News

2023:

  • On February 27th, 2024 DAISY member Kathleen Cachel won 1st place in WPI's 3 Minute Thesis Competition for her work 'Technologies for Fair Consensus Decision-Making.'
  • On December 15th, 2023 the following papers were accepted for publication at SIAM International Conference on Data Mining (SDM 2024).
    • Dongyu Zhang, Ruofan Hu, and Elke Rundensteiner. CoLafier: Collaborative Noisy Label Purifier With LID Guidance.
  • On December 11th, 2023 the following papers were accepted for publication at AAAI 2024.
    • Jidapa Thadajarassiri, Walter Gerych, Xiangnan Kong, and Elke Rundensteiner. Amalgamating Multi-Task Models with Heterogeneous Architectures.
  • On November 30th, 2023 Professor Rundensteiner spoke as a panelist at the presidential event Beyond These Towers: Data Science & AI in Our Lives. Read More.
    • Data science and AI have so much potential for profound impact on the challenges of today and tomorrow, and WPI is at the forefront. A NYC event with WPI President Grace Wang, WPI faculty, alumni, and industry leaders for a reception and panel discussion. Learn more here
  • On November 16th, 2023 Abdulaziz Alajaji, Kavin Chandrasekaran, Luke Buquicchio, Walter Gerych, Emmanuel Agu, and Elke Rundensteiner won the Best Paper award at COMPSAC 2023 for their work titled 'Adversarial Human Context Recognition: Evasion Attacks and Defenses'. Read More
  • On November 1st, 2023 the following papers were accepted for publication at IEEE BigData 2023.
    • Ricardo Flores, Avantika Shrestha, ML Tlachac, and Elke Rundensteiner. DeepScreen: Boosting Depression Screening Performance with an Auxiliary Task. Special Session on Machine Learning on Big Data (MLBD).
    • Ricardo Flores, Avantika Shrestha, and Elke Rundensteiner. Multi-Task Learning Using Facial Features for Mental Health Screening. Special Session on HealthCare Data.
    • Ruofan Hu, Dongyu Zhang, Dandan Tao, Huayi Zhang, Hao Feng, and Elke Rundensteiner. UCE-FID: Using Large Unlabeled, Medium Crowdsourced-Labeled, and Small Expert-Labeled Tweets for Foodborne Illness Detection. Special Session on Machine Learning on Big Data (MLBD).
    • Walter Gerych, Kevin Hickey, Thomas Hartvigsen, Luke Buquicchio, Abdulaziz Alajaji, Kavin Chandrasekaran, Hamid Mansoor, Emmanuel Agu, and Elke Rundensteiner. Stabilizing Adversarial Training for Generative Networks. Special Session on Machine Learning on Big Data (MLBD).
  • On October 3rd, 2023, Walter Gerych successfully passed his PhD Dissertation Defense "Working With What You've Got: Leveraging Mislabeled Datasets And Improving Imperfect Pretrained Models". Congratulations Dr. Gerych! Thank you to Walter's dissertation committee members Prof. Elke Rundensteiner (WPI, Advisor), Prof. Emmanuel Agu (WPI, Co-Advisor), Prof. Oren Mangoubi (WPI), and Dr. Adam Kalai (Microsoft Research).
  • On September 26th, 2023, Ricardo Flores successfully passed his PhD Dissertation Defense "Multi-modal Models for Depression Screening". Congratulations to Dr. Flores on achieving this important milestone. Many thanks to his dissertation committee members Prof. Elke Rundensteiner (WPI, Advisor), Prof. Xiaozhong Liu (WPI), Prof. Nima Kordzadeh (WPI), and Prof. Farah Shamout (NYU-Abu Dhabi).
  • On October 1st, 2023 the following papers were accepted for publication at ICMLA Special Session on Machine Learning for Predictive Models in Engineering Applications (MLPMEA) 2023.
    • Biao Yin, Yangyang Fan, Nicholas Josselyn, and Elke Rundensteiner. AlloyGAN: Domain-Promptable Generative Adversarial Network for Generating Aluminum Alloy Microstructures.
    • Biao Yin, Nicholas Josselyn, Thomas Considine, John Kelley, Berend Rinderspacher, Robert Jensen, James Snyder, Ziming Zhang, and Elke Rundensteiner. DeepSC-Edge: Scientific Corrosion Segmentation with Edge-Guided and Class-Balanced Losses.
  • On September 21st, 2023 the following papers were accepted for publication at NeurIPS 2023.
    • Walter Gerych, Kevin Hickey, Luke Buquicchio, Kavin Chandrasekaran, Abdulaziz Alajaji, Elke Rundensteiner, and Emmanuel Agu. Debiasing Pretrained Generative Models by Uniformly Sampling Semantic Attributes.
  • On September 15th, 2023 the following papers were accepted for publication at IEEE the MIT Undergraduate Research Technology Conference (URTC) 2023.
    • Nikola Grozdani, America Muñoz, Alexander Pietrick, Ricardo Flores, Avantika Shrestha, Xingtong Guo, Shichao Liu and Elke Rundensteiner. Wearable Wellness: Depression Screening via Fitbit Data Collected During COVID-19 Pandemic. (REU Project Paper)
  • On August 23rd, 2023 the following papers were accepted for publication at ACM SIGMOD 2023.
    • Peter M. VanNostrand, Huayi Zhang, Dennis Hofmann, and Elke Rundensteiner. FACET: Robust Counterfactual Explanation Analytics.
  • On August 7th, 2023 the following papers were accepted for publication at ACM CIKM 2023.
    • Kathleen Cachel and Elke Rundensteiner. Fair&Share: Fast and Fair Multi-Criteria Selections, Full Paper.
    • Biao Yin, Nicholas Josselyn, Ziming Zhang, Elke Rundensteiner, Thomas Considine, John Kelley, Berend Rinderspacher, Robert Jensen, and James Snyder. MOSS: AI Platform for Discovery of Corrosion-Resistant Materials, Demonstration Paper.
  • On August 7th, 2023 the following papers were accepted for publication at Journal on Food Engineering and Technology Applications of Artificial Intelligence in Food Industry, MDPI 2023.
    • Dandan Tao, Ruofan Hu, Dongyu Zhang, Jasmine Laber, Anne Lapsley, Timothy Kwan, Liam Rathke, Elke Rundensteiner, Hao Feng. A Novel Foodborne Illness Detection and Web Application Tool Based on Social Media
  • On April 18th, 2023, Dr. Jidapa Thadajarassiri successfully passed her PhD Dissertation Defense "Knowledge Amalgamation from Heterogeneous Pre-Trained Models". Congratulations to Jida on achieving this important milestone. Many thanks to her dissertation committee members Prof. Elke Rundensteiner (WPI, Advisor), Prof. Xiangnan Kong (WPI, co-advisor), Prof. Jian Zou (WPI), and Prof. Supasorn Suwajanakorn (VISTEC Thailand).
  • On April 17th, 2023 Professor Rundensteiner spoke with the Worcester Business Journal about the power and risks of using AI in healthcare applications. Read More
  • On April 4th, 2023 DAISY students Ricardo Flores won 2nd place in Data Science for GRIE 2023 with Yao Su, Joshua DeOliveira, and Peter VanNostrand tied for 3rd place.
  • On April 7th, 2022 the following papers were accepted for publication at FAccT 2023.
    • Kathleen Cachel and Elke Rundensteiner. Fairer Together: Mitigating Disparate Exposure in Kemeny Rank Aggregation.
    • Hilson Shresta, Kathleen Cachel, Mallak Alkhathlan, Elke Rundensteiner and Lane Harrison. Help or Hinder? Evaluating the Impact of Fairness Metrics and Algorithms in Visualizations for Consensus Ranking.
  • On February 8th DAISY students Joshua DeOliveira, Ricardo Fores, Nicholas Josselyn, and Peter VanNostrand won round one of GRIE 2023. Winners will move to final round on April 4th.

