🎥 فیلم جلسه اول درس System 2
🔸 موضوع: Introduction & Motivation
🔸 مدرسین: دکتر رهبان و آقای سمیعی
🔸 تاریخ: ۲۱ بهمن ۱۴۰۳
🔸لینک‌ یوتیوب
🔸 لینک آپارات

🚀 We will be live from 19:45. Join us here:
https://www.youtube.com/watch?v=Y4UZNc4eh4U

🎙 Title: The Increasing Role of Sensorimotor Experience in Artificial Intelligence
👨‍🏫 Speaker: Rich Sutton (Keen Technologies, University of Alberta, OpenMind Research Institute)

🚀 Join Michael Littman’s Talk at Sharif University of Technology

🎙 Title: Assessing the Robustness of Deep RL Algorithms
👨‍🏫 Speaker: Michael Littman (Brown University, Humanity-Centered Robotics Initiative)
📅 Date: Friday (Feb 21, 2025)
🕗 Time: 5:30 PM Iran Time
💡 Sign Up Here: https://forms.gle/amgtsGrDVn4mdRai9

🚀 Join Chris Watkins’s Talk at Sharif University of Technology

🎙 Title: From Shortest Paths to Value Iteration to Q-Learning
👨‍🏫 Speaker: Chris Watkins (Professor of Computer Science, Royal Holloway)
📅 Date: Friday (Feb 21, 2025)
🕗 Time: 3:00 PM Iran Time
💡 Sign Up Here: https://forms.gle/ET3Y5jB6Jt9vkQ2x9

@DeepRLCourse

🚀 Join Peter Stone’s Talk at Sharif University of Technology

🎙 Title: Multiagent RL: Cooperation and Competition
👨‍🏫 Speaker: Peter Stone (Professor of Computer Science, University of Texas at Austin)
📅 Date: Thursday (Feb 27, 2025)
🕗 Time: 3:30 PM Iran Time
💡 Sign Up Here: https://forms.gle/M4QxTUWimGyvUmPv7

@DeepRLCourse

🔥 Open Position: Research Intern/Collaborator – Virtual Staining of Histopathology Images

🔸 Join our CVPR conference paper project on Virtual Staining!
We are looking for dedicated researchers, with a preference for local candidates, as this role requires 20 hrs/week of in-person collaboration.

🔸 Technical Requirements:
💠 Strong English reading & writing skills for technical documentation.
💠 Hands-on experience with:
    🌀 PyTorch & deep learning fundamentals
    🌀 Running & troubleshooting GitHub repositories
    🌀 Exposure to generative models (GANs, diffusion models) is a plus!
    🌀 Ability to write clean, organized Python code

🔸 Non-Technical Requirements:
💠 Commitment to 20 hrs/week in-person work at our lab
💠 Persistence in solving technical challenges (e.g., debugging model training)
💠 Strong teamwork & communication skills
💠 Curiosity about medical imaging & generative AI

🔸 Why Join?
💠 Mentorship from Dr. Rohban & the RIML Lab team
💠 Hands-on experience with generative models (GANs/Diffusion) for medical imaging
💠 Work with collaborative coding (GitHub) & Linux-based workflows
💠 Opportunity for CVPR-tier co-authorship & strong recommendation letters

📩 How to Apply
The deadline for submission has already passed

🚀 Join Jakob Foerster’s Talk at Sharif University of Technology

🎙 Title: Reinforcement Learning at the Hyperscale!
👨‍🏫 Speaker: Jakob Foerster (Associate Professor, University of Oxford)
📅 Date: Friday (Mar 7, 2025)
🕗 Time: 1:00 PM Iran Time
💡 Sign Up Here: https://forms.gle/HYDizuvMkxVGA5hu7

@DeepRLCourse

کد تخفیف ۵۰ درصدی مخصوص اعضای کانال:
RIMLLab

🚀 Open Research Position: Hallucination Detection & Mitigation in Vision-Language Models (VLMs)

We are looking for motivated students to join our research on hallucination detection and mitigation in Visual Question Answering (VQA) models at RIML Lab.

