Hamed Amini

A substantial piece of work from Apple led by Iman Mirzadeh, keivan alizadeh vahid, Oncel Tuzel, Samy Bengio, Mehrdad Farajtabar and Hooman Shahrokhi supports the thesis that transformer-based LLMs do not reason--they perform pattern-matching. The team from  also provides a great benchmarking tool--GSM-Symbolic for assessing mathematical and formal reasoning. This supports my anecdotal findings when I evaluated o1 https://lnkd.in/ec72fecb as well as my thoughts on the incompleteness of our assessments of AGI https://lnkd.in/ehBT3HB3

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📣 Calling All Persian-Speaking Researchers and Academics! 🎓 I am excited to introduce a new GitHub repository that contains a LaTeX template for your thesis, specifically designed to be compatible with the Farsi language! 📚 This template is designed to help you focus on the content of your work, while we take care of the formatting and structuring. It's user-friendly, customizable, and complies with academic standards. Whether you're working on your Bachelor's, Master's, or Ph.D. thesis, this LaTeX template can save you hours of work. It comes with pre-defined sections such as Abstract, Introduction, Methodology, Results, Discussion, and References, all in Farsi. The best part? It's open-source! You can modify it as per your needs, and even contribute to the repository to help improve it further. Check out the repository, star it, fork it, and spread the word. Let's make academic writing easier and more efficient for everyone! Link to the repository: [https://lnkd.in/dbxpsZWH] #AcademicWriting #Thesis #LaTeX #OpenSource #GitHub #Farsi

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We are thrilled to introduce Nahid Moradi, MD, a dedicated Stanford Data Ocean graduate and medical doctor from Isfahan University of Medical Sciences in Iran who is currently engaged in translational and clinical research focusing on cancer pathophysiology and treatment. In this testimonial, Nahid shares her enlightening experience with the Stanford Data Ocean platform. Having studied R programming and Python for the past two years, she found the program to be the perfect blend of medical science and data science. The platform offered a user-friendly interface with well-designed Jupyter notebooks, making it easy to navigate and practice coding. Nahid particularly appreciated the AI tutor, which provided insightful guidance whenever she faced challenges. Nahid's favorite aspect of the program was how the courses were tailored for individuals at any level of knowledge in medical science and programming. The practical examples in areas like image analysis, omics, and clinical data allowed her to see how data science could be applied directly to her research. Looking ahead, Nahid plans to leverage the knowledge she gained from Stanford Data Ocean in her ongoing research in cancer pathway physiology and treatment. She aims to integrate deep learning and neural networks with clinical practice image data, such as CT, MRI, and pathology samples, to enhance diagnostic accuracy and improve patient outcomes, especially in cancer care. Nahid emphasizes the importance of bioinformatics, noting that in today’s era, combining medical knowledge with computational tools is essential for advancing diagnostic and therapeutic approaches. She highly recommends the Stanford Data Ocean program to researchers and students in biology and medicine who are interested in integrating data science with clinical science. Join us in celebrating Nahid’s achievements and her exciting journey at the intersection of medicine and data science! We remain committed to empowering women across the globe, with a special focus on the Middle East, Africa, and South America. Through our scholarships, we support their educational and professional development, ensuring they have the necessary resources to thrive and make a lasting impact in their communities. Start your bioinformatics journey with Stanford Data Ocean: https://lnkd.in/ggsKFHWG Fundamentals of Data Science in Precision Medicine and Cloud Computing: https://lnkd.in/dKeqBUn3 Fundamentals of AI/ML in Precision Medicine: https://lnkd.in/dx5UR-SR We believe that anyone who wants a precision medicine education should be able to get one. If you earn less than 70k/yr, you are eligible for a scholarship. Apply here: https://lnkd.in/eqyCP2eZ #DeepData #PrecisionMedicine #Bioinformatics #AI #ML #AIHealthcare #DataScience #ComputationalBiology #Python #MD #Certification #Stanford #StanfordMedicine #Iran #Testimonial #CancerResearch

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Exploring exosomes as therapeutic and drug delivery vehicles for neurodegenerative diseases: in this review article, Zeynab Nouri, Fatemeh Atyabi at Tehran University of Medical Sciences and collaborators highlighted the potential of exosomes in treating neurodegenerative diseases, focusing on the relevant signaling pathways and molecular mechanisms involved https://lnkd.in/eX6rpZ3N They noted that although exosomes possess unique properties beneficial for neurodegenerative therapy, further advancements in surface modification are needed to enhance targeted delivery, bypass the blood-brain barrier, and achieve optimal biodistribution. An article also authored by Ashkan Barfar, Sahra Perseh, Hamidreza motasadizadeh, Samane Maghsoudian, Yousef Fatahi, keyvan nouri, Mohaddese Pourashory Yektakasmaei and Rassoul Dinarvand #extracellularvesicles #exosomes #neurodegenerativediseases #targeteddelivery #Vesiculab

