motivated students with a GPA in A, A+ range. Please send your CV, all your transcripts to date, and any prior experience (if any) with Python, PyTorch, deep learning, and LLMs. Please list all languages that you are familiar. For this particular project, please list if you have other native languages besides English.
+**Required skills:**
+  - Machine learning courses
+  - Programing in Python and PyTorch
+  - Experience in deep learning and LLMs
+  - GPA in A, A+ range or demonstration of existing successful projects in machine learning. GPA below B+ will not be considered.
+I encourage students who are motivated for real, impactful research to apply. Those who may be willing to take the project and continue it to get to the publication stage. Upon successful research experience, students will be considered for NSERC USRA/LURA and Vector Institute Master Award nomination and Connected Minds graduate scholarship (in case they apply for the Master's program at York). So far, our team have had 100% award acceptance rate in diverse program for graduate students.
+**Recommended skills:**
+  - Experience in computer vision
+**Instructions:**
+If you would like to apply, please complete the [[https://docs.google.com/forms/d/e/1FAIpQLSdQk7ChC59SqY-dVYmNPfzkAJWWLpeugXmYrU-NK9-EN0GH8g/viewform | Responsible AI Lab's undergraduate research project form]].
+[[https://responsibleai.eecs.yorku.ca/index.html | Learn more about the Responsible AI lab]].
 ==== Dialect bias in LLMs ====
@@ Line 62: / Line 122: @@
 **Instructions:**
-If you would like to apply, please complete the [[https://docs.google.com/forms/d/e/1FAIpQLSdQk7ChC59SqY-dVYmNPfzkAJWWLpeugXmYrU-NK9-EN0GH8g/viewform | Responsible AI Lab's undergraduate research project form]] form.
+If you would like to apply, please complete the [[https://docs.google.com/forms/d/e/1FAIpQLSdQk7ChC59SqY-dVYmNPfzkAJWWLpeugXmYrU-NK9-EN0GH8g/viewform | Responsible AI Lab's undergraduate research project form]].
 [[https://responsibleai.eecs.yorku.ca/index.html | Learn more about the Responsible AI lab]].
@@ Line 178: / Line 238: @@
 ** Required skills or prerequisites: **EECS 4412 or EECS4404
+Data Analysis, Report Writing, Python programming, web app development, appetite for research
+** Instructions:** send a CV, transcript, statement of interest, and skills to the instructor (Pooja).
+----
+==== Adaptive Routing for Cost-Efficient Autonomous Email Systems ====
+** [added 2026-08-08] **
+** Course:**  {EECS4088}
+** Supervisors:**  Pooja Vashisth
+** Supervisor's email address: ** vashistp@yorku.ca
+** Project Description: ** This project aims to implement Agentic system for an email assistant.
+This project designs and implements a multi-agent email processing system that routes incoming emails to different handlers based on email type, rather than always invoking an expensive large language model (LLM). The system classifies emails into categories such as acknowledgment, meeting request, FAQ, and emotional, and dispatches each to the cheapest appropriate handler — including a template engine, cache, retrieval module, calendar integration, and LLM fallback. A DistilBERT classifier is implemented as an upgrade to a rule-based baseline, enabling a direct comparison. The system is evaluated on routing accuracy, token cost, and response quality against multiple baselines, with the goal of demonstrating meaningful cost reduction without quality degradation.The aim is to use and test the results and develop a strong research writing of publishable nature.
+This project is an academic research in nature as it equips the student with skills in research paper writing, survey, text analytics, NLP tools, and data visualization.
+** Required skills or prerequisites: **
 Data Analysis, Report Writing, Python programming, web app development, appetite for research