2022:

  • On December 5th 2022, Dr. Xika Lin successfully passed her PhD Dissertation Defense "Frequent Pattern Mining Analytics". Congratulations to Xika on achieving this important milestone. Many thanks to her dissertation committee members Prof. Elke Rundensteiner (WPI, Advisor), Prof. Mohamed Y. Eltabakh (WPI), Prof. Xiangnan Kong (WPI), and Prof. Cindy Chen (UMASS Lowell).
  • On November 21st, 2022 the following papers were accepted for publication at AAAI 2023.
    • Jida Thadajarassiri, Tom Hartvigsen, Walter Gerych, Xiangnan Kong and Elke Rundensteiner. Knowledge Amalgamation for Multi-Label Classification via Label Dependency Transfer.
  • On November 16th 2022, DAISY member Oluseun Olulana received the prestigious American Association of University Women's International Doctoral Degree Fellowship. Congratulations Olu! Read More
  • On November 15th, 2022 the following papers were accepted for publication at VLDB 2022.
    • Liang Zhang, Noura Alghamdi, Huayi Zhang, Mohamed Y. Eltabakh, and Elke A. Rundensteiner. PARROT: Pattern-Based Correlation Exploitation in Big Partitioned Data Series.
  • On November 7th, 2022 the following papers were accepted for publication at the 2022 IEEE International Conference on Big Data.
    • ML Tlachac, Walter Gerych, Kratika Agrawal, Benjamin Litterer, Nicholas Jurovich, Saitheeraj Thatigotla, Jidapa Thadajarassiri, and Elke Rundensteiner. Text Generation to Aid Depression Detection: A Comparative Study of Conditional Sequence Generative Adversarial Networks. Workshop on Big Data Analytics in Healthcare.
    • Nicholas Josselyn, Biao Yin, Ziming Zhang, and Elke Rundensteiner. An Empirical Study of Domain Adaptation: Are We Really Learning Transferable Representations? Special session on Machine Learning on Big Data (MLBD2022).
    • Joshua DeOliveira, Walter Gerych, Aruzhan Koshkarova, Elke Rundensteiner, and Emmanuel Agu. HAR-CTGAN: A Mobile Sensor Data Generation Tool for Human Activity Recognition. 5th Special Session on HealthCare Data.
  • On October 10th, 2022 the following papers were accepted for publication at the 21st IEEE International Conference on Machine Learning and Applications, 2022.
    • Nicholas Josselyn, Biao Yin, Thomas Considine, John Kelley, Berend Rinderspacher, Robert Jensen, James Snyder, Ziming Zhang, and Elke Rundensteiner. Transferring indoor corrosion image assessment models to outdoor images via domain adaptation.
  • On September 9th, 2022 the following papers were accepted for publication at the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) 2022.
    • Avantika Shrestha, ML Tlachac, Ricardo Flores, Elke Rundensteiner. BERT Variants for Depression Screening with Typed and Transcribed Responses. Computing for Well-being (WellComp) Workshop
    • Ricardo Flores, ML Tlachac, Avantika Shrestha, Elke Rundensteiner. AudiFace: Multimodal Deep Learning For Depression Screening, Temporal Facial Features for Depression Screening. Mental Health: Sensing and Intervention (MHSI) workshop
  • On September 2nd, 2022 the following paper was accepted for publication at the IEEE Conference on Data Mining (ICDM) 2022.
    • Ramesh Doddaiah, Prathyush Parvatharaju, Elke Rundensteiner, and Thomas Hartvigsen.Class-Specific Explainability for Deep Time Series Classifiers.
  • On August 22nd, 2022 the following paper was accepted for publication at the IEEE Journal of Biomedical and Health Informatics 2022.
    • ML Tlachac, Avantika Shrestha, Mahum Shah, Benjamin Litterer, and Elke A. Rundensteiner. Automated Construction of Lexicons to Improve Depression Screening with Text Messages.
  • On August 22nd, 2022 the following paper was accepted for publication at ACM SIGMOD 2022.
    • Lei Cao, Yizhou Yan, Samuel Madden, and Elke Rundensteiner. AutoOD: Automatic Outlier Detection.
  • On August 10th 2022, Dr. Noura Alghamdi successfully passed her PhD Dissertation Defense "Big Time Series Analytics Using a Distributed Infrastructure". Congratulations to Noura on achieving this important milestone. Many thanks to her dissertation committee members Prof. Elke Rundensteiner (WPI, Advisor), Prof. Mohamed Eltabakh (WPI), Prof. George Heineman (WPI), and Prof. Mirek Riedewald (Northeastern Univeristy).
  • On August 4th the following papers were accepted for publication at ACM CIKM'2022.
    • Walter Gerych, Thomas Hartvigsen, Luke Buquicchio, Emmanuel Agu and Elke Rundensteiner. Robust Recurrent Classifier Chains For Multi-Label Learning With Missing Labels.
    • Thomas Hartvigsen, Walter Gerych, Jidapa Thadajarassiri, Xiangnan Kong and Elke Rundensteiner. Stop&Hop: Early Classification of Irregular Time Series.
