{"schema":"BUIDL","d":{"id":22379,"members":[],"pictures":["https://cdn.dorahacks.io/static/files/194c724b4181db5bbc1aa574014993fe.png"],"roundProjects":[],"hackathonProjects":[{"id":24657,"hackathon":{"id":819,"tabSet":[{"id":1335,"name":"Rules","slug":"rules","description":"Students who have registered for HackRU and checked-in to the event are eligible to participate. Those attending must abide by the MLH code of conduct. Code of conduct: HackRU is a community hackathon intended for collaboration and learning in the student community. We value the participation of each member of the student community and want all attendees to have an enjoyable experience. All participants are expected to show respect to other fellow participants throughout the hackathon. All attendees and speakers at HackRU are required to conform to the code of conduct. The organizing team and rutgers university reserve the right to enforce, revise, and append these rules. We believe that every individual has the right to hack in a safe and amicable environment. All HackRU participants must comply to the following: be respectful of other attendees in speech and of their boundaries, withhold from demeaning, discriminating or harassing other participants through behavior- including but not limited to offensive comments related to gender, age, sexual orientation, disability, physical appearance, body size, race, religion, sexual images in public spaces, intentional intimidation, stalking, following, harassing photography or recording, sustained disruption of talks or other events, inappropriate physical contact, and unwanted sexual attention. If a participant engages in harassing behavior, HackRU may take any action that deems appropriate, including warning the offender or even expulsion from the event. Reporting procedures: if you feel uncomfortable or think there may be a possible violation of the code of conduct, please report it immediately. All individuals who report remain anonymous. The HackRU organizers will work to resolve all incidents alongside MLH representatives."},{"id":1378,"name":"Submission Guide","slug":"submission-guide","description":"# Tutorial Video\n\n![YouTube](https://youtu.be/yWhQPzxptg0)\n\n# **Getting Started [3-5 MIN]**\n\n**1.** **Submit your BUIDL via [DoraHacks.io](https://dorahacks.io/). You need an account with DoraHacks before you can submit.**\n\nUse the **Log in** button in the upper right corner of the page to access the sign-up options.\n\n

\n\nYou can create your account with either your **GitHub account, Google account, crypto wallet** or **email address**. We recommend connecting your account to GitHub to share your projects with a wider audience.\n\n*If asked for a verification code via email, the email may take a few minutes to arrive. The code expires 10 minutes after you click “**send code**”.\n\n**2.** **Before the submission deadline, make sure you have added your Github link to the project. You can submit the project first, and continue editing until the deadline.**\n\nClick “**Submit BUIDL**”.\n\n

\n\n\n> **→ Already have a BUIDL on DoraHacks?**\n> \n\n1. Click “**Use existing BUIDL**” and select your BUIDL project.\n2. Choose the track you want to enter. \n3. Answer the questions set by the organizer in the input field if applicable.\n\n

\n\n\n> **→ Submitting a new BUIDL?**\n> \n> Click **“Create new BUIDL”** and fill out the form with your project details.\n\n

\n\nBe sure to include **URLs (with http/https://)** for your demo, demo link, and social media.\n\n

\n\n

\n\nOnce you’ve completed the new BUIDL setup, select the relevant track, and click **“Submit for review”**.\n\n

\n\nAfter submitting successfully, you'll see this notification.\n\n

\n\n# **Manage BUIDL submission**\n\nAfter submitting your application, the \"Submit\" button will update to \"Manage Submission\". Click the button to manage your BUIDL's Track/Bounty submission.\n\n

\n\n# **Project Approval**\n\nAfter submission, your project needs to be approved by the Hackathon Organizer before it becomes publicly visible in the Hackathon [BUIDLs gallery](https://dorahacks.io/hackathon/822/buidl).\n\n

\n\n# **Getting Support**\n\nIf you have any questions for the hackathon organizers, feel free to contact them via their dedicated Telegram, Discord, or Slack communication channel. You can also click the \"**Message**\" button next to the organizer's logo to DM them on DoraHacks.\n\n# Need to Update Your BUIDL?\n\nTo make changes to your project, click [Avatar] -> [Profile] to access your Account Center. Then, click the \"**Edit**\" button on the top right of your BUIDL to update your BUIDL information.\n\n

