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Greetings Everybody I’m Adithya Srivastava, a final student of NITH pursuing my Bachelor’s in Computer Science and Engineering. Throughout my academic journey, I have found a deep fascination for healthcare and medical technology and have actively taken up related projects. Some projects include Brain tumor analysis and Malaria parasite detection in thin blood smears. My previous experience in handling ECG data(using the Pan-Tompkins algorithm for QRS peak detection) and expertise in medical image analysis propelled me toward this prestigious organization. I am eager to contribute to the project A Framework for Unsupervised Deep Clustering. I have begun my literature review on autoencoders and various deep clustering algorithms that can be used for EEG data. Inquiries: I would like to ask where I should post the latest findings of my literature review to keep you(@zeydabadi) in the loop related to the research work. Also, @zeydabadi, it would be great if you could assign some coding challenges or guide me on how I can contribute to the organization apart from my research work. I am excited to contribute and collaborate with other developers of this esteemed organization. For More Info - Portfolio: https://adithyasrivastava01.github.io/Portfolio/ |
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Hello everyone, I'm Phani, pursuing a major in pharmaceutical sciences and a minor in computer sciences from IIT-BHU. I had previously contributed to Drupal and a few hacktoberfest organizations. I am looking to contribute to the UC_OSPO-OSRE in the fields of Python, JavaScript, technical writing, and even MERN applications. Also, learning hands-on experience with new frameworks and libraries is part of my daily routine. Let's Connect LinkedIn: https://www.linkedin.com/in/chakka-phani-simha-12454b224/ |
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Hello! Additionally, I've led my graduation project (NeuroPhone: https://github.com/NorhanAbdelhafez/NeuroPhone-RealTime-BrainMobilePhone-Interface), which was accepted into prestigious research forums, and secured funding, honed my ability to apply DSP techniques to preprocess EEG data, resulting in groundbreaking real-time BCI. My passion led me to go further and participate in various hackathons/competitions, in October 2022 me and my team won the best use of data challenge by NASA Space Apps Cairo. I recently got involved in a research project dedicated to developing a clustering algorithm for protein-protein interaction networks. All that made me drawn to the GSoC project on Unsupervised Deep Clustering. I'm excited to channel my experiences and enthusiasm into the GSoC community, contributing meaningfully to this groundbreaking project! Email: norhan.abdelhafez3@gmail.com |
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Greetings everyone I really wish to work on the Development of an Open-Source EEG Foundation Model and want to make open sources contributions here, would be great to get some help to get started! |
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Hello everyone, I am Pranav Sarda, a pre-final year student at IIPE, Vizag. I have experience in Machine Learning, Deep Learning and Reinforcement Learning. I am interested in developing framework that utilizes unsupervised deep learning techniques for data clustering. Email ID: pranav.r.sarda@gmail.com |
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Hello Everyone! Hope you all are doing well... In previous projects, such as MediChain, I have demonstrated a keen understanding of the intersection between technology and healthcare(especially medical data). Furthermore, I am involved in Research work that revolves around ANN and CV in my college, I have won many international hackathons like Girls Who code'21 @uva, StormHacks'22 @sfu 's premiere hackathon, MLH etc, with ML-based projects that underscores my ability to apply cutting-edge techniques practically. Please find more details about my work here Currently I have been focusing on DICOM file management and building my technical proficiency to navigate and process medical imaging data effectively. I am eager to contribute to the advancement of the team's research goals and project under GSOC 2024. LinkedIn: https://www.linkedin.com/in/prachi-nandi-461641198/ |
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Hello Everyone, My expertise spans across deep learning, machine learning, and Digital Signal Processing (DSP), and I have a strong foundation in Python frameworks such as PyTorch, TensorFlow, and scikit-learn. Throughout my academic journey, I've actively undertaken projects that bridge the gap between engineering and technology, particularly focusing on healthcare applications. In my graduation project, I'm applying few-shot learning techniques to tackle the challenge of matching subsequences in EMG signals. This project aims to address the limited medical data problem. Moreover, I bring experience in problem-solving competitions, having participated in events like ACM and Dell Hackathon Haktrick. While I'm relatively new to open source contributions, I've found the projects offered by your organization to be particularly intriguing. GitHub: https://github.com/MohamedNasser8 |