  • On August 4th the following papers were accepted for publication at Healthcare Analytics, Elsevier Publisher, 2022.
    • ML Tlachac, Miranda Reisch, Brittany Lewis, Ricardo Flores, Lane Harrison, and Elke Rundensteiner. Impact Assessment of Stereotype Threat on Mobile Depression Screening using Bayesian Estimation.
  • On August 4th the following papers were accepted for publication at Machine Learning for Healthcare (MLHC), 2022.
    • Ricardo Flores, ML Tlachac, Ermal Toto, Elke Rundensteiner. AudiFace: Multimodal Deep Learning For Depression Screening.
  • On July 15th the following short papers were accepted for publication at ASSETS'2022.
    • Mallak Alkhathlan, ML Tlachac, Lane Harrison, and Elke Rundensteiner. Improving Image Accessibility by Combining Haptic and Auditory Feedback.
  • On July 7th the following short papers were accepted for publication at the ACM International Conference on Information Technology for Social Good (GoodIT 2022).
    • Ricardo Flores, ML Tlachac and Elke A. Rundensteiner. Measuring the Uncertainty of Environmental Good Preferences with Bayesian Deep Learning
  • On June 16th the following short papers were accepted for publication at IEEE VIS, 2022.
    • Hilson Shrestha, Kathleen Cachel, Mallak Alkhathlan, Elke A Rundensteiner and Lane Harrison. FairFuse: Interactive Visual Support for Fair Consensus Ranking.
  • On May 27th the following papers were accepted for publication at VLDB 2022.
    • Dennis Hofmann, Peter VanNostrand, Huayi Zhang, Yizhou Yan, Lei Cao, Samuel Madden, and Elke Rundensteiner. A Demonstration of AutoOD: A Self-Tuning Anomaly Detection.
  • On May 18th the following papers were accepted for publication in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.
    • ML Tlachac, Ricardo Flores, Miranda Reisch, Katie Housekeeper, Elke Rundensteiner. DepreST-CAT: Retrospective Smartphone Call and Text Logs Collected During the COVID-19 Pandemic to Screen for Mental Illnesses.
    • ML Tlachac, Ricardo Flores, Miranda Reisch, Rimsha Kayastha, Nina Taurich, Veronica Melican, Connor Bruneau, Hunter Caouette, Joshua Lovering, Ermal Toto, Elke Rundensteiner. StudentSADD: Rapid Mobile Depression and Suicidal Ideation Screening of College Students during the Coronavirus Pandemic.
  • On May 16th the following works for accepted for publication as chapters in Deep Learning Applications, Vol. 4. Springer Verlag, 2022.
    • Ricardo Flores, ML Tlachac, Ermal Toto, Elke A. Rundensteiner. Transfer Learning for Depression Screening from Follow-up Clinical Interview Questions.
    • ML Tlachac, Ricardo Flores, Ermal Toto, Elke A. Rundensteiner. Early Mental Health Uncovering with Short Scripted and Unscripted Voice Recordings.
  • On April 28th 2022, Walter Gerych successfully passed his PhD Dissertation Proposal "Deep Learning Methods To Improve Real-World Data Quality". Congratulations to Walter on achieving this important milestone. His dissertation committee members are Prof. Elke Rundensteiner (WPI, Advisor), Prof. Emmanuel Agu (WPI), Prof. Oren Mangoubi (WPI), and Dr. Adam Kalai (Microsoft Research).
  • On April 26th 2022, WPI featured DAISY members' research into AI screen for depression on voice recordings in their article Researchers Develop Novel Technology to Screen Voice Recordings for Depression.
  • On April 20th the following papers were accepted for publication at the AAAI ACM Conference on Artificial Intelligence, Ethics, and Society (AIES-2022).
    • Kathleen Cachel and Elke Rundensteiner. FINS Auditing Framework: Group Fairness for Subset Selections.
  • On April 4th the following papers were accepted for publication at the 2022 Proceedings of the 13th Language Resources and Evaluation Conference.
    • Ruofan Hu, Dongyu Zhang, Dandan Tao, Thomas Hartvigsen, Hao Feng and Elke Rundensteiner. TWEET-FID: An Annotated Dataset for Multiple Foodborne Illness Detection Tasks.
  • On April 1st the following papers were accepted for publication at EMBC 2022.
    • Saskia Senn, ML Tlachac, R. Flores, E. Rundensteiner. Ensembles of BERT for Depression Classification.
  • On March 2nd DAISY members Walter Gerych, Kevin Hickey, and Jadipa Thadajarassiri were selected from more than 150 Master's and PhD students to advance to the finals of WPI's Graduate Research Innovation Exchange.
  • On March 8th 2022 the following papers were accepted for publication at ACM SIGMOD 2022
    • Lei Ma, Chuan Lei, Olga Poppe, and Elke Rundensteiner. Gloria: Graph-based Sharing Optimizer for Event Trend Aggregation.
  • On February 17th 2022, DAISY member Walter Gerych was invited to present his work in an oral presentation at AAAI 2022

2021:

  • On December 20th, 2021 the following papers were accepted for publication at SDM 2022.
    • Walter Gerych, Thomas Hartvigsen, Luke Buquicchio, Abdulaziz Alajaji, Kavin Chandrasekaran, Hamid Mansoor, Elke Rundensteiner, Emmanuel Agu. Positive Unlabeled Learning with a Sequential Selection Bias.
  • On December 14th, 2021 the following papers were accepted for publication at ACM SIGMOD 2022.
    • Noura Alghamdi, Liang Zhang, Elke A. Rundensteiner, and Mohamed Y. Eltabakh. Scalable Time Series Compound Infrastructure
  • On December 1st, 2021 DAISY member Tom Hartvigsen successfully completed his PhD dissertation defense, congratulations Dr. Hartvigsen! Tom has accepted a postdoctoral position at MIT for Spring 2022 after which he plans to conduct a search for a tenure-track faculty position.
  • On December 1st, 2021 the following papers were accepted for publication at AAAI 2022.
    • Walter Gerych, Thomas Hartvigsen, Luke Buquicchio, Emmanuel Agu, and Elke Rundensteiner. Recovering the Propensity Score from Biased Positive Unlabeled Data.
  • On November 29th, 2021 the following papers were accepted for publication at IEEE International Conference on Data Engineering 2022 (ICDE).
    • Kathleen Cachel, Elke Rundensteiner, and Lane Harrison. MANI-Rank: Multiple Attribute and Intersectional Group Fairness for Consensus Ranking.
  • On November 22nd, 2021 the following papers were accepted for publication at the International Joint Conference on Computer Vision, Imaging and Computer Graphics.
    • Tabassum Kakar, Xiao Qin, Suranjan De, Sanjay Sahoo, Thang La, Elke Rundensteiner, and Lane Harrison. ConText: Supporting the Pursuit and Management of Evidence in Text-based Reporting Systems.
  • On November 10th, 2021 the following papers were accepted for publication at Scientific Reports 11 (Sci Reports 2021).
    • Dandan Tao, Dongyu Zhang, Ruofan Hu, Elke Rundensteiner, and Hao Feng. Crowdsourcing and Machine Learning Approaches for Extracting Entities Indicating Potential Foodborne Outbreaks from Social Media.
  • On November 8th, 2021 the following papers were accepted for publication at the 2021 IEEE International Conference on Big Data.
    • Walter Gerych, Harrison Kim, Joshua DeOliveira, MaryClare Martin, Luke Buquicchio, Kavin Chandrasekaran, Abdulaziz Alajaji, Hamid Mansoor, Emmanuel Agu, and Elke Rundensteiner. GAN For Generating User-Specific Human Activity Data From An Incomplete Training Corpus, 4th Special Session on HealthCare Data.
    • Dongyu Zhang, Cansu Sen, Jidapa Thadajarassiri, Thomas Hartvigsen, Xiangnan Kong, and Elke Rundensteiner. Human-like Explanation for Text Classification with Limited Attention Supervision.
    • Luke Buquicchio, Walter Gerych, Kavin Chandrasekaran, Abdulaziz Alajaji, Hamid Mansoor, Thomas Hartvigsen, Elke Rundensteiner, and Emmanuel Agu. Variational Open Set Recognition.
    • Maryam Hasan, Elke Rundensteiner, and Emmanuel Agu. DeepEmotex: Classifying Emotion in Text Messages using Deep Transfer Learning, Special Session: Machine Learning on Big Data.
  • On November 2nd, Ermal Toto and ML Tlachac were awarded the final winner of the Best Applied Research Paper at CIKM 2021 for their collaborative work AudiBERT: A Deep Transfer Learning Multimodal Classification Framework for Depression Screening. See the announcement here.
  • On October 15th, 2021 the following papers were accepted for publication at the British Machine Vision Conference (BMVC 2021).
    • Biao Yin, Nicholas Josselyn, Thomas Considine, John Kelley, Berend Rinderspacher, Robert Jensen, James Snyder, Ziming Zhang, and Elke Rundensteiner. Corrosion Image Data Set for Automating Scientific Assessment of Materials.
  • On September 28th, 2021 the following paper was accepted for publication at the NeurIPS 2021.
    • Walter Gerych, Tom Hartvigsen, Luke Buquicchio, Emmanuel Agu, and Elke Rundensteiner. Recurrent Bayesian Classifier Chains for Exact Multi-Label Classification.
  • On September 21st, 2021 the following papers were accepted for publication at 20th IEEE International Conference on Machine Learning and Applications (ICMLA 2021).
    • Ricardo Flores, ML Tlachac, Ermal Toto, and Elke Rundensteiner. Depression Screening Using Deep Learning on Follow-up Questions in Clinical Interviews.
    • Luke Buquicchio, Walter Gerych, Abdulaziz Alajaji, Kavin Chandrasekaran, Hamid Mansoor, Emmanuel Agu, and Elke Rundensteiner. Few-Shot Classification for Human Context Recognition Using Smartphone Data Traces.
    • Walter Gerych, Jessica Bader, Declan Nelson, Thalia Chai-Zhang, Luke Buquicchio, Abdulaziz Alajaji, Kevin Chandrasekaran, Emmanuel Agu, Elke Rundensteiner. Local Geometry Preserving Deep Networks For Featurizing High-Dimensional Datasets.
  • On August 10th, 2021 the following papers were accepted for publication at CIKM 2021.
    • Prathyush S Parvatharaju, Ramesh Doddaiah, Thomas W Hartvigsen and Elke A Rundensteiner. Learning Saliency Maps to Explain Deep Time Series Classifiers.
    • Ermal Toto, ML Tlachac, Elke Rundensteiner. AudiBERT: A Deep Transfer Learning Multimodal Classification Framework for Depression Screening.
  • On June 16th, 2021 the following papers were accepted for publication at VLDB 2021.
    • Huayi Zhang, Lei Cao, Samuel Madden, Elke Rundensteiner. LANCET: Labeling Complex Data at Scale.
  • On June 7th, 2021 the following papers were accepted for publication at the IEEE International Conference on Biomedical and Health Informatics 2021 (BHI'21).
    • ML Tlachac, Katherine Dixon-Gordon, and Elke Rundensteiner. Screening for Suicidal Ideation with Text Messages.
    • ML Tlachac, Veronica R. Melican, Miranda Hernandez-Reisch, and Elke Rundensteiner. Mobile Depression Screening with Time Series of Text Logs and Call Logs.
  • On May 19th, 2021 DAISY PhD graduate Dr. Susmitha Wunnava was featured speaker at WPI's Class of 2021 commencement. Congratulations, Susmitha! A recording of her speech is availible on YouTube. Susmitha now moves on with her career as a Research Fellow at Harvard Medical School pursuing her dream of working in medical analytics.
  • On May 16th, 2021 the following papers were accepted for publication at SIGKDD 2021:
    • Huayi Zhang, Lei Cao, Peter Van Nostrand, Sam Madden, and Elke Rundensteiner. ELITE : Robust Deep Anomaly Detection with Meta Gradient.
  • Professor Elke Rundensteiner is named WILLIAM B. SMITH PROFESSOR!
  • Congrats to DAISY Students win awards in GRIE'2021 ! First Place: Walter Gerych, Second Place: Jidapa Thadajarassiri, Peter VanNostrand