\n\n

"}],"skills":null,"applied":false,"isCurrentHackerRegistered":false,"buidlsCount":119,"applicationsCount":125,"organization":{"id":3104,"name":"HackRU","logo":"https://cdn.dorahacks.io/static/files/19474f873362b11e6f2b67b4414a68b5.png"},"description":"# Introduction \nHackRU is a 24-hour hackathon at Rutgers University. We welcome hundreds of students to join us in building awesome software and hardware projects. \n\nYou must submit your hack to be considered for one track (Social Good, Education, Maverick) only. Submitting multiple times to more than one track will lead to an automatic disqualification. More information about tracks can be found in the Tracks section.\n\nEach team is allowed to submit their project for as many superlative (bounty) prizes as their hack applies to.\n\n# Requirements\n\n**Please read all of the following information carefully.**\n- In order to participate in HackRU, you must be at least 18 years old.\n- In order to be judged, one person on your team **only** must submit a BUIDL (project) on DoraHacks. Before you do, your whole team must be registered HackRU participants.\n- Your submission must include a link to the shared repository you used, and include all names of your team members for your submission. **For the Telegram box, please put NA.**\n- The max team size is 4 people. Each team member must have a DoraHacks account and be listed as a contributor on the project submission.\n- All projects **must** be submitted in DoraHacks by **10:00 am on Sunday, February 2nd.** Submitting on DoraHacks does not mean hacking is over! You can still hack from the beginning of the hackathon, 12:00 pm on Saturday, February 1st until 12:00 pm on Sunday, February 2nd, but you **must** make sure to push all updated code to your submitted repository prior to judging. \n- You are not allowed to submit a project that has been built before the start of hacking or a project built at/submitted for another hackathon.\n- Any hack found to have been made before the start of hacking or for another hackathon will lead to automatic disqualification.\n- When submitting your project, make sure to submit all project info and answer the questions on the submission page.\n- You must submit your hack for one track only (Social Good, Education, Maverick or Transit). \n- Each team is allowed to submit their project for as many relevant superlatives as their hack applies to. Please only choose the superlatives that apply to your hack.\n- Each team is only allowed to submit a single project.\n- All members of your team **must** be present for judging beginning at 12:30 PM EST on Sunday, February 2nd.\n- All prize winners **must** be present to sign a prize form if your team wins a prize. No exceptions will be made.\n- *Any hack that fails to meet any of the above requirements or the eligibility requirements will be disqualified and not be considered for any prize.*\n\nBe sure to specify the track you want to be considered for otherwise you will not be considered for a track prize.\n\n# Tracks\n**Social Good** - Hacks that drive positive change and uplift communities. \n**Education** - Hacks that foster education. \n**Maverick** - Any other hack! The opportunities are limitless. \n\n\n# Track Prizes\n\n**Social Good Track:** \nWinner: Ninja Ice Cream Maker \nRunner Up: LARQ Bottle PureVis 17 oz \n\n**Education Track:** \nWinner: Kindle Paperwhite \nRunner Up: Corsair K70 Pro Keyboard \n\n**Maverick Track:** \nWinner: Therabody SmartGoggles \nRunner Up: Cosori Air Fryer \n\n# Judging criteria\n\n**Functionality and Execution** \nDoes the Hack work as intended? \n**Creativity and Innovation** \nIs the idea unique? Has significant thought been put into the idea? \n**Technical Difficulty** \nWas the project technically challenging to execute? Does it require a high level of understanding/skill? \n\n# Contact us \n\nPlease contact info@hackru.org or message in discord with any further queries/question","onboardingCompleted":false,"registerFormUrl":null,"preRegisterTime":0,"publicContactHackerHandle":"hackru","hackersCount":244,"winnerAnnounced":true,"teamCount":0,"title":"HackRU Spring 