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Hello everyone, My name is Adeola Aderemi and I'm an Electrical Engineering graduate student. I'm excited to contribute to opensource Deep Learning projects and can't wait to get started here! |
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Hello everyone, I am Shreyas, a sophomore Engineering student majoring in Computer Science. My passion lies in Deep Learning and Data Analysis. Over the past year, I've had the privilege of being actively involved in aresearch project centered around a novel model for antispoof detection, employing Siamese networks.The joy I find in advancing our knowledge and contibuting to research is what fuels my dedication to this path. Email: Zhreyas1@gmail.com |
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Hello everyone! I'm Pandurang Mopgar, currently in my third year at MGM Kamothe as a Software Engineering student with an emphasis on AI and DL. I have experience with most of the state-of-the-art (SOTA) algorithms, which represent the cutting edge of technological advancements. I also have some experience with front-end and back-end technologies, notably React.js, Flask, and Django. My recent participation in the Smart India Hackathon and contributing to a project for the Ministry of Jal Shakti in field of AI/ML was an enriching experience that I am eager to build upon. I'm on the lookout for opportunities to apply my knowledge and experience in AI/ML/DL, and I would be grateful for any guidance or advice the community can offer, particularly to a newcomer eager to make a significant contribution . |
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Greetings! The expected outcomes, as outlined in your project details, perfectly align with my academic background and research interests. I am particularly drawn to the project of A Framework for Unsupervised Deep Clustering, specifically utilizing autoencoder networks for data clustering. I believe that this project offers a unique opportunity to address current limitations and challenges in the field of medical data analysis, with a specific focus on EEG data. I am committed to dedicating the necessary time and effort to ensure the successful completion of the project within the stipulated timeframe. I will be keep updated about every new solution. |
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Dear Sir. I am pursuing undergrad program in Computer Science and Engineering at the Manipal Institute of Technology at Manipal. I am in my second year. I wish to express my interest to contribute to your project on "Auto-detect coverage bounding boxes for brain MRI images". As a preparation for this project, I am going through a tutorial series on MRI Pre-Processing techniques, and gaining experience on necessary python tools, SimpleITK, Ants, and Antspynet. Currently I am learning through writing code on my local repository, and may upload my Notebooks which may be useful for my later work. I have come across two approaches: a template-based registration approach, and a deep learning based approach using pre-trained net, and which I am working on. I have collected a few references of landmark detection work for studying as well. I have downloaded few brain scans from the Cancer Imaging Archive (TCIA) to use. I am learning basic image processing operations on the data. These datasets are in raw format, but I can use SimpleITK to read from DICOM data as well. I am also going through the tutorials provided by the ants team. Please suggest me what I need to add to my learning to be better prepared for the work. Sincerely, |
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Hello Everyone, Thank You, |
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Hello everyone, I am Dhruvanshu Joshi, a prefinal year student at VJTI, India pursuing my bachelor's in Computer Engineering. I am interested in the project "Python Expansion of the Open Source Electrophysiological Toolbox". I have successfully build the reference project OSET locally. I currently am studying the matlab implementation of OSET and the current python implementation. From my understanding the python package currently supports peak detection in the ecg module and also supports some submodules from the generic module. The full scope of this project will be complete python translation of all the tools written in matlab along with their relevant tests. I would like to contribute to this project. Sincerely, |
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Hello Everyone, Sincerely, |