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I'm thrilled to announce the release of two new fine-tuned large language models (LLMs) and a groundbreaking dataset for Persian NLP. 🚀 Shotor (Llama 3 8B): Fine-tuned on the Persian Alpaca Deep Clean dataset. Paya (Aya 23 8B): Also fine-tuned on the same comprehensive dataset. These models are crafted for high-quality performance in various Persian language applications, leveraging the Alpaca Deep Clean dataset which I meticulously processed. The fine-tuning was achieved using Dora for efficiency. Explore the models: Shotor: https://lnkd.in/ddge8CAh Paya: https://lnkd.in/dT55qCH4 Additionally, I’ve released the first Persian DPO dataset for LLM alignment, aiming to set a new standard in Persian language processing. Check out the datasets: Persian Alpaca Deep Clean: https://lnkd.in/d8ejpYRf Persian DPO: https://lnkd.in/dMF2sihF Your feedback and insights are invaluable as we strive to advance Persian NLP. I invite the community to test these models and datasets, and share your thoughts. Feel free to engage and share this post to spread the word! Looking forward to your feedback and collaboration. #NLP #PersianNLP #MachineLearning #AI #LanguageModels #DataScience #HuggingFace

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Our very own Prof. Hermona Soreq, Endowed Slesinger Professor of Molecular Neuroscience, is featured in the "Brain Medicine" journal. Prof. Soreq's groundbreaking work on poly(A) tails, mRNA stability, and acetylcholine is revolutionizing our understanding of brain-body communication across the lifespan. Her research sheds light on stress responses, neurodegenerative diseases, and the intricate workings of the cholinergic system (= one of the most important modulatory neurotransmitter systems in the brain). We invite you to read the below article, which showcases Prof. Soreq's pioneering contributions to molecular neuroscience and her ongoing impact on the field. Edmond and Lily Safra Center for Brain Sciences - ELSC #HebrewUniversity #Neuroscience #BrainResearch #MolecularBiology

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6 Open Positions under National Elite Foundation grant, AI and Quantum Computing We are excited to announce that our project, “Creating Building Blocks for Hybrid Quantum-Classical Neural Networks,” has been awarded the annual grant from the National Elite Foundation of Iran, one of the highest prestigous and competetive national grants. This project integrates deep learning components (such as residual block, dense block, attention layers, etc.) with quantum computing, targeting complex high-variance problems. Successful candidates will receive support from the National Elite Foundation. Qualification Requirements and Conditions: Two Sub-Groups of Positions: * Sub-Group 1 - Three Positions: Candidates should be distinguished winners of prestigious events, including: - Medalists (gold, silver, bronze) from international or national student Olympiads. - Top 1000 rank holders in Regions 1, 2, or 3 of the National Competitive Examination; i.e. Iran Conquer. - Top 100 rank holders in the the National Competitive Examination of art and foreign languages. - Highest rank achievers in the student, scholar, and technologist sections of the Khawarzmi Youth Festival. - 1st to 3rd rank holders in the Kharazmi International Festival. - 1st to 3rd rank holders in the National Student Olympiads endorsed by the Ministry of Science. - 1st to 3rd rank holders in the Farabi Youth Festival. - 1st to 3rd place winners in the "Business Designers" section of the Sheikh Bahai Festival. - Top 10 rank holders in the National Nanotechnology Competition (Student). - 1st to 3rd place winners in problem-oriented competitive events (Shahid Babaei Project), as per the National Elite Foundation regulations. * Sub-Group 2 - Three Position: Candidates must solve the following task and submit the code via email: “Update a simple residual block using a quantum algorithm.” The choice of Python framework is open. Preferred Selection Criteria: - High motivation and goal orientation with a passion for AI and quantum algorithms. - Proficiency in Pytorch or Tensorflow frameworks. - Familiarity with QNN libraries, such as Qiskit. - Strong analytical skills for tackling complex problems. - Excellent problem-solving abilities and grasp of new theories. - Ability to work both independently and collaboratively. - Competence in conducting and reporting research professionally. Benefits of Joining Our Team: - Certificate opportunity from one of the most prestigious academies in the country. - Exciting job opportunities in one cutting-edge interdisciplinary field. - Professional development opportunities. - High scoring potential from the National Elite Foundation. How to Apply: Interested candidates should send their resumes to: - Head of the Group: Ali A. Kiaei, email: [email protected] - Research Assistant: Fatemeh Aqaei, email: [email protected] For more information, please contact Fatemeh Aqaei. We look forward to welcoming talented individuals to our innovative team

