Visual AI Hackathon - Northeastern University
Sept 20, 2024 at 10 AM to 5 PM Eastern
Register for the Hackathon
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Visual AI Hackathon - Northeastern University
Join us for an exciting hackathon at Northeastern University, where ML enthusiasts and college students alike will come together to tackle real-world challenges in the field. With cash prizes, intimate space, refreshments, and swag, participants can expect an immersive experience filled with learning, networking, and the opportunity to showcase their skills. Whether you’re a beginner eager to explore foundational concepts or an intermediate looking to add flair to your projects, this event offers something for everyone.
Attend workshops during the hackathon to learn some of the best practices in Computer Vision and ML. Judges, including industry experts, will evaluate submissions across various levels, with prizes awarded to the most innovative solutions. Don’t miss out on this chance to collaborate, learn, and contribute to the vibrant AI community.
Come build projects, engage with fellow enthusiasts, and be part of the future of machine learning!
What you can expect
🚀 Tech Talks: Deep dive tech talks on Computer Vision and Data-Centric AI.
🔧 Hands-on Workshops: Learn how to build AI applications through code examples
🏅 Engaging Challenges: Tackle real-world problems with AI solutions.
🤝 Networking Opportunities: Connect with fellow developers, builders, and industry experts.
🎁 Exciting Prizes: Demo your projects and compete for cash prizes.
Join one of our three tracks
🧭 Level 0 – Beginner: For those who are just getting started on their ML Journey!
🛞 Level 1: – Intermediate: For those familiar with some Data Science or ML practices, but looking to level up!
🔥 Level 2 – Expert: For those who are the frontier of ML or Computer Vision today looking to make a positive impact!
When and Where
10:00 AM – 5:00 PM Eastern
Northeastern University
Raytheon Amphitheater – 240 Egan Building
360 Huntington Avenue, Boston, MA
Snacks and refreshments will be available!
Hosts / Instructors
Prof Sarah Ostadabbas
Professor / Northeastern University
Professor Ostadabbas is an associate professor in the Electrical and Computer Engineering Department at Northeastern University (NU) in Boston, Massachusetts, USA. She joined NU in 2016 after completing her post-doctoral research at Georgia Tech, following the achievement of her PhD at the University of Texas at Dallas in 2014. At NU, Professor Ostadabbas holds the roles of Director at the Augmented Cognition Laboratory (ACLab), and Director of Women in Engineering (WIE). Her research focuses on the convergence of computer vision and machine learning, particularly emphasizing representation learning in visual perception problems. In her applied research, she has significantly contributed to the understanding, detection, and prediction of human and animal behaviors through the modeling of visual motion, considering various biomechanical factors. Professor Ostadabbas also extends her work to the Small Data Domain, including applications in medical and military fields, where data collection and labeling are costly and protected by strict privacy laws.
Professor Ostadabbas has co-authored over 130 peer-reviewed journal and conference articles and received research awards from prestigious institutions such as the National Science Foundation (NSF), Department of Defense (DoD), Sony, Mathworks, Amazon AWS, Verizon, Oracle, Biogen, and NVIDIA. She has been honored with the NSF CAREER Award (2022), Sony Faculty Innovation Award (2023), was the runner-up for the Oracle Excellence Award (2023), and One of the 120+ Women Spearheading Advances in Visual Tech and AI Recognized by LDV Capital (2024).
Dan Gural
Machine Learning Engineer and Developer Evangelist
Daniel Gural is a seasoned Machine Learning Evangelist with a strong passion for empowering Data Scientists and ML Engineers to unlock the full potential of their data. Currently serving as a valuable member of Voxel51, he takes a leading role in efforts to bridge the gap between practitioners and the necessary tools, enabling them to achieve exceptional outcomes. Daniel’s extensive experience in teaching and developing within the ML field has fueled his commitment to democratizing high-quality AI workflows for a wider audience.
Beyond his professional role at Voxel51, Daniel actively contributes to the growth and development of young entrepreneurs and STEM students at the high school and college levels, serving as a mentor. His dedication to fostering the next generation of innovators showcases his belief in the importance of sharing knowledge and inspiring others to embrace the world of AI.
Jacob Marks, PhD
Machine Learning Engineer and Researcher
Jacob Marks is a Machine Learning Engineer and Developer Evangelist at Voxel51, where he helps bring transparency and clarity to the world’s data. He is passionate about education, and brings years of experience teaching, TAing, and tutoring to this workshop. Prior to joining Voxel51, Jacob founded a startup to help emerging musicians connect and share creative content with fans. Before that, he worked at Google X, Samsung Research, and Wolfram Research. In a past life, Jacob was a theoretical physicist. In 2022, he completed his Ph.D. at Stanford, where he investigated quantum phases of matter.
Allen Lee
Machine Learning Engineer
Allen Lee is a Customer Success Machine Learning Engineer at Voxel51, where he is helping build the world’s leading visual AI platform. He has worked in computing for many years and is passionate about helping teams to collaboratively build practical, effective AI/ML solutions. Prior to joining Voxel51 he spent over ten years as co-founder of a thriving scientific software consultancy. Allen lives in the lovely Garden State of New Jersey with his family.
Judges
Prof Ehsan Elhamifar
Professor / Northeastern University
Ehsan Elhamifar is an Associate Professor in the Khoury College of Computer Sciences, the director of the Mathematical Data Science (MCADS) Lab and the Director of MS in AI at Northeastern University. He has broad research interests in computer vision and machine learning. The overarching goal of his research is to develop computer vision systems that learn from and make inferences about data analogous to humans. He is a recipient of the DARPA Young Faculty Award. Prior to Northeastern, he was a postdoctoral scholar in the EECS department at UC Berkeley. He obtained his PhD in ECE at the Johns Hopkins University (JHU) and received two Masters degrees, one in EE from Sharif University of Technology in Iran and another in Applied Mathematics and Statistics from JHU.
Agata Lapedriza
Principal Research Scientist / Institute for Experiential AI at Northeastern
Agata Lapedriza is a Principal Research Scientist at the Institute for Experiential AI, where she leads research on AI for Health and Responsible AI. She is also Affiliated Professor at the Bouvé College of Health Sciences at Northeastern University. Her research interests are related to Computer Vision, Natural Language Processing, Affective Computing, AI for Health and Wellness, Social Robotics, and Responsible AI. More concretely, her current research focuses on Human-Centric AI, which refers to creating AI that meets human needs, enhances human capacities, and aligns with human values. Her research program includes fundamental research on explainable, contextualized, and multi-modal systems for emotion and social signal perception, and their use cases for Health and Human Wellness.