2020:

  • Dr. Tabassum Kakar will join Well as a Data Visualization and Reporting Specialist.
  • Dr. Susmitha Wunnava was awarded a position as "Postdoctoral Research Fellow in the Harvard-MIT Center for Regulatory Science" at Harvard Medical School with research mentor Dr. Timothy Miller, Harvard Medical School. Her role is to develop analytical tools to predict device safety and effectiveness in pre-market and post-market databases. This will allow the FDA to analyze a range of medical device data to identify trends and safety signals, assess device performance across different device types, and analyze data-related processes to inform process improvements for the future.
  • Congratulations to Dr. Cansu Sen on passing her PhD Dissertation Defense this Wednesday, July 15, 2020. Her dissertation research was titled " Attention-based Deep Learning Models for Text Classification and their Interpretability". It focuses on innovative deep learning techniques and systems for natural language processing for the classification and their interpretability of patient outcomes based on series of clinical patient notes. Her research has been widely published in excellent venues ranging from publications in ACL, Big Data, KDD, and other venues. Cansu will be continuing on this line of research tackling challenges around clinical notes using deep learning based architectures as a Data Scientist at Codametrix, a Subsiduary of Partners Healthcare in Boston.
  • Congratulations to soon-to-be Dr. Yizhou Yan on passing her PhD Dissertation Defense this Thursday, May 26, 2020.
    • Her dissertation research, titled "Contextual Outlier Detection from Heterogeneous Data Sources " focuses on innovative efficient techniques and systems for identifying outliers in heterogeneous data types from images, time series, event series to high-dimensional structured data records.
    • Her research has been widely published in top venues ranging from publications in KDD to VLDB and SIGMOD.
    • Yizhou has already accepted a position at Facebook, Boston applying her system and machine learning skills to new problem domains.
  • Congratulations to soon-to-be Dr. Caitlin Kuehlman PhD Dissertation Defense this past Friday, May 15, 2020.
    • Her dissertation research, titled "Ranking for Decision Making: Fairness and Usability" focuses on innovative efficient techniques and systems for AI ranking to support fair decision making.
    • Her research has been widely published in top venues ranging from publications in CHI, WWW, KDD, ECML, CIKM, and other venues.
    • The core piece of her dissertation got accepted into one of the top big data conferences. Caitlin Kuhlman and Elke Rundensteiner, Rank Aggregation Algorithms for Fair Consensus, Proc. VLDB 2020.
    • Caitlin has accepted a position at Apple, California.
  • Congratulation to Allison Rozet for successfully defending her MS thesis today Wednesday May 5, 2020 on the topic of "MUSE - Shared Complex Event Trend Aggregation".
  • Ermal Toto has successfully passed his Ph.D. Comprehensive Exam this Friday, Jan 31, 2020.
    His areas of study covered questions broadly in (1) deep learning for voice analysis, (2) machine learning in psychology, and (3) human computer interface technology for health care. Congratulations to Ermal on having passed this important milestone in his Ph.D. studies.

2019:

  • April 12, 2019. On April 9, more than 75 Master’s, PhD candidates, and Post-Doctoral Fellows shared their innovative and purposeful research with the WPI community at the 2019 Graduate Research Innovation Exchange (GRIE). It was an exciting event that had the Rubin Campus Center Odeum buzzing with activity and engaged conversation. The following students were awarded prizes (the number of prizes was determined based on the number of students presenting in each category):

    https://www.wpi.edu/news/announcements/grie-winners-announced

    Data Science, Cybersecurity, and Computer Science
    • 1st Place: Tom Hartvigsen, Data Science.
    • 2nd Place: Brian Zylich, Computer Science (did mqp project with Tabassum/Xiao).
    • 3rd Place: ML Tlachac, Data Science.
    • 3rd Place: Caitlin Kuhlman, Computer Science.

  • WiDS Central Massachusetts @ WPI
    March 4. 9:00 AM – 5:30 PM in Campus Center Odeum. WiDS Central MA @ WPI is a satellite event coinciding with the annual Global Women in Data Science (WiDS) Conference held at Stanford University and an estimated 150+ locations worldwide. All genders are invited to attend this WiDS regional event, which features outstanding women doing outstanding work -- including keynote speaker Dr. Fernanda Viégas, Senior Researcher, Google, Co-Leader PAIR (People + AI Research) Initiative and Big Picture Team. The Global WiDS Conference aims to inspire and educate data scientists worldwide, regardless of gender, and to support women in the field. This one-day technical conference provides an opportunity to hear about the latest data science related research and applications in a number of domains, and connect with others in the field. Best of all the event is free sponsored by the WPI WIN network.