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Greetings everyone, I'm Utkarsh Singh Gehlot, currently a third-year student pursuing a Bachelor's in Computer Science and Engineering at JK Lakshmipat University, Jaipur. My academic journey has been deeply influenced by my passion for machine learning and its applications in various domains. Throughout my coursework, I've been actively exploring the intricacies of machine learning, particularly its relevance in healthcare and medical technology. Inspired by projects such as brain tumor analysis and malaria parasite detection, I've delved into the power of transfer learning to analyze medical images, aiming to contribute to advancements in diagnostics and treatment. One of my notable experiences includes a project undertaken during my time at IIIT Bangalore, where I delved into clustering algorithms. This experience has equipped me with valuable insights into unsupervised learning techniques, which I believe will be invaluable for the proposed project on unsupervised deep clustering. My proficiency extends to languages such as Python and frameworks like TensorFlow and PyTorch, where I've developed and deployed advanced models. Deep learning, in particular, has captured my interest, as I've explored architectures and techniques aimed at pushing the boundaries of artificial intelligence. I'm excited about the opportunity to be a part of the A Framework for Unsupervised Deep Clustering project. Currently, I'm deeply engaged in conducting an extensive literature review on various deep clustering algorithms specifically catered to EEG data analysis. Collaborating with the team, I aim to utilize my findings to drive forward innovative solutions within this domain |
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Hello everyone! I am Zaha, a recent Biomedical Engineering graduate who is excited to participate in this year's GSOC! I am very new to open source; however, I am very passionate about open source development and advancing biomedical informatics and will use this opportunity to learn and keep contributing to open source. I am very interested in contributing to Project [3] Python Expansion of the Open Source Electrophysiological Toolbox mentored by @rsameni. I am confident in my skills in Python and MATLAB as I have used them throughout my undergraduate coursework and in my hobby projects. I have also completed university coursework in Digital Signal Processing, Biosignal Processing, Neuroscience and Neural Networks in which I have gained experience in working with biosignals like EEG, EMG and ECG, and applying filters like notch and kalman filters to process and denoise data. An example of such project is my project for the Neuroscience course, wherein I participated in collecting and processing EEG data of subjects to determine the effect of a neuro-feedback program. I have been working with the OSET and have explored both MATLAB tools and Python tools by applying them to sample data, and I am now excited to start contributing! I am looking forward to working with you all and utilising my skills in Python, MATLAB, biomedical signal processing and unit testing to contribute to OSET's codebase for its Python expansion. Email: zahafatimazf@gmail.com |
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Hey Everyone, I am Prateek Pal, a final-year student at IET Lucknow, deeply immersed in the fascinating realm of AI for several years now. Along my journey, I've had the privilege to collaborate with a diverse array of startups such as ResoluteAI, Infiheal, Viga Entertainment Technologies, and Pibit.ai, to name a few. Currently, I'm honing my skills as an AI Engineer Intern at Lambdatest where I am working on a research project to build a foundational model to change the face of UI testing with enabling it to perform tests using natural language commands. My passion for problem-solving extends beyond conventional boundaries, as evidenced by my active participation and notable achievements in various hackathons. These include securing top positions in events like the LLM Bankathon by Axis Bank, UST Decode by UST, SIH 22, UIA Hackathon jointly organized by the Indian and African governments, and the 30Hacks by Hitachi, among others. Additionally, I've been fortunate to receive prestigious scholarships such as the AWS Advanced AI Scholarship and the Fellowship.ai Fellowship, further fueling my commitment to advancing in this dynamic field. |
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Hi Y'all, I'm Hanliang Xu, a rising senior at Vanderbilt University, US. My email is: hanliang.xu@vanderbilt.edu. I'm interested in Project [5] A graphical user interface of Foundational Model Toolbox for Image Segmentation. My passions exactly match the requirements for the project, lying at the intersection of deep learning / foundation models, image segmentation / medical image processing, and software development / interface design. Specifically, here are my experience which demonstrate my skills: Deep learning & foundation models - studied in the grad-level class "Deep Learning;" delved deeper with the FAIR's self-supervised learning cookbook; implemented and evaluated foundation models for medical image segmentation in my current research with Dr. Bennett Landman. Image segmentation & medical image processing - reviewed both traditional and deep learning image segmentation methods in the PhD-level class "Medical Image Segmentation"; implemented methods from gradient vector flow and active contours to U-Net / nnU-Net and swin transformer in assignments; published a paper on SPIE Medical Imaging as the first author about harmonizing connectivity matrices of diffusion MRI. Software development & interface design - mastered software design principles, tools, and architectures in the grad-level class "Intermediate Software Design" and programming skills in "Data Structures," "Algorithms," etc; led a group of seven to develop a user portal and an admin portal for the non-profit organization Book'em with Figma and the MERN stack. These experiences prepare me well for contributing to project 5. Feel free to reach out to me via email about project or research ideas! Really excited to be part of Emory BMI community. |
