A few memories from my first @icors2026 conference as an Oral Presentation.🤍✨️
Grateful for the opportunity to present my work, meet inspiring researchers, make new friends, and become part of such a welcoming
scientific community.
#ICORS2026#Statistics#MachineLearning
Closing my @icors2026 journey with a few memorable moments!👩🏻💻🇹🇷
Grateful for the opportunity to present my work, exchange ideas with researchers from around the world, and learn from leading experts in robust statistics.
Until the next conference!
#ICORS2026#RobustStatistics
I’m happy to share that my abstract titled “Uncertainty-aware Statistical Learning for Robust Clinical Risk Analytics” has been accepted as a Contributed Oral Presentation at the International Conference on Robust Statistics 2026 (#ICORS2026), to be held in Istanbul, Türkiye.
Don’t miss @Maral__94 on Stage 1! She’s breaking down the powerful intersection of financial fraud detection and healthcare AI. See you there! #AppliedHealthcareAISummit
Great practical discussion on imbalanced learning, threshold tuning, and ensemble models translating directly into clinical risk prediction. #AppliedHealthcareAISummit@Maral__94
I'm happy to share that my talk is now officially scheduled at the #AppliedAISummit2026!🚀
Presenting: "Scaling Imbalanced ML from Financial Fraud to Clinical Risk: A Practical Deployment Framework"
Date: April 15, 2026
Details:
https://t.co/p4kzsw52jA
I'm happy to share that my talk is now officially scheduled at the #AppliedAISummit2026!🚀
Presenting: "Scaling Imbalanced ML from Financial Fraud to Clinical Risk: A Practical Deployment Framework"
Date & Time: April 15, 2026 | 3:45–4:15 pm ET
Details:
https://t.co/p4kzsw52jA
Thrilled to be invited as a speaker at the 2026 Healthcare Applied AI Summit! 🎉
Presenting: "Scaling Imbalanced ML from Financial Fraud to Clinical Risk: A Practical Deployment Framework"
Details & profile: https://t.co/Lxb3xXrFp4
Can't wait!🚀 #AIinHealthcare#MachineLearning
Thrilled to be invited as a speaker at the 2026 Healthcare Applied AI Summit! 🎉
Presenting: "Scaling Imbalanced ML from Financial Fraud to Clinical Risk: A Practical Deployment Framework"
Details & profile: https://t.co/Lxb3xXrFp4
Can't wait!🚀 #AIinHealthcare#MachineLearning
Merry Christmas and Happy Holidays! 🎄✨
Reflecting on an exciting year full of growth and grateful for new research opportunities ahead in machine learning and distributed systems.
Wishing everyone joy, peace, and inspiration in the new year!
#HappyHolidays#NewYear2026
This year I devoted 3,788 minutes to language learning, completing 1,191 lessons in French🇲🇫, German🇩🇪, and English. The outcome: placement in the global top 3% and two weeks in the Diamond League.
Duolingo 2025 Year in Review
Petit à petit, l’oiseau fait son nid. 🐦
This year’s turning point: Istanbul, standing on the bridge between continents.
Perfect metaphor for balancing deep technical work with moments that recharge the mind.
Ready for the next round of models, papers, and breakthroughs.
🌏🇹🇷☀️🌿
#DataScience#ML#BirthdayTrip
I’m proud to announce that I’ve joined the IEEE Engineering Medicine and Biology Society (EMBS) Technical Committee on Biomedical Imaging and Image Processing (BIIP) as a Member. Looking forward to contributing to advancements in #medicalimaging and #AI!
I’m happy to share that I’ve obtained a new certification: Bioinformatics: Long-read Sequencing Applications from SHARCNET!
Mind-blowing workshop on PacBio HiFi sequences and long-read tech for genomics!
🎉Proud to have completed the "Introduction to Anti-Money Laundering Regulations" course on Alison!Gained valuable insights into money laundering complexities and prevention strategies across finance and healthcare. Excited to apply these skills! #AntiMoneyLaundering#DataScience
Diving into the Applied #AISummit2025!
This 3-day virtual event unites thousands of AI pros with 50+ sessions on Generative AI,LLMs,NLP, and AI governance,themed “Lessons Learned Putting AI to Work.”
https://t.co/I8BUyqgqZD
Excited to share my latest project: Credit Card Fraud Detection! 🚀
I developed a #Machinelearning solution using Isolation Forest, Random Forest, and XGBoost to detect fraud in the creditcard dataset.
Check out the code on GitHub: https://t.co/ys5QMcsMs4