• Machine Learning, Image Classification, Natural Language Processing
• Intelligent Transportation
• Spatial-Temporal Data Mining and Prediction
• Online Disinformation Mining and Detection

Intelligent Transportation 2020	Spatial-Temporal Data Prediction 2020

• AIT 636: Machine Learning
• AIT 746: Advanced Machine Learning
• AIT 690: Urban Computing

Determinant	Eigenvectors and Eigenvalues
Smart Cities	Smart Cities
Smart Cities	Smart Cities Analytics
Video Analytics for Event Detection	Intelligent Transportation Systems
Deep Reinforcement Learning for Traffic Light Control

Welcome

Welcome to the Machine Learning and Urban Computing Group. If you have not started already, please strengthen yourself in Python and Algorithms. You can find my list of publications on my website. I recommend you to read the ones that are relevant to your research, before our first meeting. Always read the new publications that appear on my website. Check this link . Under final project it has helpful instructions about how to write a paper.

Weekly group meetings

Members will be assigned time slots during these meetings to present their research ideas and progress, regardless of how mature the idea is, to receive constructive criticism and feedback from their peers and the advisor. All group members are encouraged to provide feedback to their peers and propose new ideas to expand or extend that research. New research ideas might rise from these discussions. Sometimes the advisor might give a brief talk on topics that concern the group about academic procedures, academic milestones, research milestones, courses, goals, expectations, etc.

Individual meetings

Individual meetings will be arranged upon your request. The email requesting an individual meeting, must specify the reason or agenda for the meeting.

One-Page Research Proposal Summary

At the beginning of every research, you need to write a one-page proposal and email it to me. This is a mandatory first step. It must include the following sections (font: Times New Roman, font size: 11, line spacing: Single, Paragraph spacing: 0):

Title
Title of your research.
Overview
Summary of what you want to do, why is it significant, what is the motivation for doing this research?
Contribution
What has been done in this field and how your work contributes in this field. Contribution means how your research would add to the state-of-the-art science or knowledge. Contribution does not mean describing what you like or want to do.
Impact
What pressing problem might it help us solve? What would the knowledge obtained from your research do for us? How does it advance science?

This is all assuming that you are not repeating someone else’s work. If someone else has already done something similar and answered these questions, you cannot duplicate it and claim it as your own.

Lab Unfinished Projects Excel Sheet

The following excel sheet helps me to keep track of who is working on how many and what projects: . This excel sheet is for you to put the title of your papers that are under work, submitted, or rejected. You can see your name in this excel sheet. If you do not, just add your name. Write the title of each individual paper under your name. Before the title, determine the status of your paper. A paper’s status could be three things: (1) Under Development, (2) Submitted, and (3) Rejected n Times. For instance, if I am still working on a paper and it has never been submitted, I should write under my name:
Under Development: A new model for traffic prediction
If I have a paper that has been rejected two times and I am still working on it to fix it, I should write:
Rejected 2 Times: A new model for traffic prediction
If for any reason, the title of your project changes, you need to update the title in this excel sheet as well. When a paper is accepted, you must remove it from this excel sheet, because then it will go in your personal excel sheet under the published papers.

Funding Policy for PhD

Following are the guidelines regarding how the PhD funding decisions are made:

Summer Funding:
If you are a GRA, to qualify for summer funding, you have to have published or accepted a minimum of 5 papers during the past 12 months, up to April 01.
If you are a GTA, to qualify for summer funding, you have to have published or accepted a minimum of 3 papers during the past 12 months up to April 01.
Academic Year Funding:
If you are a GRA, to keep your academic year funding for the next academic year, you have to have published or accepted a minimum of 3 papers during the past 12 months up to August 01. If the number of published papers is 2 or 1, you will be transferred from GRA to GTA. If it is 0, you will not have any academic year funding.
If you are a GTA, to keep your academic year funding for the next academic year, you have to have published or accepted a minimum of 1 paper during the past 12 months up to August 01. If the number of published papers is 0, you will not have any academic year funding. If it is 4 or more, you will be transferred from GTA to GRA, depending on availability of funds.
Acceptable Publications:
Conferences with a rank of A or B. Conferences with a rank of C do not count. A rank of C is equivalent to an acceptance rate of 25% or more. In other words, only conferences with acceptance rates of 24% or less will count.
Journals must have an impact factor, be related to our field, and belong to a reputable publisher. Before submission to a journal we will discuss whether or not it counts.
Publication fees:
I will pay the registration fee for conferences that I recommend or approve. You are responsible for travel costs and you can always apply for university scholarships or conference scholarships. It is important to submit to domestic conferences to be sure that travel costs are manageable and no visa will be needed. I will always recommend domestic conferences.
If you intend to submit to a Journal that has publication fees, you need to talk to me in advance to see if I will cover the publication fees. I usually do for prestigious and high impact journals.
To defend PhD proposal:
At least 5 papers (published or accepted), at least one of which should be a journal paper.
To defend PhD dissertation:
At least 10 papers (published or accepted), at least two of which should be journal papers.

