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Friday, April 14, 2023 - 11:30 am
550 Assembly St, Room 2277
Graduate students will be selected by their advisor to present a research poster. Monetary awards will be given to the top 3 posters.
Agenda
Time | Location | Event |
---|---|---|
11:30 am – 12:45 pm | Room 2277 (If no seating is available in room 2277, please visit rooms 2265, 2267 and 2268) |
Networking and refreshments |
12:45 pm – 2:00 pm | 2nd floor hallway | Graduate student poster session |
2:00 pm – 2:15 pm | Break | |
2:15 pm – 4:00 pm | Room 1400 (1st floor) | 7 Minute Madness |
4:00 pm – 4:20 pm | Room 1400 (1st floor) | Closing Notes and Poster Awards |
Poster Session Authors
Poster Number | Advisor Name | Poster Title |
---|---|---|
1 | Amit Sheth | Towards Rare Event Prediction in Manufacturing Domain |
2 | Amit Sheth | Alleviate: Artificial Intelligence Enabled Virtual Assistance for Telehealth: The Mental Health Case |
3 | Amit Sheth | FACTIFY3M - A benchmark for multimodal fact verification with explainability through 5W Question-Answering |
4 | Amit Sheth and Forest Agostinelli | Inductive Logic Programming for Explainable Artificial Intelligence |
5 | Biplav Srivastava | Rating of AI Systems Through a Causal Lens |
6 | Biplav Srivastava | Group Recommendation and a Case Study in Team Formation with ULTRA |
7 | Biplav Srivastava | Planner Performance Improvement using Ontology |
8 | Chin-Tser Huang | Smarkchain: An Amendable and Correctable Blockchain Based on Smart Markers |
9 | Chin-Tser Huang | Investigation of 5G and 4G V2V Communication Channel Performance Under Severe Weather |
10 | Christian O'Reilly | Deep Ensemble Learning: A Synergistic Approach for Ultrasonic Vocalization Analysis in Post-Traumatic Stress Disorder Study |
11 | Christian O'Reilly | Characteristics of cerebrospinal fluid in Autism Spectrum Disorder (ASD): A systematic review |
12 | Christian O'Reilly and Amit Sheth | Interpretable Machine Learning for Predicting the Likelihood of Autism from Infant ECG Recordings |
13 | Forest Agostinelli | Explainable AI for Solving Pathfinding Problems through Collaborative Education |
14 | Ioannis Rekleitis | SM/VIO: Robust Underwater State Estimation Switching Between Model-based and Visual Inertial Odometry |
15 | Ioannis Rekleitis | Confined Water Body Coverage under Resource Constraints |
16 | Ioannis Rekleitis | Weakly Supervised Caveline Detection For AUV Navigation Inside Underwater Caves |
17 | Jianjun Hu | crystalTransformer |
18 | Jianjun Hu | Composition based Oxidation State Prediction of Materials using Deep Learning Language Model |
19 | Jianjun Hu | DeepXRD, a Deep Learning Model for Predicting XRD spectrum from Material Composition |
20 | Jianjun Hu | Scalable deeper graph neural networks for high-performance materials property prediction |
21 | Pooyan Jamshidi | Partitioning and Mapping for ASIC AI Accelerators |
22 | Pooyan Jamshidi | Not Just a Rose by Any Other Name: Differential Privacy as an Instrumentality of Effective Regulation Thwarting the Subterfuge of Differential Privacy by another Name and Undue Influence |
23 | Qi Zhang, Christopher Sutton | Maximizing Learning Efficiency in Material Science through Domain Adaptation |
24 | Ramtin Zand | Reliability-Aware Deployment of DNNs on In-Memory Analog Computing Architectures |
25 | Sanjib Sur | MatGAN: Sleep Posture Imaging using Millimeter-Wave Devices |
26 | Sanjib Sur | Towards Robust Pedestrian Detection with Roadside Millimeter-Wave Infrastructure |
27 | Sanjib Sur | Outdoor Millimeter-Wave Picocell Placement using Drone-based Surveying and Machine Learning |
28 | Sanjib Sur | Outdoor Small Scale Point Cloud Reconstruction Using Drone-based Millimeter-Wave FMCW Radar System and CFAR |
29 | Sanjib Sur | MmSight: Millimeter-Wave Imaging on 5G Handheld Smart Devices |
30 | Sanjib Sur | Enabling Integrated Networking and Activity Sensing in Indoor Millimeter-Wave Networks |
31 | Sanjib Sur | mmWaveNet: Indoor Point Cloud Generation from Millimeter-Wave Devices |
32 | Sanjib Sur, Srihari Nelakuditi | SSCense: A Millimeter-Wave Sensing Approach for Estimating Soluble Sugar Content of Fruits |
33 | Song Wang | Few-shot 3D Point Cloud Semantic Segmentation via Stratified Class-specific Attention Based Transformer Network |
34 | Song Wang | Parametric Surface Constrained Upsampler Network for Point Cloud |
35 | Song Wang | MISF: Multi-level Interactive Siamese Filtering for High-Fidelity Image Inpainting |
36 | Stephen Fenner | Implementing the fanout operations with simple pairwise interactions |
37 | Homayoun Valafar | "Revolutionizing Cardiovascular Health: Harnessing the Power of Deep Learning for Automatic Calcification Calculation in Vascular Systems" |
38 | Homayoun Valafar | Smartwatch-Based Smoking Detection Using Accelerometer Data and Neural Networks |
39 | Homayoun Valafar | Analysis of cancer patients’ molecular and clinical data using Machine Learning approaches |
40 | Vignesh Narayanan | On Safe and Usable Chatbots for Promoting Voter Participation |
41 | Vignesh Narayanan | Building a Digital Twin for Information Environment |
42 | Yan Tong | Unlocking the Potential of Consumer Wearables for Predicting Sleep in Children: A Device-Agnostic Machine Learning Approach |
43 | Yan Tong | Cascade Feature Fusion Network for Facial Expression Recognition |
44 | Ramtin Zand | Facial Expression Recognition at the edge: CPU vs GPU vs VPU vs TPU |
45 | Ramtin Zand | Static American Sign Language Recognition Using Neuromorphic Hardware |
7 Minute Madness
Number | Time slot | Speaker |
1 | 2:15 – 2:22 | Ramtin Zand |
2 | 2:30 - 2:37 | Pooyan Jamshidi |
3 | 2:40 – 2:47 | Sanjib Sur |
4 | 2:50 – 2:57 | Forest Agostinelli |
5 | 3:00 – 3:07 | Vignesh Narayanan |
6 | 3:10 – 3:17 | Ioannis Rekleitis |
7 | 3:20 – 3:27 | Song Wong (presented by Ping Ping cai) |
8 | 3:30 – 3:37 | Christian O’Reilly |
9 | 3:40 – 3:47 | Biplav Srivastava |
10 | 3:50 – 3:57 | Jianjun Hu |
11 | 4:00 – 4:07 | Yan Tong |
12 | 4:10 – 4:17 | Steve Fenner |
13 | 4:20 – 4:27 | Homayoun Valafar |
Closing Notes and Poster Awards
4:30 – 4:45 Dr. Homayoun Valafar