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Team of Physics, Math and CS engineers are solving complex molecular biology problems in AI. Almost no biologists 👏 Chai Discovery team is excited to release Chai-1, a new multi-modal foundation model for molecular structure prediction that performs at the state-of-the-art across a variety of tasks relevant to drug discovery. Chai-1 enables unified prediction of proteins, small molecules, DNA, RNA, covalent modifications, and more. Chai-1 model achieves a 77% success rate on the PoseBusters benchmark (vs. 76% by AlphaFold3), as well as an Cα LDDT of 0.849 on the CASP15 protein monomer structure prediction set (vs. 0.801 by ESM3-98B). #Math #AI #Biology https://lnkd.in/gTJEgVBY

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Excited to share that our recent work "Static Graph Approximations of Dynamic Contact Networks for Epidemic Forecasting" is published at Scientific Reports. Thanks to my amazing co-authors Razieh Shirzadkhani, Abby L. and Reihaneh Rabbany. In this work, we propose two novel methods, EdgeMST and DegMST, to approximate the structure of dynamic contact networks with a static graph for epidemic forecasting. This is important for forecasting future trends of ongoing epidemics where future contact networks are not observed. Paper Link: https://lnkd.in/ei4bx58P Github Link: https://lnkd.in/ecgZW_xK

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Really interesting approach to ADC therapeutics with conjugation to silencing mRNA.

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📣 The Smart Software Laboratory at Qom University Selected as one of the Reference Lab for Evaluating Large Language Models in Iran! In its first call for establishing a network of AI product evaluation laboratories, the Ministry of Communications and Information Technology introduced reference labs to set more precise standards and enhance AI services. As part of this initiative, the ICT Research Institute has chosen the Smart Software Laboratory at Qom University as one of the key reference laboratories to collaborate in evaluating and developing standard guidelines for large language models. This achievement represents a significant opportunity to enhance the quality of AI products and take meaningful steps toward improving industry standards. Reference laboratories play a crucial role in standardization efforts and fostering trust in AI-driven systems through their scientific evaluations.

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I'm thrilled to share our work of WelQrate, a benchmark dataset collection setting the gold standard for small molecule drug discovery! 🧪 It features rigorously curated datasets, a robust evaluation framework, and open-source tools for researchers to test and innovate. #WelQrate #DrugDiscovery #NeurIPS2024 #NeurIPS

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🎙️ The First Persian Multi-Speaker Text-to-Speech Model 🎙️ After a long period of hard work during my master’s studies and now in my Ph.D., along with countless experiments and training various models, I’m excited to share the development of the first Persian “multi-speaker” text-to-speech model. This model produces natural-sounding speech and closely resembles the target speaker. The speech in the video below was created using this model, based on the voice of the well-known speaker Behrouz Razavi. Soon, we will release a higher-quality version with better voice cloning and more accurate speaker similarity. Special thanks to Dr. Hossein Zeinali for guiding this project and Shatel for their support in recent months. I’d appreciate your thoughts and any feedback! Note: This video is only for demo purposes to show the similarity to the original speaker’s voice inspired by similar content. Public use of such voices will not occur without proper permissions.

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Exploring Advanced Deep Learning for Medical Imaging I'm thrilled to share our latest research published in Springer Nature: "Innovative Fusion of VGG16, MobileNet, EfficientNet, AlexNet, and ResNet50 for MRI-based Brain Tumor Identification". 🔍 Why is this important? Brain tumor detection has always posed a diagnostic challenge. Our study pushes the boundaries by integrating multiple state-of-the-art deep learning models with an attention mechanism, significantly enhancing classification accuracy and robustness in MRI-based tumor detection. 🎯 What makes it unique? This research pioneers an ensemble approach combining strengths of models like ResNet50 and MobileNet, along with a custom-built attention layer, to refine predictions by focusing on critical MRI regions. 🌐 Check out the open-access paper for all the details: https://rdcu.be/d20Mu 💡 This work aligns closely with our ongoing discussions on leveraging metadata and multi-model AI systems to solve complex problems like reasoning in large-scale datasets. The innovations in this study also underscore the potential of integrating attention mechanisms into diverse AI workflows for more informed decision-making. I would love to hear your thoughts on how this approach might extend to other fields like education or real-time diagnostics. #DeepLearning #MedicalAI #BrainTumorDetection #AttentionMechanism #AIResearch #OpenAccess

