Recent News from Carlo Pinciroli
Carlo Pinciroli had two papers accepted at the 2019 IEEE International Conference on Robotics and Automation.
Jayam Patel, Xu Yicong, Carlo Pinciroli. Mixed-Granularity Human-Swarm Interaction. 2019 IEEE International Conference on Robotics Automation (ICRA2019).
Luca Carlone, Carlo Pinciroli. General Robot Co-design: Beyond the Monotone Case. 2019 IEEE International Conference on Robotics Automation (ICRA2019).
Updates from Solovey
Erin Solovey was recently appointed as Deputy Editor for the International Journal of Human-Computer Studies (IJHCS), after serving on the editorial board for five years.
She has received $1 million from the National Science Foundation to use computer science and neuroscience tools to study online learning. She is part of a group of researchers using brain imaging to improve personalized learning environments.
Her research was highlighted on the 6pm Worcester 3 news.
She was awarded WPI-UML seed grant for a collaborative project "Towards Biometric Input for Multi-Agent Adaptive Human-Robot Collaboration" with Rodica Neamtu and Yanhua Li at WPI as well as Holly Yanco, Adam Norton, PeiChun Kao and Winnie Wu from UMass Lowell
She spoke on a panel on Academic Careers at the Scientista Symposium for Women in STEM in Boston.
She gave an invited talk on "Improving Human-Computer Interaction with Real-time Brain Input" at UMass Interdisciplinary Neuroscience Conference
She is giving a keynote talk at Neuroadaptive Technology Conference in Liverpool, England in July.
NSF highlighted her recent grant in this episode of NSF360
WBZ4 CBS News profiled her research: 'Thinking Cap' Study Could Improve Online Learning
J. Dubey, M. Sumaria, E. Oktay, Y. Li, Z. Li, R. Neamtu, E. T. Solovey (2019). Towards neuroadaptive technology using time warped distances for similarity exploration of brain data. In Proc. of Neuroadaptive Technology Conference (NAT 2019), Liverpool UK.
A. Girouard, O. Shaer, E.T. Solovey, M. Poor, R.J.K. Jacob. (2019). The Reality of Reality-Based Interaction: Understanding the Impact of a Framework as a Research Tool. ACM Transactions on Computer-Human Interaction (TOCHI).
R. Liu, A. Sarkar, E.T. Solovey, S. Tschiatschek (2019). Evaluating Rule-based Programming and Reinforcement Learning for Personalizing an Intelligent System. In Proc. of the 2019 on IUI Workshop on Explainable Smart Systems.
Michael Gennert was a panelist on a briefing to the Congressional Budget Caucus on PREPARING THE WORKFORCE FOR AUTOMATION: Examples in the Real World. His presentation focused on Human Machine Teaming from the Perspective of the Human - Strategies for Engaging Students and Communities with Emerging Technology.
He was co-organizer and co-presenter for the 2nd workshop on "The Future of Mechatronic and Robotic Education" in conjunction with the Robotics Summit & Expo in Boston.
H Kimpara, KC Mbanisi, J Fu, Z Li, D Prokhorov, MA Gennert, "Human Model-Based Active Driving System in Vehicular Dynamic Simulation", IEEE Transactions on Intelligent Transportation Systems, April, 2019.
Rodica Neamtu received Schloss Dagstuhl NSF Support Grant for attending the invitational-only Dagstuhl Seminar on Data Series Management, Dagstuhl, Germany, July 2019.
She received a WIN IMPACT Grant for Fostering Collaboration in Teaching, Research and Entrepreneurship among Faculty, Students and Alumnae.
She was part of of WPI and UMass Lowell faculty to receive a seed grant "Towards Biometric Input for Multi-Agent Adaptive Human-Robot Collaboration" collaboratively with Erin Solovey, Yanhua Lee, Pei-Chun Kao, Adam Norton, Yi-Ning Wu, Holly Yanco.
Rodica Neamtu, Andre Camara, Carlos Pereira, Rafael Ferreira "Using Artificial Intelligence for Augmentative Alternative Communication for Children with Disabilities". In International Conference on Human Computer Interaction (INTERCT2019), September 2-6, 2019, Paphos Cyprus.
Jayesh Dubey, Mihin Sumaria, Erden Oktay, Yu Li, Ziheng Li, Rodica Neamtu, Erin T. Solovey "Towards neuroadaptive technology using time warped distances for similarity exploration of brain data". In Neuroadaptive Technology Conference (NAT 2019), July 16-18, 2019, Liverpool UK.