2018:

  • On April 20th 2018, Yizhou Yan successfully passed her PhD Dissertation Proposal "Contextual Outlier Detection from Heterogeneous Data Sources". Congratulations to Yizhou on achieving this important milestone. Her dissertation committee members are Prof. Elke Rundensteiner (WPI, Advisor), Prof. Mohamed Y. Eltabakh (WPI), Prof. Xiangnan Kong (WPI), and Prof. Sam Madden (MIT).
  • On April 11th 2018, Xiao Qin successfully passed his PhD Dissertation Proposal "Sequential Data Mining and its Applications to Pharmacovigilance". Congratulations to Xiao on achieving this important milestone. His dissertation committee members are Prof. Elke Rundensteiner (WPI, Advisor), Prof. Xiangnan Kong (WPI), Prof. Mohamed Y. Eltabakh (WPI), and Prof. Fei Wang (Cornell Univeristy).
  • On March 22nd 2018, Maryam Hasan successfully passed her PhD Dissertation Proposal "Emotion Classification in Social Text Streams". Congratulations to Maryam on achieving this important milestone. Her dissertation committee members are Prof. Elke Rundensteiner (WPI, Advisor), Prof. Kyumin Lee (WPI), Prof. Emmanuel Agu (WPI), and Prof. Wei Ding (UMass Boston).

2017:

  • On December 8th 2017, Ramoza Ahsan successfully passed her PhD Dissertation Proposal "Exploration and Mining of Temporal Data". Congratulations to Ramoza on achieving this important milestone. Her dissertation committee members are Prof. Elke Rundensteiner (WPI, Advisor), Prof. Gabor Sarkozy (WPI, Advisor), Prof. Xiangnan Kong (WPI), and Prof. Vassilis Athitsos (The University of Texas at Arlington).
  • On November 27th 2017, Olga Poppe successfully defended her PhD dissertation. Congratulations to Dr. Olga Poppe! Olga's dissertation research, titled "Event Stream Analytics", focuses on strategies for scaling analytics including trend discovery and aggregation on event streams. Her dissertation committee members are Prof. Elke Rundensteiner (WPI, Advisor), Prof. Mohamed Eltabakh(WPI), Prof. Dan Dougherty (WPI), and Prof. D. Mailera (Portland State University).
  • On May 11th 2017, Phd student Cansu Sen has successfully passed her Ph.D. Research Qualifier. Congratulations to Cansu on achieving this important milestone!
  • On May 9th 2017, Phd student Caitlin Kuhlman has successfully passed her Ph.D. Research Qualifier. Congratulations to Caitlin on achieving this important milestone!
  • On April 12th 2017, Rodica Neamtu successfully defended her PhD dissertation. Congratulations to Dr. Rodica Neamtu! Rodica's dissertation entitled "Interactive Exploration of Time Series Powered by Time Warped Distances" falls into the broad areas of data analytics. Her dissertation committee members are Prof. Elke Rundensteiner (WPI, Advisor), Prof. Gabor Sarkozy (WPI, Advisor), Prof. George Heineman (WPI), and Prof. Sam Madden (MIT).
  • On March 9th 2017, Phd student Yizhou Yan has successfully passed her Ph.D. Research Qualifier. Congratulations to Yizhou on achieving this important milestone!
  • On January 29th 2017, Phd student Olga Poppe has successfully passed her Ph.D. Comprehensive Exam. Congratulations to Olga on achieving this important milestone! Her PhD committee are Prof. Elke Rundensteiner (WPI, Advisor), Prof. Daniel Dougherty (WPI), Prof. Mohamed Eltabakh (WPI), and Prof. David Maier (Portland State University).

During 2016:

  • On September 27th 2016, Rodica Neamtu successfully passed her PhD Dissertation Proposal "Interactive Exploration of Time Series Powered by Time Warped Distances", develops both theoretical underpinnings as well as technologies for processing rich classes of interactive queries over time series empowered by multiple distances. Congratulations to Rodica on achieving this important milestone. Her dissertation committee members are Prof. Elke Rundensteiner (WPI, Advisor), Prof. Gabor Sarkozy (WPI, Advisor), Prof. George Heineman (WPI), and Prof. Sam Madden (MIT).
  • On August 29th 2016, Phd student Ramoza Ashan has successfully passed her Ph.D. Comprehensive Exam. Congratulations to Ramoza on achieving this important milestone! Her PhD committee are Prof. Elke Rundensteiner (WPI, Advisor), Prof. Gabor Sarkozy (WPI), Prof. Xiangnan Kong (WPI), and Prof. Vassilis Athitsos (Univ. of Texas at Arlington).
  • PhD student Olga Poppe, supervised by Prof. Rundensteiner, is Research Intern at NEC Laboratories America, Inc in summer 2016.
  • PhD student Caitlin Kuhlman, supervised by Prof. Rundensteiner, is a "Social Good" Research Fellow at IBM TJ Watson in summer 2016.
  • On May 23rd 2016, Phd student Rodica Neamtu has successfully passed her Ph.D. Comprehensive Exam. Congratulations to Rodica on achieving this important milestone! Her PhD committee are Prof. Elke Rundensteiner (WPI, Advisor), Prof. Gabor Sarkozy (WPI, Advisor), Prof. George Heineman (WPI), and Prof. Sam Madden (MIT).
  • DSRG celebrated the graduations of Kaiyu Zhao, Lei Cao and Chuan Lei with a party at Elke's house.
  • On May 12th 2016, WPI's 148th Commencement Ceremony was held. Our newest PhD's Dr. Kaiyu Zhao, Dr. Lei Cao and Dr. Chuan Lei received their diploma from Prof. Elke Rundensteiner.
  • On May 11th 2016, Olga Poppe successfully passed her PhD Dissertation Proposal "Event Stream Analytics", focused on strategies for scaling analytics including trend discovery and aggregation on event streams. Congratulations to Olga on achieving this important milestone! Her dissertation committee members are Prof. Rundensteiner (advisor), Prof. Mohamed Eltabakh, Prof. Dan Dougherty, and Prof. D. Mailer from Portland State University.
  • On March 29th 2016, Lei Cao has received his Ph.D. degree from WPI.
  • On Feb 23rd 2016, Kaiyu Zhao has received his Ph.D. degree from WPI.

2015:

  • On Aug 17th 2015, Chuan Lei has received his Ph.D. degree from WPI.

