Tehmina Amjad

(she/her)

Associate Teaching Professor

Tehmina Amjad
  • Information retrieval
  • Machine learning
  • Academic social network analysis
  • Natural language processing
  • Scientometrics

Amjad’s research interests are centered on machine learning, information retrieval, natural language processing, academic social network analysis, and scientometrics, with applications in intelligent search, summarization, sentiment analysis, and data-driven understanding of research impact and knowledge dissemination. She is broadly interested in how scholarly networks operate and how impact can be quantified through academic social networks and altmetrics. Recently, Amjad has expanded her focus into geoscience, where she applies deep learning and data mining techniques to pore pressure prediction and subsurface characterization, marking a significant extension of her previous work and shaping the direction of my current projects.

Current projects

  • Summarization Assistant for Academic Research: An intelligent summarization tool for academic papers that uses fine-tuned transformer models. The system improves user trust by going beyond a typical “black-box” approach, showing researchers which parts of the original text were most important in creating the summary.
  • HME Framework for Pore Pressure Prediction: A unique meta-ensemble framework that combines multiple models, including CNNs, RNNs, and Random Forest, to improve the accuracy of pore pressure prediction in complex geological areas. By capturing both spatial and temporal patterns in well log data, the system provides a more robust and accurate solution for subsurface exploration.
  • PhD in Computer Science, International Islamic University, Islamabad — Pakistan (research conducted at Indiana University, Bloomington, under split program)
  • MS in Computer Science, International Islamic University, Islamabad — Pakistan

Tehmina Amjad is an associate teaching professor at the Khoury College of Computer Sciences at Northeastern University, based in Silicon Valley. She is dedicated to preparing students for their academic and professional careers by fostering a deep understanding of core computational concepts. Her teaching focuses on courses like Discrete Structures, Databases, Computer Systems, and Information Retrieval.

With over 16 years of experience as a professor prior to joining Northeastern, Amjad brings a passion for advancing students’ intellectual development. In her courses, she imparts foundational concepts, often incorporating analytics and data science principles.

Her research interests are diverse, spanning topics from citation analysis and knowledge diffusion to machine learning and natural language processing. Her work has been published in leading journals such as Future Generation Computer Systems, Scientometrics, and various IEEE publications.