Now that we have all recovered from the sleep deprivation caused by the hackathon that took place last weekend, I would like to reflect on the amazing opportunity that Deltahacks provided for both the hackers and the executives. I had the privilege of meeting one of the coolest speakers Tanmay Bakshi , who made everyone interested in machine learning. I hope to have future collaborations with him on other projects. I would like to extend my gratitude to Almen Ng for her dedication to Deltahacks, even though it required her to go through sleepless nights to make this amazing event happen. Lastly, I would like to thank the rest of Deltahacks team, as this event would not have been possible without their contributions. #hackathon #deltahacks
Arian Ahmadinejad’s Post
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It was a pleasure working alongside you guys. As a first time experience travelling and hacking in US, I’m definitely coming back for more :)
I'm excited to share that I recently participated in my first hackathon at Hacklytics 2024, hosted by Data Science @ GT. Alongside my team members, Arian Ahmadinejad, Ayush Shukla Arora, and Annika Logarta, we spent 36 hours working to implement our idea for an application used to predict the likelihood of relapse for individuals admitted to drug rehabilitation facilities. The idea here is that we wanted to evaluate and analyze the factors that can theoretically contribute to a patient’s potential relapse pertaining to substance abuse. By analyzing existing SAMHSA data aggregated from 1992 to 2021, the team opted to create a predictive model that can accurately identify the most significant correlative factors for relapse. This, in conjunction with a variety of Tableau visualizations, provides valuable insight into America’s current substance abuse crisis and potential future actions to mitigate its consequences. The team used Python and Tableau alongside machine learning library tools to produce data-driven insights on patterns among patients admitted to drug rehabilitation institutions across the United States. Python libraries including Pandas, NumPy, and Sci-Kit learn were leveraged to optimize our dataset for the application of machine learning models such as random forests to predict the possibility of readmission, given a set of parameters for individual patients. Additionally, the team implemented a fully interactable dashboard using Gradio and HTML/CSS linked with Tableau to include geo visualizations of national health data to tell the story of the impact of psychoactive substances on institutional healthcare decisions and American society as a whole. Although it was my first hackathon, I am happy to announce that we did not leave empty-handed, as our team won Snowball iCE Logitech microphones for our efforts as well as free lifetime access to our website domain. I would like to express my thanks to my team members, the event coordinators, and the sponsors, including MLH, Intel, Traversal AI, Assurant, NSA, among others.
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I’m happy to share that I’m starting a new position as Machine Learning Engineering Intern at Bell!
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I’m happy to share that I’m starting a new position as Teaching Assistant at McMaster University!
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I’m happy to share that I’m starting a new position as Technical Manager at McMaster Computer Science Society!
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Software Quality Engineer @ Red Hat | Software Engineering & Management Graduate @ McMaster University | Former Co-Director of DeltaHacks
1yYou all are the best 🥰 The hackathon wouldn't have gone so smoothly if it weren't for your hard work along with the rest of tech team!! You all had to pull a hackathon before the hackathon and I am extremely grateful for you guys!