Mohammad Falakmasir

I have a background in Software Engineering and started my first job as a developer in 2002. Later on, I co-founded a startup focusing on web-based learning platforms and multimedia content for e-learning. I finished college and continued working in the startup two years, collaborating with a number of major e-learning institutes in Iran. Then, I went to graduate school and got my Master's Degree with a focus on Business Intelligence and Decision Support Systems. Graduate school was a transition for me from Software Engineering to Data Mining and Artificial Intelligence. After graduating, I decided to pursue my passion for machine learning and data mining as a PhD student in the US. You can find more about me in my CV.

One Page Resume

Curriculum Vitae

Employment

  • September 2019 – Present

    Wells Fargo

    NLP Data Scientist

    Working as a member of AI Center of Excellence, applying Machine Learning and topic modeling models to analyze consumer complaints data. Building NLP models to and identify unfair and deceptive treatment of customers and escalate them through company’s executive offices.

  • January 2019 – September 2019

    CXO Nexus

    Sr. Engineering Manager, Machine Learning Platform

    Leading a team of machine learning engineers to develop a Business Intelligence (BI) platform to provide insight about companies’ IT spending by aggregating data from account payable, purchase orders, and other financial records and comparing them with like-size agencies with similar business line. More specifically, we are building a platform targetted to the C suite to provide visibility into their IT spending through resellers and value added resellers to provide negotiation leverage, identify compliance risks, and eliminate redundant vendors and hypebeast resellers.

  • May 2018 – December 2018

    Astound AI

    Machine Learning Scientist

    Worked with a team of machine learning engineers and natural language processing experts to build a knowledge engineering platform to support organizations to replace forms and emails with collaborative service experiences that incorporate live chat, intelligent knowledge retrieval, and real-time request fulfillment. In particular, I was part of a team focused on building an automated IT support system that provides answers to routine questions, accurately assigns and categorizes incidents, and recommends the best resolutions.

  • May 2016 – September 2017

    LegalSifter

    Data Scientist

    Worked as a Machine Learning lead on ContractSifter and LegalSifter. I was working with a sizable corpus of contracts and applying unsupervised / semi-supervised methods to facilitate information extraction. I had the following responsibilities:
    - Scraping publicly available company filings and contracts from web.
    - Preprocessing, cleansing, and verifying the integrity of data used for analysis.
    - Text Mining using unsupervised and semi-supervised models.
    - Optimizing classifiers (sifters) using machine learning and feature engineering.
    - Building a platform to enhance data-collection, annotation, and sifter development process.

  • August 2009 – August 2011

    e-Learning Center, University of Tehran

    Data Analysit and Technology Consultant

    Led a team of engineers in migrating to a new online learning platform that supports online monitoring of student interactions.
    Created an online analytical processing (OLAP) framework using Microsoft SQL Server Analysis Service (SSAS).

  • March 2008 – August 2009

    E-Learning Center, Iran University of Science and Technology

    Technical Support

    Performed technical software and server support for online learning environment. Provided help and supplementary materials for learners and instructors to use the environment effectively, assisting with critical system outages, software upgrades, and capacity planning, maintenance, and support, in a 24x7 availability environment.

  • March 2006 – March 2008

    Click E-Learning Solutions

    Co-Founder and CTO

    Led a team of engineers to develop a PHP based online learning platform that served 4 major e-learning institutes with more than 10,000 online students.
    Led a team of content developers to produce we-based, interactive, multimedia courseware using Adobe Flash, Presenter, and Captivate.

  • August 2004 – March 2006

    Computer Aided Process Engineering (CAPE) Lab

    Software Architect and IT Project Manager

    Lead designer and developer of software applications in oil, gas and petrochemical industry, including Oilfield Development Industry Feasibility Analysis (ODIFA), Thermodynamic Properties Calculations (Thermoprop), and Pipeline Transformation Simulation (PipeSim), using Borland C++ Builder, Microsoft Visual C++ and Visual C#.Net.

  • March 2002 – December 2004

    Pishrayan Paytakht

    Software Designer and Developer

    Cooperated in team Projects, to develop web-based, network and windows-based applications, including Network Surveillance and Control (3rd Eye), IP Based Camera Surveillance System (Varadid), using Borland C++ Builder and Delphi.

Research

  • August 2012 – April 2018

    Learning research & Development Center (LRDC)

    Graduate Student Researcher

    Working with Kevin Ashley, Chris Schunn, and Diane Litman on ArgumentPeer project, an NSF funded project for Teaching Writing and Argumentation with AI-Supported Diagramming and Peer Review. Developing computational linguistic model that identifies argumentative elements from student essays and provides feedback and scaffolding based on the identified elements.
    Developed a web-based application (ArguPod) using Flask, JavaScript, and mongodb for annotating essays and creating diagrams from the annotations.

  • May 2015 – September 2015

    Pearson Center for Digital Data, Analytics & Adaptive Learning

    Summer Intern

    Worked with Jose González-Brenes and Geoff Gordon to create a data analytics pipeline using Python to predict students’ post-test scores based on their interactions with an educational game. More ...

  • June 2012, 2013, and 2014

    LearnLab Summer School

    Student and Mentor

    Worked under the mentorship of Geoff Gordon and Zach Pardos to develop a spectral learning method for inferring student mastery in a Java self-assessment tool.
    Worked with Michael Yudelson to design a new model for inferring student mastery on the data from KDD Cup 2010, Educational Data Mining Challenge with 20 million transactions belonging to over 6 thousand students working on nearly 150 sections of mathematics curriculum practicing around 1650 skills.
    Mentored a summer school student to use different text similarity metrics in order to cluster reading comprehension passages in a language tutoring system.