GMU Writing Center

The GMU writing Center (https://writingcenter.gmu.edu/) teaches writing skills for PhD students, e.g. dissertation writing. They offer one-to-one meetings. You are required to contact them and go through their training. I will check with you at some point to see your certificate of training through Mason Writing Center.

Graduate Student Research and Travel Grants

The office of Graduate Fellowships (gradfellows.gmu.edu) helps Graduate students find and win fellowships, scholarships, and grants. Contact Dr. Kay Agoston kagoston@gmu.edu to make an appointment.

List of Internal Awards: https://provost.gmu.edu/academics-and-research/graduate-education/awards-and-grants

• Dissertation Completion Fellowship – Apply in October and get it in Spring (for PhD students)
• Summer research fellowship – apply January (for PhD and master students)
• Graduate student travel fund (conference travel) – has six deadlines each year: gstf.gmu.edu

List of external grants:

• https://gradfellows.gmu.edu/fellowship-opportunities/
• Every conference has a travel fellowship award for students. I encourage you to always apply.

The Structure of Proposal for PhD Dissertation

1. Abstract
   • In the Abstract, you should answer the question: how your research contributes "to promote the progress of science; to advance the national health, prosperity, and welfare; to secure the national defense; and for other purposes." The abstract should clearly highlight the contribution of your work.
2. Chapter 1: Problem statement and motivation
   • Clearly state what problem is the focus of the work. State the research questions and/or hypotheses.
   • Why is it important to address the problem?
3. Chapter 2: Introduction
   • Highlight the reasons why the problem needs to be addressed
   • Briefly describe the proposed approach
   • Explain the objectives
   • Explain the challenges
   • Explain the contributions
4. Chapter 3: Background and related work
5. Chapter 4: Proposed approach
6. Chapter 5: Preliminary research
7. Chapter 6: Proposed tasks/timelines

Open PhD Position

One PhD position is available, for applicants interested in the research conducted in our lab. Please submit your application for the IST PhD program here. The minimum requirements are:

• you have both a Bachelor and a Master
• all your GPAs are above 3.3
• these three courses in your transcripts: data structure, algorithms, and machine learning or a similar course
• GRE Verbal above 147, Quantitative above 160, and writing above 3.5

Open Positions for Master Students

To be considered for TA or RA positions, you have to have passed AIT 636 and AIT 690 (Urban Computing).

PhD Students

	Sarik Dhungel, 06/2021 - Present Google Scholar Project(s): Intelligent Transportation, Machine Learning
	Zinat Ara, 06/2020 - Present Google Scholar Project(s): Intelligent Transportation, Machine Learning
	Jahnavi Jonnalagadda, 03/2020 - Present LinkedIn Project(s): Spatial-Temporal Data Prediction, Machine Learning

Master Students

	Vishwajeet Vijay Paradkar, 06/2020 - 08/2020 LinkedIn Project(s): Natural Language Processing, Machine Learning, Deep Learning
	Prashanti Maktala, 02/2020 - 05/2020 LinkedIn Project(s): Global land temperature forecasting using long short-term memory network
	Srikanth Vadlamani, 03/2020 - 05/2020 LinkedIn Project(s): Studying the impact of streetlights on street crime rate using geo-statistics
	Sai Shashank Gourisetty, 02/2020 - 05/2020 LinkedIn Project(s): Detecting breast cancer in cell images using deep convolutional networks