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Hello everyone, my name is Philippe Bouchet, I have recently graduated from EPITA in August 2023, with a Master's degree in Computer Science, with a specialization in deep learning for medical imaging. I am interested in project [6], “Auto-detect coverage bounding boxes for brain MRI images”. During my time as a student at EPITA, I had the opportunity to publish a paper in MICCAI for glioblastoma segmentation from mpMRI (T1, T2, T1CE, FLAIR) volumes as a first author. As such I believe that these experiences prove that I am qualified and suited for contributing to project 6. Feel free to reach out to me about any project or ideas! I am open to discussion and would love to exchange. My email is philippebouchet13@gmail.com |
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Hello everyone, I'm Utkarsh Raj, a 3rd-year undergraduate student pursuing an Integrated Dual Degree (B.Tech+M.Tech) in School Biomedical Engineering at the Indian Institute of Technology (IIT-BHU), India. I am highly passionate about computational neuroscience and medical image processing. I'm interested in the project [6] "Auto-detect coverage bounding boxes for brain MRI images." I have prior experience working with MRI and FMRI image processing, and segmentation. In the second year of my college, I completed a research internship at UNISR(Vita-Salute San Raffaele University), Milan, Italy. in which I worked as on “Development and optimization of machine learning algorithms to classify patients’ status based on radiomics MRI features". During this period, I gained massive hands-on experience working remotely with big data sets and utilized a range of machine learning algorithms, including developing predictive models. I have also worked on "Diagnostic classification of autism using fMRI and machine learning" at my department, during which I developed a working model for predicting ASD with the help of image processing and feature extraction to identify significant brain activation patterns. In my 3rd year I have worked on "Emotion detection" with the help of Eda, phasic, and non-phasic signals. Working with these projects, I have gained a complete practice on how to build a complete architecture of a project and build a proper workflow pipeline and have gained experience on various machine learning and deep learning techniques. Working with this project I have worked with different combinations of deep learning methods and implemented multiple architectures to achieve a good accuracy for classification of emotions. Currently, I am involved in a research intern project at Charité – Universitätsmedizin ,Berlin and working on a project "Preclinical lesion network mapping" in which I will be involved in practical basics of magnetic resonance imaging (MRI) in preclinical animal models (mouse and rat) of neurological disease.perform diffusion MRI and resting state functional MRI and process these data and to collect and harmonize an already existing internal database of diffusion and resting state MRI data and to transfer a technique called “lesion network mapping (LNM)” from human to rodents. I am confident that my expertise in this area will bring significant benefits, and it fits well with the project criteria. Collaborating under the mentorship of Puneet Sharma and Tony Pan presents an ideal chance to enhance my research skills and deepen my understanding of this scientific field. My email is utkarsh.raj.bme21@itbhu.ac.in |
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Hi everyone, My name is Nina Gruteser, and I am currently studying computer science at Purdue University. I have a passion for machine learning and its application to healthcare. I have previous experience working with deep learning models, such as detecting seizures in EEG data and training tumor segmentation models for 3D PET scans. I am interested in projects [1] Development of an Open-Source EEG Foundation Model and [6] Auto-detect coverage bounding boxes for brain MRI images. For the projects, I wanted to ask how big the publicly available EEG and brain MRI datasets will be. I look forward to sharing my proposals! My email is ngrutese@purdue.edu |
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Hello everyone, Nice to meet you all! I have experience in EEG signal analysis and already done a project related to it . And also have prior experience in Brain Tumor MRI classification using PyTorch: So as my knowledge in 1st project EEG signal we need to understand signal anomalies first need a way to is it an actual anomaly or not then we can use LSTM or something related to RNN to identify signals. In Auto-detect coverage bounding boxes for brain MRI images there is multioutput models bounding box is regression and segmentation is classification. a classic deep neural network can use to identify and also some autoencoder techniques to solve the problem. As I mentioned I'm a undergraduate and I don't have lectures or exams in upcoming month but I have to work on final phase parallel project along with this an ERP system.so I need some flexibility there to visit my supervisor and prepare the presentation.so I dedicate work up to 24-21 hours per week. As a drag I'm not skilled with PyTorch compared to TensorFlow. I will expect some mentoring to adapt to Torch in serious problems. Skills are: If you think I'm fit to your work I will eager to join with you. Contact me via anudaattanayake@gmail.com. GitHub: https://github.com/ANEASER. Thank you, |