A paper from the group of Yanhua Li group won the Best Applied Data Science Paper Award in SIAM conference on Data Mining, SDM 2019. It selected from 397 submissions and 90 accepted papers this year.
Menghai Pan, Yanhua Li, Xun Zhou, Zhenming Liu, Rui Song, Hui Lu, Jun Luo, Dissecting the Learning Curve of Taxi Drivers: A Data-Driven Approach, SIAM International Conference on Data Mining (SDM19), Hyatt Regency Calgary | Calgary, Alberta, Canada, May 2 - 4, 2019. (90/397=22.7% Acceptance Ratio)
He serves on the program committees for ICDM 2019, CIKM 2019, and SIGSPATIAL GIS 2019.
He had one paper accepted at IEEE Transactions on Knowledge and Data Engineering.
Tianfu He, Jie Bao, Sijie Ruan, Ruiyuan Li, Yanhua Li, Hui He, Yu Zheng, Interactive Bike Lane Planning using Sharing Bikes' Trajectories, IEEE Transactions on Knowledge and Data Engineering (TKDE), Accepted for publication, 2019.
Students from the SCREAM (Superelastic Continuum Robot for Endoscopic Manipulation and Articulation) MQP team advised by Loris Fichera presented their work at the 2019 Design of Medical Devices Conference in Minneapolis, MN. Their paper was nominated as "one of the top ten papers that describe medical devices with potential for commercialization" out of more than 150 submissions. In May, the team was awarded the RBE Director's MQP award. Team members are: Kevin O'Brien (CS), Zach Boyer (ME/RBE), Ben Mart (ME/BME), Cory Brolliar (RBE).
He Fichera was the recipient of the 2019 Rho Beta Epsilon award for excellence in robotics education. Rho Beta Epsilon is the Robotics Engineering Honor Society at WPI.
He was invited to give a grand rounds seminar at Massachusetts Ear and Eye Infirmary. The title of the talk was "Combining robotics and AI to enable advanced treatment modalities in the head and neck."
Smith Presents Paper
Therese Smith gave a paper (On the nature of intelligence in Artificial Intelligence) by Smith, Telliel, Benasutti at the International Society for the Study of Information 2019 Summit in Berkeley, California.
Recent publications from Kyumin Lee:
T. Tran, R. Sweeney, and K. Lee. Adversarial Mahalanobis Distance-based Attentive Song Recommender for Automatic Playlist Continuation. SIGIR 2019.
N. Vo, and K. Lee. Learning from Fact-checkers: Analysis and Generation of Fact-checking Language. SIGIR 2019.
T. Tran, X. Liu, K. Lee, and X. Kong. Signed Distance-based Deep Memory Recommender. WWW, 2019.
Shue Accepted Papers and Cybersecurity Scholarships
Craig Shue received a few recent paper acceptances:
Robert J. Walls, Nicholas F. Brown, Thomas Le Baron, Craig A. Shue, Hamed Okhravi, Bryan Ward, "Control-Flow Integrity for Real-Time Embedded Systems," Euromicro Conference on Real-Time Systems (ECRTS), 2019.
Yunsen Lei, Craig A. Shue, "Detecting Root-Level Endpoint Sensor Compromises with Correlated Activity," Conference on Security and Privacy in Communication Networks (SecureComm), 2019.
Yu Liu, Matthew R. Squires, Curtis R. Taylor, Robert J. Walls, Craig A. Shue, "Account Lockouts: Characterizing and Preventing Account Denial-of-Service Attacks," Conference on Security and Privacy in Communication Networks (SecureComm), 2019.
The cybersecurity Scholarship For Service program issued scholarships to three WPI undergraduates, two of whom are in CS.
Carolina Ruiz, together with Prof. Kristin Wobbe (Associate Dean of Undergraduate Studies and Co-Director of the WPI Center for Project-Based Learning), delivered a two-day workshop entitled "Project-Based Learning: Impacts and Implementation" for 40 faculty members at the Vellore Institute of Technology. Vellore, India.
M. Sokolovsky, F. Guerrero, S. Paisarnsrisomsuk, C. Ruiz, S.A. Alvarez. "Deep Learning for Automated Feature Discovery and Classification of Sleep Stages". IEEE/ACM Transactions on Computational Biology and Bioinformatics. Accepted. 2019.
E.F. Ryder, C. Ruiz, S. Weaver and R.J. Gegear. "Choosing your own adventure: Engaging the new learning society through integrative curriculum design". Learning International Networks Consortium Conference (LINC) 2019. MIT, Cambridge, MA. June 2019.
