Research Interests: AI and Agriculture/Forestry, Natural Language Processing, Mobile and Edge Computing, Distributed Systems, Social Network Analysis and Mining
Grants
Total 584K so far.
- MTRAC AgBio Full Grant, PI, 147K, 2025
- MTRAC AgBio Grant Phase I, PI, 45K, 2025
- CSCE mini grant, GVSU, PI, 500, 2025
- Sandbox Learning Innovation Grant, FTLC, GVSU, PI, 500, 2025
- PRTS, ACI, PI, 33K, 2024
- College of Computing, GVSU, Seed Grant, PI, 20K, 2024
- Adopt a Hemlock, PI, 7K, 2024
- ESC Grant, PI, 5K, 2023
- GVSU University Counselling, PI, 7K, 2023
- Engagement Scholarship Consortium, PI, 5K, 2023
- MI DNR & Adopt a Hemlock, PI, 32K, 2023
- Stenger & Stenger, PI, 53K, 2023
- Array Of Engineers Grant, PI, 38K, 2023
- Special Project GA, GVSU, 9K, 2022-2023
- Array Of Engineers Gift, PI, 45K, 2022
- P&G Gift, Co-PI, 50K, 2022
- Special Project GA, GVSU, 9K, 2021-2022
- CSCE Grant, GVSU, 3K, 2021
- P&G Gift, Co-PI, 75K, 2021
Current Research Projects
AdmitFair: Multi agent, gen AI powered approach to tackle holistic college admission challenges.
AI and Forestry: Partnering with Adopt a Hemlock and MI DNR to leverage computer vision and UAVs to facilitate early detection of oak wilt in Michigan
AI and Indoor Farming: Leverage edge AI for efficient indoor farm management
Startup: EdgeForestry
Current Students
- Colin Brennan, EdgeForestry
- Ahsanul Kabir, EdgeForestry
- Jacob Ferrari, EdgeForestry
- Ishra Naznin, EdgeForestry
- Mortadha Ghnimi, AI in Indoor Farms Project
Past Students
- Abu Naweem Khan, now at Dematic
- Debit Paudel, now at Mitsubishi
- Griffin Going, now at RankOne Computing
- Esteban Echeverri Jaramillo, Now pursuing PhD at Michigan State University
- Alvaro Ardila Perez, now at Facebook
- SM Azizul Hakim, now at Array of Engineers
- Muttaki Islam Bismoy, now doing PhD, University of Michigan
- Aliah Lloyd, now at Gartner
- Nazmus Sakib, now at Stenger and Stenger
- Grant Alphenaar
- Mohammad Shafiq, now at Supported Intelligence
- Fahim Morshed, now at OWL Computing Development
- Malek Garrach, now applying to PhD
- Minh Tran, AI Engineer at VinSmart
Masters Thesis
- Grant Alphenaar : Predicting Course Performance on a Massive Open Online Course Platform: A Natural Language Processing Approach, Advisor
- Muttaki Bismoy: Early Detection of Oak Wilt using Unmanned Aerial Vehicles (UAV) and Computer Vision, Advisor
- Mohammad Shafiqul Islam: Cyberbullying Defensive Strategy in Social Media Sessions via Machine Learning and Cyber Deception, committee member
- SM Azizul Hakim: Structuring Software Test Requirements wih NLP, Advisor
- Malek Garrach: Distilled Intelligence at the Edge: An IoT-Driven Deep Learning Architecture for Plant Health Assessment
Previous Projects
GoFundMe Analysis: This project involves the following. First, collect GFM data for future analysis. Second, use NLP and ML techniques to predict the category of a fundraiser (emergency, community, education) based on the description of the fundraiser. Three, understand how the fundraiser behavior is different across different categories. Fourth, can we predict the success probability of a given fundraiser given the initial donation time series of the samaritans.
HITL-NLP Powered approach to visualize Gene Pathway Research: Collaboration with Dr. Guenter Tusch to develop an nteractive dashboard for research into gene pathways.
YouBrush: Low-latency, low-friction, and responsive mobile application to improve oral care regimens in users.
BullyAlert: an Adaptive Cyberbullying Detection Mobile Application for Parents
LGTBQA+ Cyberbullying: In this project, we are using Data Mining, Machine Learning , Natural Language Processing and Community finding techniquesto understand how cyberbullying languages directed to LGBTQA+ communities evolved through the years across online communities in Twitter.
Rate My Professors Analysis: We are interested in predicting the quality of a professor using the reviews and other metadata collected from RMP.
NLP for software test generation: Collaboration Array of Engineers to develop a system that can generate safety critical software tests from requirements.