2025","uname":"hackru-s25","imageUrl":"https://cdn.dorahacks.io/static/files/19475b45f3774298e3720fa4fe5bb1e7.png","originUrl":null,"startTime":1738429200,"endTime":1738515660,"timezone":"300","city":null,"visible":true,"approvalStatus":6,"state":0,"voteUrl":null,"voteMechanism":null,"bonusPrice":3574,"bonusMechanism":null,"followersCount":0,"ecosystem":"MongoDB,Terraform,AI","applyGuide":null,"weight":0,"participationForm":"IRL","field":"Student","email":"info@hackru.org","contacts":"Email,info@hackru.org","externalContacts":null,"telegram":null,"discord":null,"whatsapp":null,"wechat":null,"prizeFundingEscrowed":0,"token":"USD","prizeSafeForm":0,"prizeSafeNetwork":null,"prizeSafeOwner":null,"prizeSafeWallet":null,"prizeSafePublishDate":null,"hasOnboarding":false,"isPublicTrackJudging":false,"isEndedTrackJudging":false,"question":"[{\"id\":1,\"text\":\"Shared Repository (GitHub) Link. ONLY PUT YOU'RE LINK IN THIS BOX. Do not put it in the other GitHub Link box:\",\"required\":true},{\"id\":2,\"text\":\"Please list ALL team members' first and last name separated by a comma:\",\"required\":true},{\"id\":3,\"text\":\"Please list ALL team members' emails in the same order that you listed your names, separated by a comma: \",\"required\":true},{\"id\":4,\"text\":\"Please list ALL team members' schools in the same order that you listed your names, separated by a comma: \",\"required\":true},{\"id\":5,\"text\":\"Technologies used:\",\"required\":true},{\"id\":6,\"text\":\"What school do you attend? If you are no longer in school, what university did you most recently attend?\",\"required\":true},{\"id\":7,\"text\":\"Please include AT LEAST ONE phone number of a team member as a point of contact (for prizes, updates, etc.)\",\"required\":true},{\"id\":9,\"text\":\"Which of the following GenAI tools did you use this weekend? (OpenAI, Anthropic, Hugging Face, Llama, IBM Watson, Gemini)\",\"required\":true},{\"id\":10,\"text\":\"How did you use GenAI tools this weekend?\",\"required\":true},{\"id\":11,\"text\":\"If you used a GenAI Tool, why did you select the tools you did?\",\"required\":true}]","countryId":230,"cityId":1840081697,"venueName":"Rutgers University Busch Student Center","venueAddress":"604 Bartholomew Rd, Piscataway, NJ 08854","category":3,"isEnableBounty":true,"isBountyRequired":false,"isEndedBountyJudging":false,"bountiesLimitForBuidl":10,"isPublicBountyJudging":false,"isMultiTracksAllowed":false,"tracksLimitForBuidl":0,"showIdeaTab":false,"showQuestionTab":false,"showTeamTab":false,"bonusDescription":[],"askHackers":[],"isEnabledQuestions":true,"isEnabledAskHackers":false,"isBuidlsPrivate":false,"trackJudgingMaxScore":100,"bountyJudgingMaxScore":100,"isExtended":false,"oldEndTime":null,"status":2},"status":4,"bounty":null,"track":null,"table":"0","trackObj":{"id":2093,"name":"Social Good","judgingCriteria":"Eligible projects for this track must focus on bettering the community in some way. A winner and a runner-up will be chosen.","weight":3},"bountyObjs":[{"id":977,"name":"Best UI/UX Hack","token":"USD","bonus":50,"link":"","description":"Prize: JellyCat Amuseables Chocolate Milkshake plushie. For hacks with the most aesthetically pleasing and intuitive UI/UX, each team member will receive a JellyCat Amuseables Chocolate Milkshake plushie."},{"id":996,"name":"Best Use of AI powered by Reach Capital","token":"N/A","bonus":0,"link":"","description":"Prize: Logitech Webcam & Meeting with Co-Founding Partner at Reach Capital\n\nAI has upended what we can accomplish with technology. [Reach Capital](https://mlh.link/reach-capital) invests in the next generation of founders and technical talent, and they want you to use AI to transform the future of learning, health, and work. Build a project that impacts one (or all!) of these areas for a chance to win a Logitech webcam for each member of your team and the exclusive opportunity to discuss your creation with Reach Capital’s team of expert investors."},{"id":998,"name":"Best Use of Gen AI","token":"N/A","bonus":0,"link":"","description":"Prize: Mechanical Keyboard & Fitbit\n\nGenerative AI is rapidly changing the landscape of software development. This category challenges you to build novel applications that leverage the power of Generative AI APIs. Think outside the box and integrate cutting-edge AI models to create innovative solutions with real-world impact.