Our team

Faculty

Elke Rundensteiner

WILLIAM B. SMITH

Professor

Select Faculty Collaborators

(Jointly mentoring Phd students and/or collaborating on shared projects)

Professor

Associate Professor

Associate Professor

Assistant Professor

Associate Professor

Associate Professor

Assistant Professor

Assoc. Teaching Prof.

Asst. Teaching Prof.

Professor, MIT

Professor, U Illinois

Army Research Laboratory

PhD Students

Recent Master Thesis Students

Allison
Rozet

Luke
Buquicchio

Walter
Gerych

Muzammil
Bashir

Tom
Hartvigsen

ML
Tlachac

PhD Alumni

PhD 2021

Postdoctoral Researcher

MIT CSAIL

PhD 2021

Data Scientist

WPI

PhD 2021

Faculty

San Francisco State

PhD 2021

Data Scientist

Wells(startup)

PhD 2020

Research Fellow

Harvard Medical School

PhD 2020

Research Scientist

Facebook

PhD 2020

Data Scientist

Codametrix

PhD 2020

ML Engineer

Apple

PhD 2019

Research Scientist

Visa Research

Projects

matters

PI.Hao Feng

co-PI.Elke Rundensteiner

matters

PI.Elke Rundensteiner

Time Series Analytics

Dr.Elke Rundensteiner

Dr.Mohamed Eltabakh

matters

PI.Elke Rundensteiner

co-PI.Lane Harrison

matters

Dr.Elke Rundensteiner

Dr.Emmanuel Agu

matters

Dr.Elke Rundensteiner

Dr.Xiangnan Kong

matters

PI.Elke Rundensteiner

co-PI.Fatemeh Emdad

matters

PI.Elke Rundensteiner

Complex Event Analytics

PI.Elke Rundensteiner

Hierarchical Instantiating Timed automaton

PI.Elke Rundensteiner

A Novel Paradigm for Query Processing

PI.Elke Rundensteiner

Research Experience for K12.jpg

PI.Elke Rundensteiner

co-PI.Neil Heffernan

XQueries Over XML Streams .jpg

PI.Elke Rundensteiner

co-PI.Murali Mani

Continuous Adaptive Processing Engine.jpg

PI.Elke Rundensteiner

co-PI.Neil Heffernan

Personalized Annotation Management in RDB.jpg

PI.Elke Rundensteiner

Supporting Annotations Beyond Propagation In RDB.jpg

PI.Elke Rundensteiner

Analyzing Text Data Streams in Social Microblogging Networks.jpg

PI.Elke Rundensteiner

Visual Exploration Support for Data Mining and Discovery .jpg

PI.Elke Rundensteiner

XQuery Processing.jpg

PI.Elke Rundensteiner

XML Indexing.jpg

PI.Elke Rundensteiner

Information Integration under Dynamic Distributed Data Sources.jpg

PI.Elke Rundensteiner

Information Integration over Heterogeneous Data Sources.jpg

PI.Elke Rundensteiner

Information Integration By Discovery of Data Source Relationships.jpg

PI.Elke Rundensteiner

Model-Management Driven Integration of Heterogeneous Sources.jpg

PI.Elke Rundensteiner

Object-Oriented Database Systems.jpg

PI.Elke Rundensteiner

Spatial and Multimedia Query Processing.jpg

PI.Elke Rundensteiner

REU Program

PI.Elke Rundensteiner

co-PI.Chun-Kit Ngan

wash

PI.Emmanuel Agu

co-PI.Elke Rundensteiner

Anomaly Detection

PI.Elke Rundensteiner

Latest News

On November 16th 2022, DAISY member Oluseun Olulana recieved the prestigious American Association of University Women's International Doctoral Degree Fellowship. Congratulations Olu! Read More

On August 10th 2022, Noura Alghamdi successfully completed her PhD dissertation defense, congratulations Dr. Alghamdi!

WPI features DAISY research into AI depression screening of voice recordings Read More

Congratulations to Walter Gerych and Jadipa Thadajarassiri for winning first and third place at WPI's Graduate Resesearch Innovation Exchange! See their award photo in the carousel below!

Congratulations to Walter Gerych, Kevin Hickey, and Jadipa Thadajarassiri for being selected to advance to the finals of WPI's Graduate Research Innovation Exchange! Read More

WPI features DAISY member Kathleen Cachel's work to make AI more fair through addressing bias in automated rankings Read More

Congratulations to DAISY member Walter Gerych for being selected to present his work in an oral presentation at AAAI 2022!

On December 1st 2021, Tom Hartvigsen successfully completed his PhD dissertation defense, congratulations Dr. Hartvigsen!

Congratulations to Ermal Toto and ML Tlachac for recieving the Best Applied Research Paper award at CIK 2021! Amazing work!

Congratulations to several DAISY teams for getting papers accepted at the IEEE International Conference on Big Data! Read more on our news page below!

Congratulations to DAISY members Biao and Nick and their collaborators for getting their data set paper accepted to BMVC 2021!

Congratulations to DAISY members Ricardo, Luke, Walter, and their collaborators for getting papers accpeted to ICMLA 2021!

DAISY PhD graduate Dr. Susmitha Wunnava is featured speaker at WPI's Class of 2021 commencement. Congratulations, Susmitha!

Professor Elke Rundensteiner is named WILLIAM B. SMITH PROFESSOR!

Dr. Tabassum Kakar will join Well as a Data Visualization and Reporting Specialist.

WPI wins $3 Million Award To Launch Graduate Program Preparing Data-Driven Leaders To Build A More Sustainable And Just Future Read More

DAISY IN ACTION

DAISY PhD graduate Dr. Susmitha Wunnava was the featured speaker at WPI's Class of 2021 commencement. Susmitha now moves on with her career as a Research Fellow at Harvard Medical School pursuing her dream of working in medical analytics. Congratulations, Susmitha!