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I learned a new word: petavoxel I just came accross an exciting publication in Science by Alexander Shapson-Coe et al. The teams at Harvard University and Google Research, unlocked a new dimension of neural exploration with their "A petavoxel fragment of human cerebral cortex reconstructed at nanoscale resolution." The dataset is so vast, it offers a detailed roadmap of around 57,000 cells and 150 million synapses in just 1 cubic millimeter of brain tissue. To put this in perspective, the world’s largest metropolis, Tokyo, “only” has a population of approximately 40 million people! This 1.4 petabytes of data captures the brain's microstructure in previously unknown detail. https://lnkd.in/e4d8eNcz The implications are profound and uncovering the nuances of brain architecture could revolutionize treatments for conditions like epilepsy, Alzheimer's, and Parkinson's. Also, this is #OpenScience, setting a new bar for neuroscience collaborations and #innovation. Back to #petavoxel : it’s a unit of measurement of tri-dimensional pixels, a whole quadrillion of them! #TheMoreYouKnow #HappyFriday.

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On this day in science Ferid Murat was born. Murat was a American physician and pharmacologist who was a co-winner of the 1998 Nobel Prize for Physiology or Medicine for discovering that a gas, nitric oxide, acts as a signalling molecule in the cardiovascular system. This work, performed in the 1980's, uncovered an entirely new mechanism for how blood vessels in the body relax and widen. It led to the development of the anti-impotence drug Viagra and potential new approaches for understanding and treating other diseases. He was a co-worker with Robert F. Furchgott and Louis J. Ignarro. #chemistry #chemical #structural #inorganicchemistry #inorganic #science #scienceandtechnology #sciencecommunication #scienceeducation #nitricoxide #cardiovascular #nitrosamines #nitrosamine

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🚀 Exciting Announcement: Unveiling Custom Data YOLOv8 Iranian License Plate Detection Project on GitHub! 🌟   I am thrilled to share the launch of my latest endeavor – Custom Data YOLOv8 Iranian License Plate Detection! 🚀 This project is a personalized implementation of the cutting-edge YOLOv8 object detection model, specially tailored for accurate and efficient Iranian license plate detection. Built on the remarkable foundation laid by Ultralytics and leveraging the powerful tools provided by Roboflow, it comes packed with features to simplify the process of training and deploying your custom license plate detection model on any dataset.   Key Highlights: 🌐 Easy to Use: Navigate effortlessly through the training and deployment steps with our comprehensive tutorial, designed to make your custom Iranian license plate detection model a reality. 🤖 Versatile: From images to videos and live camera streams, our project adapts to diverse settings, ensuring seamless license plate detection across multiple scenarios. 🎯 Accurate: Harness the power of the latest YOLOv8 object detection model, known for its exceptional accuracy in detecting and recognizing Iranian license plates. Stay at the forefront of technology with our state-of-the-art solution.   A heartfelt thanks to Ultralytics for paving the way with YOLOv8, and to Roboflow for their invaluable tools and resources in data preparation and augmentation. I'm thrilled to contribute to the community with this innovative project tailored for Iranian license plate detection.   Dive in and explore the possibilities – I hope you find it as valuable as I do!   👉 Check out the project on GitHub: https://lnkd.in/dgAujGDM   Let's revolutionize Iranian license plate detection together! 🌐🚀   Ultralytics Roboflow #YOLOv8 #LicensePlateDetection #IranianAI #GitHubProject #ComputerVision #Ultralytics #Roboflow

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Our new paper has been published last week in NAR!! Dylan D'souza Giwa Olawumi Lihi Bik Hilit Levy Barazany Scojen Institute Reichman University Chimeric Transcripts and RNA-Sequencing database version 8.0 (ChiTaRS 8.0; http://biosrv.org/chitars) is a specialized repository for human chimeric transcripts, containing 47 445 curated RNA transcripts and over 100 000 chimeric sequences in humans. This updated database provides unique information on 1055 chimeric breakpoints derived from public datasets using chromosome conformation capture techniques (the Hi-C datasets). It also includes an expanded list of gene fusions that are potential drug targets, and chimeric breakpoints across 934 cell lines, positioning ChiTaRS 8.0 as a valuable resource for testing personalized cancer therapies. By utilizing text mining on a curated selection of disease-specific RNA-sequencing data from public datasets, as well as patient blood and plasma samples, we have identified novel chimeras—particularly in diseases such as oral squamous cell carcinoma and glioblastoma—now catalogued in ChiTaRS. https://lnkd.in/eS6WqEwk

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