🔍 Project Description
Visual Question Answering (VQA) models generate text-based answers by analyzing an input image and a query. Despite their success, they still suffer from hallucination issues, where responses are incorrect, misleading, or not grounded in the image content.
This research focuses on detecting and mitigating these hallucinations to enhance the reliability and accuracy of VQA models.

📄 Relevant Papers
"Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding"
"CODE: Contrasting Self-generated Description to Combat Hallucination in Large Multi-modal Models"
"Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization"

🔹 Must-Have Requirements
- Strong Python programming skills
- Knowledge of deep learning (especially VLMs)
- Hands-on experience with PyTorch
- Ready to start immediately

⏳ Workload
Commitment: At least 20 hours per week


📌 Note: Filling out this form does not guarantee acceptance. Only shortlisted candidates will receive an email notification.

📅 Application Deadline: March 28, 2025
🔗 Apply here: Google Form

🛑 This position is now closed. Shortlisted candidates have been notified by March 30, 2025. Thank you to everyone who applied! Stay tuned for future opportunities.

📧 For inquiries: iamirezzati@gmail.com
💬 Telegram: @amirezzati

@RIMLLab
#research_position #ML_research #DeepLearning #VQA

گروه Geometric Deep Learning به مباحث مرتبط با اشیاء هندسی می‌پردازد. پیش‌بینی رفتار پروتئین‌ها یا مولکول‌های شیمیایی که ساختار هندسی‌شون در اینکه چطوری در عمل رفتار می‌کنن مؤثره. مباحث تئوری مرتبط باهاش یه چیزی میان گراف و جبر و دیپ لرنینگ هست.
تحت نظر آقای سید محمد حسینی، دانشجوی دکترای مشترک دکتر جعفری و دکتر رهبان

https://docs.google.com/forms/d/e/1FAIpQLSd8FEHOmscpFo6R2SEA5LbFQ8fyM518yXIe07G29XYLk6Rgzg/viewform

پست لینکدین دکتر رهبان

نوروز باستانی و سال جدید با آغاز بهار شروع شد. در سال گذشته موقعیت‌های بسیاری را با دانشجویانم و اعضای آزمایشگاه RIML دور یکدیگر جمع گشتیم و جشن گرفتیم. من معتقدم که دانشجویان مهم‌ترین سرمایه‌های این کشور هستند و ما باید قدر ایشان را بیشتر بدانیم.
در سال گذشته ما در آزمایشگاه سعی داشتیم تا در جهت حل مشکلات کشور و علم قدم برداریم و در جهت بهتر کردن زندگی انسان‌ها تلاش کنیم. همچنین ۱۰ مقاله در کنفرانس‌ها و ژورنال‌های برتر CVPR, ICLR, ICML, NeurIPS, TMLR, ECCV با موضوع اعتمادپذیری در یادگیری ماشین منتشر کردیم.
همچنین در برگزاری ورکشاپ Spurious Correlation and Shortcut Learning در کنفرانس ICLR2025 که برای اولین بار توسط یک تیم از ایران در یکی از کنفرانس‌های برتر هوش مصنوعی اتفاق می‌افتد، تلاش کردیم.
همچنین اعضای آزمایشگاه نقش مهم و پررنگی در برگزاری مسابقه بین‌المللی هوش مصنوعی RAYAN داشتند.
ممنون از تیم فوق‌العاده، همکاران و حمایت‌کنندگان که این سال را الهام‌بخش و فوق‌العاده کردند.

#open_position -> closed

We are seeking 2–3 interns/collaborators:
- 2 positions focused primarily on technical aspects 
- 1 position with a 50/50 focus on theoretical and applied Machine Learning 

If you are interested in research on Histopathology Whole Slide Images (WSIs), VLMs, vLLMs, Self-Supervised Learning (SSL), and/or Theoretical Machine Learning—with the goal of submitting papers to conferences such as NeurIPS, ICLR, CVPR, ICASSP, WACV, or journals like IEEE Transactions on Medical Imaging, TMLR, and JMLR—please send your CV to hussein.jafarinia@gmail.com

For more context, you can review these relevant papers:
1. https://arxiv.org/abs/2408.08258
2. https://arxiv.org/abs/2306.11207
3. https://ieeexplore.ieee.org/document/10643565