Former DAISY student Dr. Manasi Vartak is now founder and CEO of AI start-up Verta which aims to bring the latest in data science research into the bussiness world by estabilishing best practices for deploying machine learning. Verta has just secured a $10 million Series A round of funding, Read More.

Open positions


We are always looking for bright, motivated, and hard-working graduate and undergraduate students to join our group and work on projects with us to develop data-centric solutions and systems that solve pressing problems in healthcare, medicine, science, or engineering with societal impact. If you are interested, please contact Elke Rundensteiner at rundenst [at] wpi [dot] edu.

Awards

Our group has been recognized many times over the years from best papers/posters to competitions to TA awards. For a full list, please click the following link.

Funding

We are grateful to have been supported by many funding agencies over the years. In addition to our ongoing projects, please refer to the following full list of funding sources.

NSF

HP

Microsoft


IBM

Verizon

MIT Lincoln Lab

Funding sources

Publications

Selected Recent Publications.

  • Jida Thadajarassiri, Tom Hartvigsen, Walter Gerych, Xiangnan Kong and Elke Rundensteiner. Knowledge Amalgamation for Multi-Label Classification via Label Dependency Transfer. AAAI 2023.
  • Liang Zhang, Noura Alghamdi, Huayi Zhang, Mohamed Y. Eltabakh, and Elke A. Rundensteiner. PARROT: Pattern-Based Correlation Exploitation in Big Partitioned Data Series. VLDB Journal, 1-24, 2022
  • 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. 2022 IEEE International Conference on Big Data
  • Nicholas Josselyn, Biao Yin, Ziming Zhang, and Elke Rundensteiner. An Empirical Study of Domain Adaptation: Are We Really Learning Transferable Representations? 2022 IEEE International Conference on Big Data
  • Joshua DeOliveira, Walter Gerych, Aruzhan Koshkarova, Elke Rundensteiner, and Emmanuel Agu. HAR-CTGAN: A Mobile Sensor Data Generation Tool for Human Activity Recognition. 2022 IEEE International Conference on Big Data
  • 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. 21st IEEE International Conference on Machine Learning and Applications, 2022.
  • Avantika Shrestha, ML Tlachac, Ricardo Flores, Elke Rundensteiner. BERT Variants for Depression Screening with Typed and Transcribed Responses. WellComp Workshop, ACM UbiComp 2022.
  • Ricardo Flores, ML Tlachac, Avantika Shrestha, Elke Rundensteiner. AudiFace: Multimodal Deep Learning For Depression Screening, Temporal Facial Features for Depression Screening. MHSI workshop, ACM UbiComp 2022.
  • Ramesh Doddaiah, Prathyush Parvatharaju, Elke Rundensteiner, and Thomas Hartvigsen. Class-Specific Explainability for Deep Time Series Classifiers. IEEE Conf on Data Mining (ICDM), 2022
  • ML Tlachac, Avantika Shrestha, Mahum Shah, Benjamin Litterer, and Elke A. Rundensteiner. Automated Construction of Lexicons to Improve Depression Screening with Text Messages. IEEE Journal of Biomedical and Health Informatics (J-BHI), 2022.
  • Lei Cao, Yizhou Yan, Samuel Madden, and Elke Rundensteiner. AutoOD: Automatic Outlier Detection. ACM SIGMOD 2022.
  • Walter Gerych, Thomas Hartvigsen, Luke Buquicchio, Emmanuel Agu and Elke Rundensteiner. Robust Recurrent Classifier Chains For Multi-Label Learning With Missing Labels. ACM CIKM'2022.
  • Thomas Hartvigsen, Walter Gerych, Jidapa Thadajarassiri, Xiangnan Kong and Elke Rundensteiner. Stop&Hop: Early Classification of Irregular Time Series. ACM CIKM'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. Healthcare Analytics, Elsevier Publisher, 2022.
  • Ricardo Flores, ML Tlachac, Ermal Toto, Elke Rundensteiner. AudiFace: Multimodal Deep Learning For Depression Screening. Machine Learning for Healthcare (MLHC), 2022.
  • Mallak Alkhathlan, ML Tlachac, Lane Harrison and Elke Rundensteiner. Improving Image Accessibility by Combining Haptic and Auditory Feedback. ASSETS'2022.
  • Ricardo Flores, ML Tlachac and Elke A. Rundensteiner. Measuring the Uncertainty of Environmental Good Preferences with Bayesian Deep Learning. 2022 ACM International Conference on Information Technology for Social Good (GoodIT 2022).
  • Hilson Shrestha, Kathleen Cachel, Mallak Alkhathlan, Elke A Rundensteiner and Lane Harrison. FairFuse: Interactive Visual Support for Fair Consensus Ranking. IEEE VIS, short paper, 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. VLDB 2022.
  • 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. ACM IMWUT, June 2022.
  • 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. ACM IMWUT, June 2022.
  • Kathleen Cachel and Elke Rundensteiner. FINS Auditing Framework: Group Fairness for Subset Selections, AAAI ACM Conference on Artificial Intelligence, Ethics, and Society (AIES-2022), May 2022.
  • Ruofan Hu, Dongyu Zhang, Dandan Tao, Thomas Hartvigsen, Hao Feng and Elke Rundensteiner. TWEET-FID: An Annotated Dataset for Multiple Foodborne Illness Detection Tasks, Proceedings of the 13th Language Resources and Evaluation Conference, 2022.
  • Saskia Senn, ML Tlachac, R. Flores, E. Rundensteiner. Ensembles of BERT for Depression Classification, 4th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'22).

Contact us