Undergraduate Students

	Ian Fitzgerald, 11/2020 - Present LinkedIn Project(s): Understanding online disinformation and propaganda
	Cydney Teasdale, 06/2020 - Present LinkedIn Project(s): Understanding online disinformation and propaganda
	Chandler Teasdale, 06/2020 - 11/2020 LinkedIn Project(s): Understanding online disinformation and propaganda
	Kaylyn Matis, 06/2020 - 11/2020 LinkedIn Project(s): Understanding online disinformation and propaganda
	Seungcheol Lee, 06/2020 - 08/2020 LinkedIn Project(s): Database, Web Service, Front End Visualization
	Jongkeung Choi, 06/2020 - 08/2020 LinkedIn Project(s): Database, Web Service, Front End Visualization

Mahdi Hashemi received the Ph.D. degree in Computing and Information from the University of Pittsburgh, Pittsburgh, PA, USA, in 2017. He is currently an Assistant Professor with the Department of Information Sciences and Technology, George Mason University, Fairfax, VA, USA. He is the founding director of the Machine Learning and Urban Computing Group, where he also specializes in intelligent transportation, spatial-temporal data mining and prediction, and online disinformation mining and detection. He served on the program committee of MLDM 2021 and is a Reviewer Board Member of Information and a Topics Board Member of Remote Sensing, since 2020. He received the Mason Summer Team Impact Project Award to mentor a multidisciplinary team of undergraduate students in 2020. He was nominated for the 2021 George Mason University Teaching Excellence Award.

Journal Papers

• M. Hashemi, H.A. Karimi, "Weighted machine learning for spatial-temporal data", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 3066-3082, 2020.


• M. Hashemi, M. Hall, "Multi-label classification and knowledge extraction from oncology-related content on online social networks", Artificial Intelligence Review, vol. 53, no. 8, pp. 5957-5994, 2020.


• M. Hashemi, "Web page classification: A survey of perspectives, gaps, and future directions", Multimedia Tools and Applications, vol. 79, no. 17, pp. 11921-11945, 2020.


• M. Hashemi, M. Hall, "Detecting and classifying online dark visual propaganda", Image and Vision Computing, vol. 89, no. 1, pp. 95-105, 2019.


• M. Hashemi, "Automatic inference of road and pedestrian networks from spatial-temporal trajectories", IEEE Transactions on Intelligent Transportation Systems, vol. 20, no. 12, pp. 4604-4620, 2019.


• M. Hashemi, "Enlarging smaller images before inputting into convolutional neural network: zero-padding vs. interpolation", Journal of Big Data, vol. 6, no. 98, 2019.


• M. Hashemi, H.A. Karimi, "Weighted machine learning", Statistics, Optimization and Information Computing, vol. 6, no. 4, pp. 497-525, 2018.


• M. Hashemi, M. Hall, "Visualization, feature selection, machine learning: Identifying the responsible group for extreme acts of violence", IEEE Access, vol. 6, no. 1, pp. 70164-70171, 2018.


• M. Hashemi, "Dynamic, stream-balancing, turn-minimizing, accessible wayfinding for emergency evacuation of people who use a wheelchair", Fire Technology, vol. 54, no. 5, pp. 1195-1217, 2018.


• M. Hashemi, "Emergency evacuation of people with disabilities: A survey of drills, simulations, and accessibility", Cogent Engineering, vol. 5, no. 1, pp. 1506304, 2018.


• M. Hashemi, "Reusability of the output of map-matching algorithms across space and time through machine learning", IEEE Transactions on Intelligent Transportation Systems, vol. 18, no. 11, pp. 3017-3026, 2017.


• M. Hashemi, "A testbed for evaluating network construction algorithms from GPS traces", Computers, Environment and Urban Systems, vol. 66, pp. 96-109, 2017.


• M. Hashemi, "Intelligent GPS trace management for human mobility pattern detection", Cogent Engineering, vol. 4, no. 1, pp. 1390813, 2017.