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Hello everyone, It's a pleasure to meet you all! I'm Manan Shah, a Research Fellow at IIT Gandhinagar with a strong background in computational sciences, including a minor in Computational Neuroscience, and a passion for pushing the boundaries of innovation. I'm excited to express my interest in contributing to the "Development of an Open-Source EEG Foundation Model" or "Auto-detect coverage bounding boxes for brain MRI images" project. My expertise lies in leveraging advanced techniques like deep learning, signal processing, and computer vision to tackle complex challenges, particularly in the healthcare and biomedical domains. Through my academic and professional pursuits, I have gained extensive experience in analyzing intricate datasets, developing cutting-edge algorithms, and implementing robust solutions. Notably, my major project "Deep Spike Neural Networks for BOLD Signal Classification" involved developing and fine-tuning novel deep learning algorithms using fMRI data and image classification techniques, showcasing my proficiency in working with complex biological data and leveraging advanced analytical methods. I developed and fine-tuned novel deep learning algorithms using spike neural networks and fMRI data, achieving good accuracy in multi-class image classification of fMRI data in order to predict MCI and Alzheimer's and other Neuroses in the patients. Additionally, in connection to another project idea we worked on involved predicting effective learning in students through Neural Alignment in subjects , under the supervision of my Thesis Supervisor, focused on employing preprocessing techniques, brain atlases (Harvard-Oxford 2001 atlas), FastICA, dictionary learning algorithms, Group ICA, and hyper-alignment algorithms to explore neural alignment and inter-subject correlations in learning processes. In this project, I used an open-source data medium for fMRI images of 20 students and 5 experts (alumni of a computer science courses). I employed effective preprocessing techniques on the fMRI images and utilized whole brain atlases to map neural alignment in students during every session in the MRI scanner. I mapped the atlases using FastICA and dictionary learning algorithms to visualize the neural alignment of each student. Furthermore, I employed Group ICA and hyper-alignment algorithms to accomplish inter-subject correlation, predicting if past knowledge affects the learning of new skills or if different learning patterns are causal to effective skill learning. The project's findings discovered a significant correlation between past knowledge and the learning of new skills, highlighting the role of prior experience in skill acquisition. Additionally, I identified distinct learning patterns among individuals that are causally linked to effective skill learning, providing valuable insights for personalized learning strategies. Ultimately, I validated the hypothesis of individual variability in learning patterns, emphasizing the importance of personalized approaches in education and skill development. Furthermore, my experience as a Patent Researcher at EduNeuro allowed me to spearhead the development of web-based document analysis platforms, leveraging NLP algorithms to identify and prioritize gaps in data with an impressive accuracy rate of over 95%. This project demonstrated my ability to design and implement complex pipelines and deliver high-quality solutions. Regarding the EEG Foundation Model project, I understand the importance of accurately identifying signal anomalies and leveraging techniques like LSTM or RNNs for signal analysis. Similarly, for the brain MRI image analysis project, I am well-versed in multi-output models, bounding box regression, and segmentation classification using deep neural networks and autoencoder techniques. With a strong foundation in programming languages like Python, frameworks like PyTorch and TensorFlow, and skills in digital signal processing, anomaly detection, and custom model development, I am confident in my ability to contribute meaningfully to these projects. While my experience with PyTorch may be relatively limited compared to TensorFlow, I am a quick learner and welcome the opportunity to receive mentorship and guidance from experienced professionals. I am committed to dedicating up to 25-30 hours per week to these projects, balancing my contributions with my academic responsibilities. Please feel free to reach out to me at mananshah@alumni.iitgn.ac.in. Thank you for your consideration, and I look forward to the opportunity to collaborate and contribute to these exciting projects. Best regards, |
