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

PhD Alumni

PhD 2024

LLM Eng/Researcher

Bytedance

PhD 2024

PhD 2023

Postdoc. Researcher

MIT CSAIL

PhD 2023

Scientific Fellow

Sanofi

PhD 2023

Assist. Prof

Uni. de Concepción, Chili

PhD 2023

Lecturer

Srinakharinwirot Univ.

PhD 2023

ML Scientist

TikTok

PhD 2022

Assistant Professor

University of Jeddah

PhD 2022

Assistant Professor

University of Manitoba

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

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

Elke Rundensteiner to Receive Another Prestigious IEEE Test-of-Time Award for Groundbreaking Visual Data Analytics Work Read More.

Congratulations to our many DAISY members who got papers accepted at FAccT 2024! Read More.

DAISY member Kathleen Cachel wins 1st place in WPI's 3 Minute Thesis Competition for her work 'Technologies for Fair Consensus Decision-Making'. Congratulations Kathleen!

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 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.

  • Oluseun Olulana, Kathleen Cachel, Fabricio Murai, Elke Rundensteiner. Hidden or Inferred: Fair Learning-To-Rank With Unknown Demographics. AAAI Conference on AI, Ethics, and Society (AIES 2024)
  • Harriet Sibitenda, Ruofan Hu, Elke Rundensteiner, Awa Diattara, Assitan Traore, and Cheikh Ba. Leveraging LLMs for Integrated Sentiment and Topic Analysis on African Social Media. ICMLA 2024, Deep Learning and Applications Special Session
  • Harriet Sibitenda, Awa Diattara, Assitan Traore, Ruofan Hu, Dongyu Zhang, Elke Rundensteiner, and Cheikh Ba. Extracting Semantic Topics about Development in Africa from Social Media. IEEE Access 2024
  • Simeon Krastev, Aukkawut Ammartayakun, Kewal Jayshankar Mishra, Harika Koduri, Eric Schuman, Drew Morris, Yuan Feng, Sai Supreeth Reddy Bandi, Chun-Kit Ngan, Andrew Yeung, Jason Li, Nigel Ko, Fatemeh Emdad, and Elke Rundensteiner. META: Deep Learning Pipeline for Detecting Anomalies on Multimodal Vibration Sewage Treatment Plant Data. Int Conf on Neural Computation Theory and Applications 2024
  • Dennis M. Hofmann, Peter M. VanNostrand, Lei Ma, Huayi Zhang, Joshua C. DeOliveira, Lei Cao, and Elke A. Rundensteiner. Agree to Disagree: Robust Anomaly Detection with Noisy Labels. ACM SIGMOD 2025
  • Peter M. VanNostrand, Dennis M. Hofmann, Lei Ma, Belisha Genin, Randy Huang, and Elke A. Rundensteiner. Counterfactual Explanation Analytics: Empowering Lay Users to Take Action Against Consequential Automated Decisions. Demonstration Paper, VLDB 2024
  • Lei Ma. Lei Cao, Peter VanNostrand, Dennis Hofmann, Su Yao, and Elke Rundensteiner. Pluto: Sample Selection for Robust Anomaly Detection on Polluted Log Data. ACM SIGMOD 2025
  • Mallak Alkhathlan, Kathleen Cachel, Hilson Shrestha, Lane Harrison, and Elke Rundensteiner. Balancing Act: Evaluating People's Perceptions of Fair Ranking Metrics. FAccT 2024
  • Peter M. VanNostrand, Dennis M. Hofmann, Lei Ma, and Elke A. Rundensteiner Actionable Recourse for Automated Decisions: Examining the Effects of Counterfactual Explanation Type and Presentation on Lay User Understanding. FAccT 2024
  • Kathleen Cachel and Elke Rundensteiner. PreFAIR: Combining Partial Preferences for Fair Consensus Decision-Making. FAccT 2024
  • 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

Contact us