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

Muzammil
Bashir

Tom
Hartvigsen

ML
Tlachac

PhD Alumni

PhD 2023

Postdoc. Researcher

MIT CSAIL

PhD 2023

Postdoc. Researcher

Sanofi Pharmaceutical

PhD 2023

Lecturer

Srinakharinwirot Univ.

PhD 2023

ML Scientist

TikTok

PhD 2022

Assistant Professor

University of Jeddah

PhD 2022

Consultant

 

PhD 2021

Asst. Prof, Uni. Virginia

(Postdoc, MIT CSAIL)

PhD 2021

Director, Academic and

Research Comp, 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

Professor Rundensteiner speaks as a panelist at the presidential event Beyond These Towers: Data Science & AI in Our Lives. Read More.

DAISY members win Best Paper award at IEEE CompSAC 2023 for paper titled 'Adversarial Human Context Recognition: Evasion Attacks and Defenses.' Congratulations! Read More.

Professor Elke Rundensteiner receives the prestigious IEEE Test-of-Time Award for her groundbreaking and durable contributions to visual data analytics! Read More.

Congratulations to our many DAISY members who got papers accepted at IEEE 2023! Read More.

Congratulations to DAISY member Walter Gerych for passing his PhD Dissertation Defense "Working With What You've Got: Leveraging Mislabeled Datasets And Improving Imperfect Pretrained Models"! Walter is now starting a position as a postdoc at MIT CSAIL.

Congratulations to DAISY member Ricardo Flores for passing his PhD Dissertation Defense "Multi-modal Models for Depression Screening"! Ricardo has accepted a postdoctoral research position at Sanofi Pharmaceutical Company focusing on AI for pharmaceuticals and healthcare.

Congratulations to DAISY member Jidapa Thadajarassiri for passing her PhD Dissertation Defense "Knowledge Amalgamation from Heterogeneous Pre-Trained Models"! Congratulations Dr. Jida!

On April 17th Professor Rundensteiner spoke with the Worcester Business Journal about the power and risks of using AI in healthcare applications. Read More

Congratulations to DAISY students for winning in the Data Science finals of GRIE 2023! Ricardo Flores took home 2nd place with Yao Su, Joshua DeOliveira, and Peter VanNostrand tied for 3rd! Great job all!

Congratulations to DAISY students Joshua DeOliveira, Ricardo Fores, Nicholas Josselyn, and Peter VanNostrand for advancing to the finals of GRIE 2023!

Congratulations to DAISY member Xika Lin for passing her PhD Dissertation Defense "Frequent Pattern Mining Analytics"! Congratulations Dr. Lin!

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 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!

Professor Elke Rundensteiner is named WILLIAM B. SMITH PROFESSOR!

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 business 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.

  • Dongyu Zhang, Ruofan Hu, and Elke Rundensteiner. CoLafier: Collaborative Noisy Label Purifier With LID Guidance. SIAM International Conference on Data Mining. SDM 2024.
  • Jidapa Thadajarassiri, Walter Gerych, Xiangnan Kong, and Elke Rundensteiner. Amalgamating Multi-Task Models with Heterogeneous Architectures. AAAI 2024.
  • 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) in IEEE BigData 2023.
  • Ricardo Flores, Avantika Shrestha, and Elke Rundensteiner. Multi-Task Learning Using Facial Features for Mental Health Screening. Special Session on HealthCare Data in IEEE BigData 2023.
  • 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) in IEEE BigData 2023.
  • 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) IEEE BigData 2023.
  • Biao Yin, Yangyang Fan, Nicholas Josselyn, and Elke Rundensteiner. AlloyGAN: Domain-Promptable Generative Adversarial Network for Generating Aluminum Alloy Microstructures. Special Session on Machine Learning for Predictive Models in Engineering Applications (MLPMEA) in 22nd IEEE International Conference on Machine Learning and Applications (ICMLA) 2023.
  • 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. Special Session on Machine Learning for Predictive Models in Engineering Applications (MLPMEA) in 22nd IEEE International Conference on Machine Learning and Applications (ICMLA) 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. NeurIPS 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. IEEE MIT Undergraduate Research Technology Conference (URTC) 2023. (REU Project Paper)
  • Peter M. VanNostrand, Huayi Zhang, Dennis Hofmann, and Elke Rundensteiner. FACET: Robust Counterfactual Explanation Analytics. ACM SIGMOD 2023.
  • Kathleen Cachel and Elke Rundensteiner. Fair&Share: Fast and Fair Multi-Criteria Selections. ACM CIKM 2023. 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. ACM CIKM 2023. Demonstration Paper.
  • 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. Journal on Food Engineering and Technology Applications of Artificial Intelligence in Food Industry, MDPI 2023.
  • Kathleen Cachel and Elke Rundensteiner. Fairer Together: Mitigating Disparate Exposure in Kemeny Rank Aggregation. FAccT 2023.
  • 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. FAccT 2023.
  • 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.

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