Hello! I am a PhD student in the Computer & Information Science & Engineering at the University of Florida. I am interested in exploring ways to make Machine Learning trustworthy, fair, and safe. I have explored explainability and fairness aspects of Machine Learning to make it fair. I hope to continue exploring this area in future.
I majored in Computer Science from Amirkabir University of Technology (AUT) and graduated with a minor in Mathematics in 2014. At AUT, I worked on research projects about use of reinforcement learning in mobile networking. In my free time, I enjoy reading biographies, cross stich and ride my bike.
I have diverse background in domains such as Machine Learning/AI, Human Computer Interaction, and Software Development
Deep Learning Framework: Tensorflow/Keras (using frequently), PyTorch (using if needed)
Other: python, NLP, Computer vision, reinforcement learning
Human Computer Interaction
Technologies: Dialog fow,Affinity Diagrams, Balsamique, Invision, prototyping, wireframe,task flow
Skills: Qualitative analysis, Quantitative analysis, Hypothesis Testing, Survey Design
Other: Java, Agile methodologies, Heroku, Vercel, Object-Oriented Design
I have diverse work experience in academics, non-profit organizations and Tech startups related to Machine Learning/AI.
Deep Learning InternGeopipe - 17 May, 2021- 6 August,2021
Tech Policy FellowElectronic Privacy Information Center - 26 May, 2020- 31 July, 2020
- Evaluated the current differential privacy effort happening at U.S. Census Bureau and bolded the current problems.
- Investigated the current development of content tracing app and their consequences for Public privacy.
Graduate Research AssistantHuman Experience Research Lab - December, 2017-now
As a PhD student, I worked on multiple projects about Machine Learning/AI and Human Computer Interaction.
ML research assistantDepartment of Health Outcomes & Bioinformatics - Aug 2015-November 2016
- Analyzed time series data to find the existing trend of using Stimuli drug in Schools.
- Designed the research agenda and most efficient ways to visualize the data using Tableau.
- Predicting the readmission rate for patients who over utilize the insurance. Using unstructured four-year ER visits data, I was able to improve the accuracy by %10.
Ethical and fairness study of Predictive Policing
Fairness-Aware Methodology in Juvenile Recidivism
Sentiment and Trust in AI
Mobile Decision Aid (MODA)
Trust and QOS optimization in adhoc networks
Outstanding International Student Award at UF|2020
Cornell Summer School on Designing Technology for Social Impact Scholarship|Summer 2021
Bank of America Travel Award to attend Grace Hopper Celebration|Fall 2020
Among the three reciepents of Media Democracy Fund fellowship|Summer 2020
Google travel award for BPDM conference at Howard University|Febraury 2019
Gartner Graduate Fellowship CISE department at UF|March 2020
Induction to AEL Top Graduate Student Honor Society | Fall 2019
Deep Learning Specialization | July 2019
Concepts: Neural networks, structure of ML projects, CNN, RNNCertificate Link
AI for Medicine | June 2020
Concepts: MRI segemntation, transfer learning, cox survival analysisCertificate Link
Google Data Analytics, Currently taking
Concepts: Data cleaning, problem solving, critical thinking, data ethics, and data visualization