2014:

  • On May 17th 2014, Karen Works has received her Ph.D. degree from WPI.
  • On April 17th 2014, Xika Lin won the 3rd prize in the Science PhD category in the final round of GRAD'14.
  • On April 17th 2014, Xika Lin was selected as finalist by the Arts and Sciences Advisory Board to participate in the final round of the i3 Competition "Investing in Ideas with Impact".
  • On April 16th 2014, the following papers were accepted for publication at SIGMOD'14:
    • Yingmei Qi, Lei Cao, Medhabi Ray and Elke A. Rundensteiner. Complex Event Analytics: Online Aggregation of Stream Sequence Patterns.
    • Dongqing Xiao and Mohamed Eltabakh. InsightNotes: Summary-Based Annotation Management in Relational Databases.
  • Xika Lin won the Deans' round of the i3 Competition "Investing in Ideas with Impact" in April 2014.
  • On March 19th 2014, Chuan Lei and Xika Lin won Research Poster Awards at senior PhD level and Maryam Hasan and Olga Poppe received Research Poster Awards at junior PhD level at GRAD'14.

2013:

  • On December 22nd 2013, the following papers were accepted for publication at EDBT'14:
    • Chuan Lei, Elke A. Rundensteiner and Mohamed Eltabakh. Redoop: Supporting Recurring Queries in Hadoop.
    • Venkatesh Raghavan and Elke A. Rundensteiner. CAQE: A Contract Driven Approach to Processing Concurrent Decision Support Queries.
    • Abhishek Mukherji, Elke A. Rundensteiner and Matthew Ward. COLARM: Cost-based Optimization for Localized Association Rule Mining.
  • On December 12th 2013, Jiayuan Wnag has successfully defended her MS thesis.

    The real-time detection of anomalous phenomena on streaming data has become increasingly important for applications ranging from fraud detection, financial analysis to traffic management. In these streaming applications, often a large number of similar continuous outlier detection queries are executed concurrently. In the light of the high algorithmic complexity of detecting and maintaining outlier patterns for different parameter settings independently, we propose a shared execution methodology called SOP that handles a large batch of requests with diverse pattern configurations.

    First, our systematic analysis reveals opportunities for maximum resource sharing by leveraging commonalities among outlier detection queries. For that, we introduce a sharing strategy that integrates all computation results into one compact data structure. It leverages temporal relationships among stream data points to prioritize the probing process. Second, this work is the first to consider predicate constraints in the outlier detection context. By distinguishing between target and scope constraints, customized fragment sharing and block selection strategies can be effectively applied to maximize the efficiency of system resource utilization. Our experimental studies utilizing real stream data demonstrate that our approach performs 3 orders of magnitude faster than the start-of-the-art and scales to 1000s of queries.

  • On November 4th 2013, Karen Works has successfully defended her PhD dissertation. Congratulations to Dr. Karen Works!

    Karen Works' research has focussed on the development of novel technology for handling stream data with multiple levels of importance to an organization, and in particular, its multi-tiered priority-based query processing in the face of limited resources. Karen's contributions include but are not limited to the following core innovations:

    • proactive promotion infrastructure for multi-tiered stream processing to assure that the most important tuples are processed before those of less importance.
    • effective optimizer for efficiently constructing optimal multi-tierd plans.
    • run-time adaptive methodology to continuously allocate resources based on monitored available load and on estimated priority needs.
    • an array of sophisticated query operators tuned for effective processing within this novel infrastructure, which includes set-based operators like aggregation and multi-input based operators like joins, and
    • extensive experimental evaluation studies to assess the effectiveness of the proposed technology against state-of-the-art alternative solutions using real-world use cases.

    We wish Dr. Karen Works best of luck in her professional career as Tenure-Track Professor of Computer Science at Westfield State University!

  • On October 15th 2013, the paper of Lei Cao and Elke A. Rundensteiner on "High Performance Stream Query Processing With Correlation-Aware Partitioning" was accepted for publication at VLDB'14.
  • On October 15th 2013, the paper of Lei Cao, Di Yang, Qingyang Wang, Yanwei Yu, Jiayuan Wang and Elke A. Rundensteiner on "Scalable Distance-Based Outlier Detection over High-Volume Data Streams" was accepted for publication at ICDE'14.
  • From July until September 2013, Chuan Lei got a chance to intern at LinkedIn Corporation and Medhabi Ray got a chance to intern at HP Research Labs.
  • On July 22nd 2013, the following papers were accepted for publication at CIKM'13:
    • Abhishek Mukherji, Jason Whitehouse, Christopher R. Botaish, Elke A. Rundensteiner, and Matthew O. Ward. SPHINX: A Parameter Space Explorer for Analyzing Evidence-Hypotheses Relationships.
    • Abhishek Mukherji, Xika Lin, Jason Whitehouse, Christopher R. Botaish, Elke A. Rundensteiner, and Matthew O. Ward. FIRE: Interactive Visual Support for Parameter Space-Driven Rule Mining.
    • Karim Ibrahim, Nate Selvo, Mohamed El-Rifai, and Mohamed Eltabakh. FusionDB: Conflict Management System for Small-Science Databases.
  • On May 17th 2013, Maryam Hasan, Abhishek Mukherji, Xika Lin, and Olga Poppe have received SIGMOD'13 student travel award.
  • On May 11th 2013, Di Wang has received her Ph.D. degree and Yingmei Qi has received her Master's degree from WPI.
  • On May 5th 2013, the paper of Dongqing Xiao and Mohamed Y. Eltabakh on "STEPQ: Spatio-Temporal Engine for Complex Pattern Queries" was accepted for publication at the International Symposium on Spatial and Temporal Databases (SSTD) 2013.
  • In April 2013, Xika Lin won the Deans' round of the i3 Competition "Investing in Ideas with Impact".
  • On April 29th 2013, Di Wang has successfully defended her PhD dissertation. Congratulations to Dr. Di Wang!

    Di Wang's dissertation research has focussed on the development of several critical innovations within the context of complex event processing over high-volume data streams to further emerging applications ranging from on-line financial transactions, RFID based supply chain management to real-time object monitoring. In particular, her contributions include innovations and publications in top venues on the following topics: a. For applications which require access to both streaming and stored data, she has introduced an active complex CEP model with clear semantics and efficient scheduler algorithms in the face of concurrent access and failures. b. When deployed in a sensitive environment such as health care, she has proposed event-suppression technology critical for mitigating possible privacy leaks within the context of complex event processing systems. c. For high-performance inferencing of probabilistic identification of events with possible missing identifiers, her work not only provides a graphical model to capture this inference problem but she also designed general system optimizations that speed up existing inference strategies on streams up to 15 fold.