\n\nTo participate, utilize publicly available Generative AI APIs (like those from OpenAI, Anthropic, Hugging Face, Llama, IBM Watson, or Google Gemini) to develop a unique and functional application. This could include:\nAI-powered creative tools: Design an app that allows users to generate unique marketing copy, translate languages in real-time, or create personalized learning experiences.\nIntelligent assistants and automation: Build a chatbot that can provide insightful customer support, or a system that automates complex tasks using natural language processing.\nNext-generation content creation platforms: Develop a platform that empowers users to generate high-quality images, write different kinds of creative text formats, or compose original music with AI assistance.\nThis is your chance to get hands on with cutting edge tech, put your skills on display, and of course, win some awesome prizes!"}]}],"chain":[],"chainList":[],"appliedGrant":false,"acceptRewards":false,"owner":199790,"ownerInfo":{"nickname":"OX-S","username":"FinnKliewer","avatar":"https://cdn.dorahacks.io/static/files/194c70bc9b6cb602e5bd197476687af8.png"},"visible":true,"deleted":false,"continuousSponsoring":false,"pageView":0,"sponsoredCount":0,"starCount":0,"sponsoredAmount":"0.00","sponsoredPersons":0,"followers":0,"voteCount":0,"projectMembers":[],"bnbRound":null,"doraGrantDaoTags":[],"techTrees":[3],"infrastructureTags":[],"otherInfrastructures":[],"lastEditor":{"id":199790,"username":"FinnKliewer","date":1738726012000},"upvoted":false,"followed":false,"upvoters":{"count":0,"list":[]},"kycStatus":0,"ideas":[],"name":"EarlyTrace.ai","techniqueField":"","source":"-","vision":"Early dementia detection through the power of AI","projectDescription":"Inspired by a 2023 Paper, **Using personal writings to detect dementia: A text mining approach [1]**, we trained an AI model to detect dementia in written texts quickly and efficiently. To do this, we first scrapped blog posts from people with and without dementia. From this, we got about 1.4 million tokens worth of training data. We then generated sentence embeddings using the BGE-large-en-v1.5 transformer model since it can run efficiently CPU only and ranks fairly high on the HuggingFace MTEB leaderboard, and the embedding dimensions of 1024 are large enough to capture the minor subtleties and nuances our texts. Sentence embeddings are a way to represent a text as a single vector. To classify the texts, we used gradient boosting with the XGBoost library to classify each text as either \"likely dementia\" or \"not likely dementia.\" Out of our roughly 3000 training points, we set aside 20% for testing and validation. These training points were not used in the training of our model. We performed 5-fold cross-validation on our model, resulting in **an F1 score of 0.95 based on a total support of 606.**\n\n\n\n\nWe ran out of time before the 10a deadline to upload our demo video, so here is the YouTube link to our video demo:\nhttps://youtu.be/nj9fFstPfls\n\n\n\n\n1) Asllani B, Mullen DM. 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To do this, we first scrapped blog posts from people with and without dementia. From this, we got about 1.4 million tokens worth of training data. We then generated sentence embeddings using the BGE-large-en-v1.5 transformer model since it can run efficiently CPU only and ranks fairly high on the HuggingFace MTEB leaderboard, and the embedding dimensions of 1024 are large enough to capture the minor subtleties and nuances our texts. Sentence embeddings are a way to represent a text as a single vector. To classify the texts, we used gradient boosting with the XGBoost library to classify each text as either \"likely dementia\" or \"not likely dementia.\" Out of our roughly 3000 training points, we set aside 20% for testing and validation. These training points were not used in the training of our model. 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