Iman Yeckehzaare Email & Phone Number
@honor.education
3 phones found area 734
LinkedIn matched
Who is Iman Yeckehzaare? Overview
A concise factual answer block for searchers comparing this professional profile.
Iman Yeckehzaare is listed as Postdoctoral Research Associate at Massachusetts Institute of Technology, based in Cambridge, Massachusetts, United States. AeroLeads shows a work email signal at honor.education, phone signal with area code 734, and a matched LinkedIn profile for Iman Yeckehzaare.
Iman Yeckehzaare previously worked as Head of Research at Honor Education, Et Al and Founder at 1Cademy. Iman Yeckehzaare holds Doctor Of Philosophy (Ph.D.), Information Science/Studies from University Of Michigan - School Of Information.
Email format at Massachusetts Institute of Technology
This section adds company-level context without repeating Iman Yeckehzaare's masked contact details.
AeroLeads found 1 current-domain work email signal for Iman Yeckehzaare. Compare company email patterns before reaching out.
About Iman Yeckehzaare
I remain dedicated to my career goal of being an information scientist with a focus on collective intelligence, cognitive and experimental psychology, and design-based research leveraging quantitative and qualitative analysis in the development of online learning/research communities.
Listed skills include Human Computer Interaction, Python, Html 5, Css, and 41 others.
Iman Yeckehzaare's current company
Company context helps verify the profile and gives searchers a useful next step.
Iman Yeckehzaare work experience
A career timeline built from the work history available for this profile.
Postdoctoral Research Associate
CurrentI'm super excited to share that I joined MIT Center for Collective Intelligence Research.
Head Of Research
CurrentI'm super excited to share that I joined Honor Education as a researcher to conduct online controlled experiments on cool and innovative design features to improve students' online learning.
Founder
Current1Cademy facilitates a large-scale collaboration of students and researchers from different schools to:1- Summarize:We summarize the gist of every valuable piece of knowledge on the Web into small chunks of knowledge that we call "nodes."2- Link:We identify and visualize the prerequisite knowledge "links" between nodes.3- Evaluate:We group-evaluate the nodes and links, through up/down-votes and comments.4- Improve:We collaboratively improve and up-date nodes and links through proposals and community approvals.https://1cademy.us/homehttps://www.youtube.com/channel/UCKBqMjvnUrxOhfbH1F1VIdQ
Expertideas: Incentivizing Domain Experts To Contribute To Wikipedia
Collaborators: Professor Yan Chen, Professor Rosta Farzan, Professor Robert Kraut, Iman Yeckehzaare, Ark Fangzhou ZhangThis study investigates the extent to which different incentives might motivate domain experts to contribute to Wikipedia by conducting randomized field experiments on Wikipedia. We explore the impact of social amplifier on the private benefit from contributing to the public good. When an expert edits a Wikipedia article relevant to her research, the private benefit is multiplied by the number of people who view that article. To measure the effect of the social amplifier, we introduce exogenous variations on the number of times the recommended Wikipedia articles have been viewed over the last 30 days. We are conducting a controlled field experiment by delivering different versions of an email message inviting researchers world-wide to contribute to Wikipedia. By studying participants' behavioral responses to various incentives using a 3×2×2 factorial design, this research investigates the incentives that might motivate scholars to contribute to Wikipedia.• developed crawlers to retrieve data from Google Scholar, Wikipedia, and RePEc.• developed a Wikipedia Bot to post comments on talk pages.• conducted usability testing and interviewed researchers about the study website.• developed an administrative web application using Django framework, including managing the subjects’ data, local time estimation, email tracking, incorporating the Wikipedia Bot. The crawlers working on multiple stations, gather the data and submit it to the administrative web application on AWS, which uses the data to conduct the study.• doing data analysis, and authoring my pre-candidacy paper about the field experiment.
Real Or Bogus: Predicting Susceptibility To Phishing With Economic Experiments
Collaborators: Professor Yan Chen, Iman Yeckehzaare, Ark Fangzhou ZhangWe present a lab-in-the-field experiment to demonstrate how individual behavior in the lab predicts their ability to identify phishing attempts. Using the business and finance staff members from a large public university in the U.S., we find that participants who are intolerant of risk, more curious, and less trusting commit significantly more false positive errors in an information security quiz. We also replicate prior results on demographics, including age, gender, and education level. Our results suggest that behavioral characteristics such as risk attitude, curiosity, and trust can be used to predict individual ability to identify phishing interfaces.