    In addition, she was a key architect and developer of the HyReminder Web Application for employing CEP technology to track health care workers's activities at the UMASS Memorial Hospital. This software, currently deployed at UMASS ICUs, has undergone a clinical trial - showing clear positive indicators of the effectiveness of such electronic reminder technology. Results of this health care trial have been submitted to a health care meeting.

    We thank everyone who was able to attend Di's presentation today and to lend Di support. In particular we would like to thank the committee members Prof. Dougherty, Prof. Eltabakh and the external committee member Dr. Badrish Chandramouli from Microsoft Research Labs for their time and effort in guiding Di through her PhD studies. We also thank the DSRG lab members for listening to Di's research, sharing ideas, and generally supporting each other over these years.

    Now we wish Di best of luck in her professional career starting at BING! at Microsoft Corp.effective immediately.

  • In March 2013, Lei Cao won PhD second place Research Poster Award and Chuan Lei won Senior PhD Research Poster Award at GRAD'13.
  • On February 5th 2013, the following papers were accepted for publication at SIGMOD'13:
    • Di Wang, Yeye He, Elke A. Rundensteiner, and Jefferey Naughton. Utility-Maximizing Event Stream Suppression.
    • Abhishek Mukherji, Xika Lin, Christopher R. Botaish, Jason Whitehouse, Elke A. Rundensteiner, Matthew O. Ward, and Carolina Ruiz. PARAS: interactive parameter space exploration for association rule mining.

2012:

  • the following papers were accepted for publication at EDBT'13:
    • Mohamed Y. Eltabakh, Fatma Ozcan, Yannis Sismanis, Peter Haas, Hamid Pirahesh, and Jan Vondrak. Eagle-Eyed Elephant: Split-Oriented Indexing in Hadoop.
    • Di Wang, Elke A. Rundensteiner, Richard T. Ellison, and Han Wang. Probabilistic inference of object identifications for event stream analytics.
    • Medhabi Ray, Elke A. Rundensteiner, Mo Liu, Chetan Gupta, Song Wang, and Ismail Ari. High-performance complex event processing using continuous sliding views.
  • On October 14th 2012, the article of Chuan Lei, Elke A. Rundensteiner, and J. D. Guttman on "Robust Distributed Stream Processing" was accepted for publication at ICDE'13.
  • In April 2012, Yingmei Qi made into the top round of the i3 Competition "Investing in Ideas with Impact".
  • On April 5th 2012, Venkatesh (Venky) Raghavan has successfully passed his final Ph.D. Dissertation Defense. Congratulations to Dr. Venkatesh Raghavan!

    Congratulations to Venky on having successfully conducted high-quality and innovative research, which has been published in top venues, including ICDE, Information Systems Journal, IDAR, and others, and several very well-received software demonstrations of core technologies in ACM SIGMOD. Venky's dissertation research falls in the area of big-data analytics and multi-criteria preference systems. His dissertation is entitled "Supporting Multi-Criteria Decision Support Queries over Disparate Data Sources". Given the exponential growth of information, providing services to help analysts, businesses and users alike to extract value from data is imperative for staying ahead and meeting one's information needs. In this context, Venky has designed a suite of innovative techniques and corresponding software technologies that tackle open problems in support of multi-dimensional preference (skyline) queries, enabling users to quickly grasp their prefered choices from a huge data store.

    Venky has started his professional career at the Greenplum startup (now, an EMC company) in California, and is enjoying every day of it. He is getting his hands deep into the guts of a commercial query optimizer for large-scale distributed compute platforms - helping to build it from the grounds up to meet the BigData buzz. We wish him the very best success and fun in his future professional career in computing!

    We also would like to thank everyone who was able to attend Venky's defense yesterday and lend their support to him. We thank the CS department, all faculty, the office and computing staff, for providing an amazingly nuturing environment in which Venky could mature into an accomplished researcher and Computer Scientist. It sure was a pleasure yesterday seeing Venky shine in his accomplishments -- he has come a long way, and I am proud of him. In particular, we thank the committee members Prof. Dan Dougherty, Prof. Murali Mani and Dr. Haixun Wang (Microsoft Research Asia) for their time, effort and extremely valuable feedback on Venky's work. Their help in guiding Venky is very much appreciated.

  • On March 7th 2012, Mo Liu has successfully passed her final Ph.D. Dissertation Defense. Congratulations to Dr. Mo Liu!

    The committee has accepted her work subject to minor revisions, which Mo plans to apply to the manuscript in the following weeks. Congratulations to soon-to-be Dr. Liu! Congratulations to Mo on having conducted high-quality research, which has been published in top venues in the database field, including SIGMOD, ICDE, and others.

    Mo's dissertation research falls in the area of Complex Event Processing on Data Streams. Specifically, her dissertation entitled "Extending Event Sequence Processing: New Models and Optimization Techniques" includes the design, development and evaluation of several techniques at the core of an E-Analytic system to achieve efficient, scalable and robust methods for in-memory multi-dimensional nested pattern analysis over high-speed event streams.

    We would like to thank everyone who was able to attend Mo's defense and lend their support to Mo. We thank the CS department for providing a nuturing environment in which Mo Liu could mature into an accomplished Computer Scientist. In particular, we thank the committee members Prof. Dan Dougherty, Prof. Yanlei Diao, University of Massachusetts Amherst; Prof. Murali Mani, University of Michigan, Flint; and Prof. Ismail Ari, Ozyegin University, Turkey for their time and valuable feedback on Moi's work. In particular, Mo would like to extend a special thank you to Prof. Dan Dougherty, who has spent countless hours in helping Mo to explore the world of CEP language design, semantics and optimization. The committee's help in guiding Mo to make her work of the utmost quality is much appreciated.

    Lastly, Mo Liu has started her professional career at Sybase, Inc, an SAP Company, in California. We wish her a fulfilling career complete with interesting challenges and both success and fun going forward, where ever life may take her.