  • September 2011 – March 2012

    Personalized Adaptive Web Systems (PAWS) Lab

    Graduate Student Researcher

    Worked with Peter Brusilovsky and Sharon Hsiao to build a statistical model for analyzing the impact of social performance visualization on student usage patterns in an adaptive educational system.

Education

  • September 2011 - Present

    University of Pittsburgh

    MS + PhD Student in Intelligent Systems Program

    Main research is focused on the application of Artificial Intelligence in Education. More specifically, improving writing and argumentation using computer and AI mediated tools. I also have publications in Adaptive Educational Hypermedia, Intelligent Tutoring Systems, Student Modeling, and Peer-Review.
    Advisor: Prof. Kevin Ashley

  • September 2008 – September 2010

    Sharif University of Technology

    MS in Information Technology Engineering

    My main studies were focused on Business Intelligence and Decision Support Systems, Machine Learning and Data Mining Concepts and Applications. My final project was An Investigation of Data Mining Methods in Educational Systems along side with applying several data mining methods on the web-usage logs of online students.
    Advisor: Prof. Jafar Habibi

  • September 2001 – September 2006

    University of Science and Technology

    BS in Computer Software Engineering

    My major was Software Engineering and Computer Programing with beneficial courses including Computer Architecture, Object Oriented Programing, Programing Languages, Network and Web Programing. As a B.S. final project I was part of a team to develop an Online Learning Environment for the e-learning center at our university.

Recognition

  • Andrew Mellon Pre-doctoral Fellowship

    Dietrich School of Arts & Sciences

    Academic Year of 2014-2015

  • Best Student Paper

    International Conference of Educational Data Mining (EDM 2013)

    Memphis, TN

  • Director's Fellowship

    Learning Research & Development Center (LRDC)

    Academic Year of 2012-2013

  • ISP Fellowship

    Dietrich School of Arts & Sciences

    Academic Year of 2011-2012

Publications

Educational Data Mining

Falakmasir, M. H., Gonzalez-Brenes J. P., S., Gordon, G. J., & DiCerbo, K. E. (2016) A Data-Driven Approach for Inferring Student Proficiency from Game Activity Logs. In 3rd ACM Conference on Learning@ Scale (L@S 2016), Edinburgh, Scotland, (pp.341-349). [PDF]

Falakmasir, M. H., Yudelson, M., Ritter, S., & Koedinger, K. (2015) Spectral Bayesian Knowledge Tracing. In 8th International Conference on Educational Data Mining (EDM 2015), Madrid, Spain, (pp.360-363). [PDF]

Falakmasir, M. H., Pardos, Z. A., Gordon, G. J. & Brusilovsky, P. (2013) A Spectral Learning Approach to Knowledge Tracing. (Best Student Paper) In 6th International Conference on Educational Data Mining (EDM 2013), Memphis, TN, US, (pp. 28–35). [PDF]

Falakmasir, M. H., Hsiao, I. H., Mazzola, L., Grant, N. & Brusilovsky, P. (2012) The Impact of Social Performance Visualization on Students. In 12th International Conference of Advanced Learning Technologies (ICALT 2012), Rome, Italy, (pp. 565-569). [PDF]

Falakmasir, M. H. & Habibi, J. (2010) Using Educational Data Mining Methods to Study the Impact of Virtual Classroom in e-Learning. In 3rd International Conference on Educational Data Mining (EDM 2010), Pittsburgh, PA, US, (pp. 241-248). [PDF]

Falakmasir, M. H., Habibi, J., Moaven S., & Abolhassani, H. (2010) Business Intelligence in e-Learning: (Case Study of Iran University of Science and Technology). In 2nd International Conference on Software Engineering and Data Mining (SEDM 2010), Chengdu, China (pp. 473-477). [PDF]

Natural Language Processing

Falakmasir, M. H., Ashley, K. D., (2017) Utilizing Vector Space Models for Identifying Legal Factors From Text. In the 30th International Conference on Legal Knowledge and Information Systems (JURIX2017), Luxembourg. [PDF]

Jabbari F., Falakmasir, M. H., Ashley, K. D., (2016) Identifying Thesis Statements in Student Essays: The Class Imbalance Challenge and Resolution. In the 29th International Florida Artificial Intelligence Research Society Conference (FLAIRS-29), Key Largo, Florida, USA, (pp. 220-225). [PDF]

Falakmasir, M. H., Ashley, K. D., Schunn, C. D., & Litman, D. J. (2014) Identifying Thesis and Conclusion Statements in Student Essays to Scaffold Peer Review. In 12th International Conference on Intelligent Tutoring Systems (ITS 2014), Honolulu, HI, US (pp.254-259). [PDF]

Lynch, C., Falakmasir, M. H., Ashley, K. D., (2014) Matching Hypothesis Text in Diagrams and Essays. In 7th International Conference on Educational Data Mining (EDM 2014), London, UK, (pp. 383-384). [PDF]

Falakmasir, M. H., Ashley, K. D., & Schunn, C. D. (2013) Using argument diagramming to improve peer grading of writing assignments. In 1st Workshop on Massive Open Online Courses (moocshop) at the 16th Annual Conference on Artificial Intelligence in Education (AIED 2013), Memphis, TN, USA, (pp. 41-48). [PDF]

Lynch, C., Ashley, K. D., Falakmasir, M. H. (2012) Comparing Argument Diagrams. In 27th Annual Conference on Legal Knowledge and Information Systems (JURIX), Amsterdam, Netherlands, (pp. 81-90). [PDF]

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