E.F. Ryder, C. Ruiz, S. Weaver and R.J. Gegear. "The Bio-CS Bridge: A Transdisciplinary Team Approach to Integrating Biology and Computer Science in High School Curricula". Poster. Science of Team Science Conference (SciTS 2019). Lansing, Michigan. May 2019.
In March 2019, WPI hosted the highly coveted "Women In Data Science Symposium (WIDS'2019)" at WPI with around 150 Women from universities, companies and government organizations from all across New England participating. This event was organized by Prof Rundensteiner worked with extremely talented Computer Science and Data Science PhD students, led this year by Dr. Erin Teeple, PhD student in Data Science and working closely with Dr. Ramona Ashan, PhD student in Computer Sciences (who graduated with PhD from WPI in May 2019!), and Allison Rozet, PhD student in Data Science, and Geri Dimas, PhD student in Data Science, and Prof. Emdad, and others. This event was fully sponsored this year by the WPI Women's Impact Network 2019 Grant for "Supporting Women in Data Science via the Women in Data Science Symposium: Fostering Diversity, Community, Mentorship, Outreach, and Global Impact all in one!", 2018-2019.
She was excited to see four of her PhD students walk at the May 2019 WPI Graduation Ceremony to be awarded their doctorate, and is wishing them all the best for their future professional careers as leaders in the Computer Science technology industry.
Dr. Abhishek Mukherji, who attended the graduate ceremony at WPI in May 2019, successfully completed his PhD in Computer Science this academic year 2019. His PhD Dissertation is in the area of "Pattern Mining and Sense Making for Enhancing User Experience Analytics". He focused on strategies for turning pattern and sequence mining into an interactive sense-making experience by scaling up the pattern mining process and by compressing the storage of the resulting patterns to support visual interactive analytics, along with applications of this technology to support on-the-smartphone prediction services for an enhanced sense making experience by phone users. Dr. Mukherji is employed at Raytheon as Senior Engineer. Committee members are Prof. Mohamed Eltabakh, Prof. Emmanuel O. Agu, and Dr. Geetika T. Lakshmanan, Amazon.
Dr. Ramoza Ashan attended the graduation ceremony at wpi in May 2019. Prof. Elke Rundensteiner and Prof. Gabor Sarkozy as co-advisors are pleased that Ramoza Ashan successfully completed her PhD in Computer Science this academic year 2019. Her dissertation research, titled "Efficient Time Series Data Analytics" focused on indexing and processing techniques to support the efficient exploration and analysis of time series data sets with a rich variety of distances. Committee members besides Prof. Elke Rundensteiner and Prof. Gabor Sarkozy include Prof. Xiangnan Kong and Prof. Vassilis Athitsos, University of Texas at Arlington.
Dr. Xiao Qin, who attended the graduation ceremony at wpi in May 2019, successfully completed his PhD in Computer Science this academic year 2019. Prof. Rundensteiner is proud for Xiao Qin to have earned his doctorate. Xiao has started his career as Research Scientist at the IBM Almanden Research Lab in California applying his analytics, modeling and machine learning skills for tackling health applications. His dissertation research, titled "Sequential Data Mining and its Applications to Pharmacovigilance" focuses on exploring, analyzing and modeling various types of sequential data important to analytical challenges in healthcare. His dissertation covers methods from stream mining to deep learning for medical text generation. Committee members are Prof. Mohamed Y. Eltabakh, Worcester Polytechnic Institute. Prof. Xiangnan Kong, Worcester Polytechnic Institute. Prof. Fei Wang, Cornell University.
Dr. Zhongfang Zhuang, who attended the graduation ceremony at wpi in May 2019, successfully completed his PhD in Computer Science this academic year 2019. Prof. Rundensteiner and Prof Kong, who served as co-advisors, are proud of Zhongfang's achievements. His dissertation research, titled "Deep Learning on Attributed Sequences", focuses on designing, building and analyzing deep learning models for four important problems on a new complex data type, called attributed sequences. Zhongfang has accepted a research position in Visa Research. Committee members besides Prof Kong and Rundensteiner include Prof. Mohamed Eltabakh and Prof. Philip Yu.
Prof. Rundensteiner with co-PI Prof. Ngan were awarded a new NSF REU SITE grant entitled DATA SCIENCE RESEARCH FOR HEALTHY COMMUNITIES IN THE DIGITAL AGE. CNS-1852498. 2019 - 2022, $366,000.
Prof. Rundensteiner, Dr. Ramona Ashan, Allison Rozet, Dr. Erin Teeple, Prof. Fatemeh Emdad, were awarded a new grant from the Women's Impact Network 2019 Grant for "Supporting Women in Data Science via the Women in Data Science Symposium: Fostering Diversity, Community, Mentorship, Outreach, and Global Impact all in one!", 2019-2020.