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Hello Everyone, My name is Ahmed Yoshay, I am currently a sophomore at FAST NUCES, Karachi, Pakistan, doing Bachelors of Science in Computer Science. I am an enthusiastic computer science student with a knack for Python, C, and C++! From developing diverse projects to crunching numbers as a skilled bookkeeper in Excel, I bring a dynamic skill set to the table. Eager to propel my journey into the realms of AI/ML, where I'm poised to leverage my sharp analytical abilities and passion for innovation. Beyond tech prowess, my stellar interpersonal and leadership skills ensure seamless collaboration and drive projects to success. Let's innovate and lead together. Please feel free to reach me out at: |
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Hello Everyone, I am Sameena Mujawar a grad student of Data Science from the Maryville university of Saint Louis. This is my career transition from Medical to the Data Science field. I have knowledge of Python, R , SAS programming languages. SQL database language. Machine Learning and Deep learning algorithms such as Linear, Logistic regression, Decision Tree, Random Forest, SVM, NLP, CNN models. Currently I am working on the Harmful Brain activity classification Project by Harvard Medical School. Looking forward to learn more from you guys by contributing in the project. I really appreciate your knowledge and experience. Feel free to reach out to me : Thank you for giving your time and for consideration. Best Regards, |
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Hello, I'm Harshita, a passionate problem solver with a knack for innovation. My expertise lies in the MERN stack, where I've honed my skills through practical experience and contributions to open-source projects. I have also worked on Generative Adversarial Networks (GANs), exploring the cutting edge of AI technology. I'm eager to apply my knowledge to new MERN projects, leveraging my experience in UI/UX design to create seamless and engaging user experiences INTERESTED IN: Python Expansion of the Open Source Electrophysiological Toolbox EMAIL: hk264603@gmail.com |
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Hi, I’m Kavindu from Sri Lanka. I’m an undergraduate software engineering student with a strong interest in Python and web development. I’m passionate about building innovative solutions, exploring new technologies, and contributing to open-source projects. email : karunasinghesampath38@gmail.com |
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Hi Kavindu,
Thanks for reaching out.
My research is around algorithm development for biomedical data analysis.
We do a lot of coding but software is not our main focus/goal.
What is your interest/experience with machine learning?
Mahmoud
…On Sun, Oct 13, 2024 at 4:39 PM Kavindu Udara ***@***.***> wrote:
Hi, I’m Kavindu from Sri Lanka. I’m an undergraduate software engineering
student with a strong interest in Python and web development. I’m
passionate about building innovative solutions, exploring new technologies,
and contributing to open-source projects.
email : ***@***.***
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Hi Mahmoud, I am interested in working on machine learning and algorithms. I may have contacted your previously too. I am currently working on research papers related to machine learning and also I am fluent with datastructures and algorithms. Is an opprtunity still available? Thank You, |
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Hi Mahmoud, I’m a fourth-year Data Science student at UBC in Canada and was wondering if you might still be open to accepting new students. If so, I’d be glad to send along my resume and any additional information that might be helpful via email. Thank you for your time and consideration! |
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Hi @zeydabadi I am Mohan from India. I am currently in my junior year. I have keen interest towards deep learning and GenAI. I have worked as machine learning engineer at a Startup SellerSetu. |
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and others
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Greetings Everyone,
We utilize GitHub Discussions as a means of communication.
While the participating organizations for GSoC 2024 have not been officially announced, it would be beneficial for us to initiate introductions and familiarize ourselves with one another. You are encouraged to respond to this discussion thread, providing information about yourself and the projects you are involved with.
A few comments to get you started:
Please go through the project ideas list and find the idea(s) that you are interested in.
Please ask your questions in the relevant channels for existing projects. Questions and discussions on projects are discussed in this repository:
https://github.com/NISYSLAB/Emory-BMI-GSoC/discussions
Please be specific when you ask a question:
"Hi, I am X from Y. I need help to start applying for project Z" is unlikely to receive any useful reply. Because the project ideas are intentionally left brief to allow the interpretations from the contributors in their proposals. If you have specific questions (rather than "help me get started"), please feel free to ask at any time!
Happy coding! Looking forward to working with you soon.
Interested students: Please add your email to your post.
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