Research Assistant
Researching under supervision of Professor Charles Severance, contributing in development of an auto-grader service for CTools, the Learning Management System of the University of Michigan.
Ui Developer
I worked with a research group under supervision of Professor Paul Resnick at the University of Michigan, School of Information. The project was about “Applying Behavioral Economics to Persistent Health Challenges”. Over this short period of time, I helped them to improve the User Interface of the project website. Working directly with Professor Resnick was a great opportunity for me to develop my research skills, and apply my experiences in a professional research project.
Research Assistant
Rumorlens: A system for analyzing the impact of rumors and corrections in social mediaAbstract: Some rumors spread quickly and widely through social media. Journalists write about them, both to help the public understand whether they are true, and to help the public understand how widely misinformation and corrections have spread, and how they did. We describe RumorLens, a suite of interactive tools that are designed to help journalists identify new rumors on Twitter and assess the audiences that rumor and correction tweets have reached. The tools make efficient use of human labor to assess whether a rumor’s content is interesting enough to warrant further exploration, to label tweets as spreading, correcting, or unrelated to the rumor, and to analyze the rumor visually. Behind the scenes, automated learning and computation amplifies the effectiveness of that labor, making it feasible to engage journalists and the broader public to run a continuous rumor-monitoring service. My role: Studied Named Entity Recognizers and Wikifiers to extract entities from news articles, finding the most different articles from what the user has already read.
Research Assistant
- Founder of IUST-One team in KDD CUP 2011 track1, developed novel User-based and Item-based Collaborative Filtering algorithms by the use of an innovative correlation coefficient factor and applying a cascade feed-forward neural network to merge the results.- Studied several state-of-the-art Chatbots, especially Alice, Eliza and Program Sharp, yielding a Persian AIML based chatbot by the use of CBR approaches.- Applied Collaborative Filtering techniques to Linkage Learning.- Researched on Recommender Systems and their applications in e-marketing.
Undergraduate Teaching Assistant
I graded Programming Language Design and Implementation course, taught by Professor Ghassem Jaberipur.
Iman Yeckehzaare education
Doctor Of Philosophy (Ph.D.), Information Science/Studies
Master Of Science In Information (Msi), Human Computer Interaction (Hci), Information Economics For Management (Iem)
Bachelor Of Engineering (Be), Information Technology
Bachelor Of Engineering (Be), Computer Engineering
Education record
Frequently asked questions about Iman Yeckehzaare
Quick answers generated from the profile data available on this page.
What company does Iman Yeckehzaare work for?
Iman Yeckehzaare works for Massachusetts Institute of Technology.
What is Iman Yeckehzaare's role at Massachusetts Institute of Technology?
Iman Yeckehzaare is listed as Postdoctoral Research Associate at Massachusetts Institute of Technology.
What is Iman Yeckehzaare's email address?
AeroLeads has found 1 work email signal at @honor.education for Iman Yeckehzaare at Massachusetts Institute of Technology.
What is Iman Yeckehzaare's phone number?
AeroLeads has found 3 phone signal(s) with area code 734 for Iman Yeckehzaare at Massachusetts Institute of Technology.
Where is Iman Yeckehzaare based?
Iman Yeckehzaare is based in Cambridge, Massachusetts, United States while working with Massachusetts Institute of Technology.
What companies has Iman Yeckehzaare worked for?
Iman Yeckehzaare has worked for Massachusetts Institute Of Technology, Honor Education, Et Al, 1Cademy, University Of Michigan, and Iran University Of Science And Technology.
How can I contact Iman Yeckehzaare?
You can use AeroLeads to view verified contact signals for Iman Yeckehzaare at Massachusetts Institute of Technology, including work email, phone, and LinkedIn data when available.
What schools did Iman Yeckehzaare attend?
Iman Yeckehzaare holds Doctor Of Philosophy (Ph.D.), Information Science/Studies from University Of Michigan - School Of Information.
What skills is Iman Yeckehzaare known for?
Iman Yeckehzaare is listed with skills including Human Computer Interaction, Python, Html 5, Css, Machine Learning, Javascript, Php, and Mysql.
Search by job title, company, industry, location, and seniority. Export verified B2B contact data when you need it.
Start free trial