Technical Requirements
- English proficiency at least B2 (preferred) or B1 
- Familiarity with Machine Learning and PyTorch 
- Experience with Git
- Ability to run and interpret academic GitHub repositories 
- Clean coding practices
- Solid understanding of Mathematics; preferably very strong in Probability and Statistics, Stochastic Processes, Information Theory, Machine Learning Theory, and High-Dimensional Statistics [for the theory-focused candidate]

Non-Technical Requirements
- Persistent and “try-hard” attitude 
- Available on-call 
- Enthusiastic about learning new platforms 
- Willing to dedicate significant time 
- Extremely resilient, comfortable with frequent schedule changes, and unafraid of polite rejections [for the theory-focused candidate]

Benefits
- Supportive RIML environment 
- Opportunity to work closely with Dr. Rohban (mainly for the theory-focused position) 
- Possibility of a research-related recommendation letter from Dr. Rohban

Final Thing
Guys, I really mean everything stated above for the Non-Technical Requirements, if you don’t meet them, please do’t email.

Research Position at the Center for Information Systems and Data Science, Sharif University in Collaboration with a Top-Three Global Institution or medical university school in  Bioinformatics.

Projects Descriptions:

1. Utilizing Large Language Models and Retrieval-Augmented Generation (RAG): Applying  knowledge graph  in medicine, inspired by Stanford University's work.

2. Predicting Profiles for Protein Sequences Using Natural Language Processing: Leveraging the performance of transformers in natural languages by treating protein sequences as a language, similar to Microsoft's research.

3. Applying Manifold Learning and Riemannian Geometry in Protein Dynamics Analysis: Designing and predicting the effects of protein dynamics using approaches akin to those from Cambridge University.

✅Requirements:
A bachelor's and master's student with strong implementation skills and clean coding in artificial intelligence, capable of reading and analyzing new Bioinformatics papers, ideating and extensively testing with well-known deep and reinforcement learning architectures, and possessing intermediate Bioinformatics or biology knowledge.

💥This project will be conducted in collaboration with three professors from Sharif University's Computer and Electrical Engineering faculties and supervised by a senior scientist from one of the top three universities in the United States.

🆔To apply and submit your CV, please contact via email with the subject line "Research Position in Bioinformatics":
data-icst@sharif.edu

فیلم جلسه ۴ الی ۷ درس System 2 در آپارات و یوتیوب آزمایشگاه آپلود شد.

یوتیوب
آپارات

تا جلسه ۱۲ آپلود شد.

🚀 Join Nan Jiang’s Talk at Sharif University of Technology

🎙 Title: Rethinking the Theoretical Foundation of Reinforcement Learning

👨‍🏫 Speaker: Nan Jiang (Associate Professor, University of Illinois Urbana-Champaign)
📅 Date: Thursday (Apr 24, 2025)
🕗 Time: 7:00 PM Iran Time
💡 Sign Up Here: https://forms.gle/KMjp2cGrnWCqSJAh7

@DeepRLCourse

دوستان عزیزی که درخواست دادین متاسفانه تعداد زیادی از ایمیل‌هاتون اسپم شده بود و یک‌مقدار فرایند بررسی طولانی‌تر میشه. ایشالا تا چند روز آینده به همه پاسخ نهایی اعلام میشه.

🚀 Join this insightful Discussion at Sharif University of Technology

🎙 Subject: Exploration in Reinforcement Learning

👨‍🏫 Guest: Ian Osband (Researcher in Artificial Intelligence, formerly at DeepMind and OpenAI)
📅 Date: Thursday (May 1, 2025)
🕗 Time: 3:00 PM Iran Time
💡 Sign Up Here: https://forms.gle/TWqkmomDAKDdioxu5

@DeepRLCourse

🚀 Join Benjamin Eysenbach’s Talk at Sharif University of Technology

🎙 Title: Self-Supervised Agents: Exploring and Learning with Minimal Feedback

👨‍🏫 Speaker: Benjamin Eysenbach (Assistant Professor, Princeton University)
📅 Date: Thursday (May 1, 2025)
🕗 Time: 4:30 PM Iran Time
💡 Sign Up Here: https://forms.gle/j4pUEa89N8kzCRpb9

@DeepRLCourse