• M. Hashemi, H.A. Karimi, "Collaborative personalized multi-criteria wayfinding for wheelchair users in outdoors", Transactions in GIS, vol. 21, no. 4, pp. 782-795, 2017.


• M. Hashemi, H.A. Karimi, "A weight-based map-matching algorithm for vehicle navigation in complex urban networks", Journal of Intelligent Transportation Systems, vol. 20, no. 6, pp. 573-590, 2016.


• M. Hashemi, H.A. Karimi, "Indoor spatial model and accessibility index for emergency evacuation of people with disabilities", Journal of Computing in Civil Engineering, vol. 30, no. 4, pp. 04015056, 2016.


• M. Hashemi, A. Sadeghi-Niaraki, "A theoretical framework for ubiquitous computing", International Journal of Advanced Pervasive and Ubiquitous Computing, vol. 8, no. 2, pp. 1-15, 2016.


• M. Hashemi, H.A. Karimi, "A critical review of real-time map-matching algorithms: Current issues and future directions", Computers, Environment and Urban Systems, vol. 48, pp. 153-165, 2014.


• M. Hashemi, M.R. Malek, "Protecting location privacy in mobile geoservices using fuzzy inference systems", Computers, Environment and Urban Systems, vol. 36, no. 4, pp. 311-320, 2012.


• M. Hashemi, A.A. Alesheikh, M.R. Zolfaghari, "A spatio-temporal model for probabilistic seismic hazard zonation of Tehran", Computers & Geosciences, vol. 58, pp. 8-18, 2013.


• M. Hashemi, A.A. Alesheikh, M.R. Zolfaghari, "A GIS-based time-dependent seismic source modeling of Northern Iran", Earthquake Engineering and Engineering Vibration, vol. 16, no. 1, pp. 33-45, 2017.


• M. Hashemi, A.A. Alesheikh, "GIS: agent-based modeling and evaluation of an earthquake-stricken area with a case study in Tehran, Iran", Natural Hazards, vol. 69, no. 3, pp. 1895-1917, 2013.


• M. Hashemi, A.A. Alesheikh, "Development and implementation of a GIS-based tool for spatial modeling of seismic vulnerability of Tehran", Natural Hazards and Earth System Sciences, vol. 12, pp. 3659-3670, 2012.


• M. Hashemi, A.A. Alesheikh, "A GIS-based earthquake damage assessment and settlement methodology", Soil Dynamics and Earthquake Engineering, vol. 31, no. 11, pp. 1607-1617, 2011.

Conference Proceedings

• J. Jonnalagadda, M. Hashemi, "Forecasting atmospheric visibility using auto regressive recurrent neural network", In IEEE 21st International Conference on Information Reuse and Integration for Data Science. Las Vegas, NV, USA: IEEE, pp. 209-215, 2020.


• P. Maktala, M. Hashemi, "Global land temperature forecasting using long short-term memory network", In IEEE 21st International Conference on Information Reuse and Integration for Data Science. Las Vegas, NV, USA: IEEE, pp. 216-223, 2020.


• S. Vadlamani, M. Hashemi, "Studying the impact of streetlights on street crime rate using geo-statistics", In IEEE 21st International Conference on Information Reuse and Integration for Data Science. Las Vegas, NV, USA: IEEE, pp. 231-236, 2020.


• M. Hashemi, M. Hall, "Identifying the responsible group for extreme acts of violence through pattern recognition", In International Conference on HCI in Business, Government, and Organizations. Cham: Springer, pp. 594-605, 2018.


• M. Hashemi, H.A. Karimi, "A machine learning approach to improve the accuracy of GPS-based map-matching algorithms", In IEEE 17th International Conference on Information Reuse and Integration. Pittsburgh, PA, USA: IEEE, pp. 77-86, 2016.


• M. Hashemi, H.A. Karimi, "Seismic source modeling by clustering earthquakes and predicting earthquake magnitudes", In Smart City 360°. Cham: Springer, pp. 468-478, 2016.


• M. Hashemi, A.A. Alesheikh, "Spatio-temporal analysis of Tehran's historical earthquakes trends", In Advancing Geoinformation Science for a Changing World. Berlin, Heidelberg: Springer, pp. 3-20, 2011.