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Shalini Ananda
ML Reseacher
Shalini Ananda is a seasoned machine learning researcher and instructor with a track record of over a decade. She specializes in applying deep learning across various domains such as healthcare, drug discovery, NLP, generative music, and medical imaging. Shalini boasts expertise in machine learning, programming languages like C++ and Python, NLP/transformers, full-stack development, computer vision, generative models, cloud solutions, DevOps, and deployment. Her forte lies in innovation through tool creation and extracting knowledge from research. Shalini's educational background includes a PhD in Materials Engineering from UC San Diego, a Bachelor of Science in Applied Mathematics, and a Masters of Science in Applied Mathematics from the University of Sydney. In her professional journey, Shalini has held key roles in organizations like Anandamide Sound Machine, UCSC Silicon Valley Extension, Scale AI, EdCast by Cornerstone, UC San Diego Extension, Sensentia, Rock Health, CRIXlabs Inc., Stanford University, and UC San Diego Magnetic Resonance Lab.
Highlights
Exciting Update: Hackathon Success and Project Progress! 🏆🚀
I'm thrilled to share some recent achievements and progress on my project, RefactorEarth:
GenLab Venture Studios Hackathon Wins:
- 🥇 1st Place
- 🌟 Best on Theme
- 🆕 Best New Team
A huge thank you to Brady F. and Daniel Riedel for organizing this incredible event. The experience was invaluable!
Thanks to judges SC Moatti Imo Udom Jesse Robbins Shreyas Srinivas for your continuing support.
Special Recognition:
- Grateful to Benjamin Dunphy and @swyz of the Latent Space podcast for the AI Engineer Fair ticket prize.
- Appreciative of the insights from Damien M.* (Deepgram) and Graham Steele (Groq) on potential applications and how companies can integrate these tools effectively.
- Thanks to Vince Kohli,An Empathy Scholar/Impact Tech Investor/LLMs for the networking opportunities and inspiring discussions.
Conference Highlights:
- Joined Microsoft for Startups (Thanks Aishwarya Srinivasan and Pamela Fox for the guidance on how to connect with more contributors!)
- Explored the concept of a GitHub sustainability badge with Alex Malebranche of GitHub
Next Steps for RefactorEarth:
- Enhancing the visual interface for code variant analysis (inspired by Coframe).
- Integrating NASA's latest consumption analysis tool.
- Expanding RefactorEarth's contributor base (excited to collaborate with new team members!) and ofcourse! publish my Notion page on the step by step of how this tool was built. To all the amazing people I met and who offered support - I'm looking forward to our future collaborations!
#Sustainability #CodeOptimization #AIEngineering #Hackathon #Innovation
Let's connect if you're interested in sustainable tech or want to learn more about RefactorEarth!
Adaptation and Ethical Decision-Making Simulations (Foundational) with Temporal Odyssey
Why This is Important:
- Baseline Understanding: Provides fundamental insights into how AI agents adapt to changing social norms and ethical challenges.
- Metric Development: Establishes key metrics like Adaptability Score and Ethical Decision-Making for evaluating AI performance.
- Scenario Complexity: Introduces a structured framework for studying AI behavior in varied, realistic settings.
- Preparation for Advanced Simulations: Lays the groundwork for more complex studies by identifying core challenges and refining methodologies.
- AI Safety: Enhances understanding of AI safety mechanisms in dynamic and unpredictable environments.
- Decision-Making: Explores how AI systems can maintain ethical behavior and social cohesion in complex scenarios.
#AI #MachineLearning #ReinforcementLearning #AISafety #EthicalAI #TemporalOdyssey #AIResearch #Adaptability #DecisionMaking #AIExperiments #ArtificialIntelligence #AICommunity
Check out the detailed experiments and findings:
https://lnkd.in/gqTzhqXt