Prof. Rundensteiner was awarded a new NSF supplement of $16,000 for NSF grant III: Small: Scalable Event Trend Analytics For Data Stream Inquiry", $499,753, 2018 - July 2021.
Prof. Rundensteiner and Prof. Fatemeh Emdad, were awarded a grant from ARL in "Data Sciences, AI and Machine Learning for Army Applications" $25,000, 2019 - 2020.
Prof. Rundensteiner and Prof. Fatemeh Emdad, were awarded a grant from PPG Industries and U.S. Department of Defense in "Accelerating R&D Innovation using Transparent and Dynamic Anticipatory Standards", $27,000, 2019 - 2020.
Some recent articles about Prof. Rundensteiner's project "Scalable Event Trend Analytics For Data Stream Inquiry" funded by the NSF on developing next-generation big data analytics tools that help make sense of streaming data in real time appeared, including:
Her work on "next-generation big data analytics tools will make sense of streaming data in real time" was highlighted in venues such as phys.org, eurekaalert.org and prweb.com.
T. Hartvigsen, C. Sen, X. Kong and E. Rundensteiner, Adaptive-Halting Policy Network for Early Classification, ACM KDD 2019. (research track).
Tabassum Kakar, Xiao Qin, Elke A. Rundensteiner, Lane Harrison, Thang La, Sanjay K. Sahoo and Suranjan De, DIVA: Exploration and Validation of Hypothesized Drug-Drug Interactions, EuroVis 2019, Full Paper Track, June 3-7, 2019, Porto, Portugal. (Also to appear in Special issue, Computer Graphics Forum (CGF) journal).
Lei Cao, Yizhou Yan, Sam Madden, Elke Rundensteiner, Efficient Discovery of Sequence Outlier Patterns, PVLDB, Vol 12, Los Angeles, 2019.
Olga Poppe, Chuan Lei, A. Rozet, E. Rundensteiner and D. Maier, Event Trend Aggregation Under Rich Event Matching Semantics. ACM SIGMOD 2019, Amsterdam, 2019.
Zhongfang Zhuang, Xiangnan Kong, Elke Rundensteiner, AMAS: Attention Model for Attributed Sequence Classification, SIAM International Conference on Data Mining (SDM19). Calgary, Canada, May 2-4, 2019.
Jidapa Thadajarassiri, Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, and Elke Rundensteiner, Comparing General and Locally-Learned Word Embeddings for Clinical Text Mining', Full paper, selected also for presentation at the Special Session: Decision-support computing by data-driven and AI-based approaches for healthcare, IEEE International Conference on Biomedical and Health Informatics (BHI'19), Dorin Forum, University of Illinois at Chicago, Chicago, IL, USA, May 19-22, 2019.
ML Tlachac, E. Toto, E. Rundensteiner, You're Making Me Depressed: Leveraging Texts from Contact Subsets to Predict Depression, IEEE International Conference on Biomedical and Health Informatics (BHI'19), Dorin Forum, University of Illinois at Chicago, Chicago, IL, USA, May 19-22, 2019.
Walter Gerych, Emmanuel Agu, and Elke Rundensteiner, Classifying Depression in Imbalanced Datasets using an Autoencoder-Based Anomaly Detection Approach, IEEE International Conference On Semantic Computing (ICSC 2019).
ML Tlachac, E. Rundensteiner, The 10 Most Important Features in Predicting Depression from Content of Retrospectively Harvested Text Messages, IEEE International Conference on Biomedical and Health Informatics (BHI'19), Dorin Forum, University of Illinois at Chicago, Chicago, IL, USA, during May 19-22, 2019. (Extended Abstract)
Bo Wang, Bonita Stanton, E. Rundensteiner, Feifan Liu and Lynette Deveaux, ``Adolescent HIV-related behavioral prediction using machine learning: Building a foundation for precision HIV prevention'', (extended abstract), Roundtable presentation, American Public Health Association Annual Meeting, (APHA'2019 Annual Meeting and Expo (Nov. 2 - Nov. 6), Philadelphia, 2019
Hamid Mansoor, Walter Gerych, Luke Buquicchio, Kavin Chandrasekaran, Elke Rundensteiner, and Emmanuel Agu, COMEX: Identifying Mislabeled Human Behavioral Context Data Using Visual Analytics, 1st IEEE International Workshop on Deep Analysis of Data Driven Applications (DADA 2019), COMPSAC 2019, Milwaukee, Wisconsin, USA.
An archive of previous SIGBITS editions is also available.