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Experience
Student Researcher Providence, RI
Sept 2019 - Sept 2022
- Advisor: Prof. Carsten Eickhoff
- AI + Healthcare: Developed a patient-centric literature summarization mechanism by implementing NLP models on biomedical texts.
- AI + HCI: Conducted user-study on the effect of multi-document summarizations on User Search Results Page (SERP) experience.
Information Security Intern Cambridge, MA
Jan 2022 - May 2022 (Part-time)
- Built and integrated Machine Learning components into a threat-intelligence dashboard.
Information Security Intern Cambridge, MA
May 2020 - August 2020 (Full-time)
- Designed and deployed UI features to achieve consistent language interpretation in Technical Risk Illuminator, a tool built to support executive decisions.
- Conceptualized and modeled an NLP-based multiple-tag generator to identify key terms and types of incidents from cyber-incident reports.
Information Security Intern Cambridge, MA
May 2019 - August 2019 (Full-time)
- Optimized the yearly audits process duration by building a systems register, which generates answers that business units require to show that they are PCI Compliant.
- Revamped the PCI Gap Analysis Template to streamline the process of products entering the PCI Compliance program for the first time.
Information Security Analyst Intern Providence, RI
May 2018 - July 2018
- Substantially improved copyright ticketing process automation through network expansion in support of internal IP address, MAC address, and public IP username identification.
- Delivered code improvements through the establishment of quality assurance (QA) environment in DeskPro (REST API), enabling daily running of specific tickets by agents.
Research Intern Singapore
April 2016 - Jan 2017
- AI + Cyber Security: Proposed a novel method to detect cyber-attacks on a Cyber-Physical System with Dr. Sridhar Adepu, Dr. Jonathan Goh, and Prof. Aditya Mathur.
- Published and won Top 3 best student paper presentation for resulting research paper entitled "Effectiveness of Association Rules Mining for Invariants Generation in Cyber-Physical Systems" for the 18th IEEE International Symposium on High Assurance Systems Engineering (HASE) 2017.
Publications
| [1] | Koyena Pal, David Bau, and Renée J. Miller. "Model Lakes." ALT-GEN: Benchmarking Table Union Search using Large Language Models." International Conference on Extending Database Technology (EDBT) (2025).
[Paper] |
| [2] | Fiotto-Kaufman, Jaden, Alexander R. Loftus, Eric Todd, Jannik Brinkmann, Caden Juang, Koyena Pal, Can Rager et al. "NNsight and NDIF: Democratizing Access to Foundation Model Internals." International Conference on Learning Representations (ICLR) (2025).
[Paper] |
| [3] | Koyena Pal, Aamod Khatiwada, Roee Shraga, and Renée J. Miller. " ALT-GEN: Benchmarking Table Union Search using Large Language Models." VLDB 2024 Workshop: Tabular Data Analysis Workshop (TaDA).
Best Long Paper [Paper] |
| [4] | Mueller, Aaron, Jannik Brinkmann, Millicent Li, Samuel Marks, Koyena Pal, Nikhil Prakash, Can Rager et al. "The Quest for the Right Mediator: A History, Survey, and Theoretical Grounding of Causal Interpretability." arXiv preprint arXiv:2408.01416 (2024).
[Paper] |
| [5] | Koyena Pal, Jiuding Sun, Andrew Yuan, Byron C. Wallace, and David Bau. "Future Lens: Anticipating Subsequent Tokens from a Single Hidden State." SIGNLL Conference on Computational Natural Language Learning (CoNLL) (2023).
[Paper] [Website] |
| [6] | Meyer, C., Adkins, D., Pal, K., Galici, R., Garcia-Agundez, A., & Eickhoff , C. (2023).
Neural text generation in regulatory medical writing. Frontiers in Pharmacology, 14. https://doi.org/10.3389/fphar.2023.1086913
[Paper] |
| [7] | K. Pal, S. Adepu and J. Goh, “Effectiveness of Association Rules Mining for Invariants Generation
in Cyber-Physical Systems,” 2017 IEEE 18th International Symposium on High Assurance Systems
Engineering (HASE), 2017, pp. 124-127, doi: 10.1109/HASE.2017.21.
[Paper] [Presentation] |
Teaching Experience
I have served as a teaching assistant for the following courses at Northeastern and Brown University. Semesters marked with double asterisks (**) denote a Graduate Teaching Assistant role that I have undertaken at Northeastern. Semesters marked with an asterisk (*) denote a Head Teaching Assistant role that I performed during my time at Brown.
CSCI 7150: Deep Learning
Fall 2022**
- Course Description:
- Introduces deep learning, including the statistical learning framework, empirical risk minimization, loss function selection, fully connected layers, convolutional layers, pooling layers, batch normalization, multilayer perceptrons, convolutional neural networks, autoencoders, U-nets, residual networks, gradient descent, stochastic gradient descent, backpropagation, autograd, visualization of neural network features, robustness and adversarial examples, interpretability, continual learning, and applications in computer vision and natural language processing. With Prof. David Bau.
CSCI 1470/2470: Deep Learning
Fall 2020*
- Course Description:
- This course intends to give students a practical understanding of deep learning as applied in these and other areas. It also teaches the Tensorflow programming language for the expression of deep leaning algorithms. With Prof. Daniel Ritchie.
- Interviewed, hired, trained, and coordinated staff of 35 undergraduate and graduate TAs.
- Developed course materials, managed course logistics, led weekly labs, graded student work and held office hours.
CSCI 1010: Theory of Computation
Fall 2019
- Course Description:
- The course introduces basic models of computation including languages, finite-state automata and Turing machines. Proves fundamental limits on computation (incomputability, the halting problem). Provides the tools to compare the hardness of computational problems (reductions). Introduces computational complexity classes (P, NP, PSPACE and others). With Prof. Lorenzo De Stefani.
CSCI 0220: Introduction to Discrete Structures and Probability
Spring 2018
- Course Description:
- Seeks to place on solid foundations the most common structures of computer science, to illustrate proof techniques, to provide the background for an introductory course in computational theory, and to introduce basic concepts of probability theory. Introduces Boolean algebras, logic, set theory, elements of algebraic structures, graph theory, combinatorics, and probability. With Prof. Caroline J Klivans.
CSCI 0170: Computer Science - An Integrated Introduction
Fall 2018
- Course Description:
- CSCI0170/0180 is an introductory sequence that helps students begin to develop the skills, knowledge, and confidence to solve computational problems elegantly, correctly, efficiently, and with ease. The sequence is unique in teaching both the functional and imperative programming paradigms--- the first through the languages Scheme and ML in CSCI0170; the second through Java in CSCI0180. All of the following fundamental computer science techniques are integrated into the course material: algorithms, data structures, analysis, problem solving, abstract reasoning, and collaboration. With Prof. Philip Klein.
In addition to the teaching committee, I have been active in organizations such as Women In Computer Science where I have served as a mentor to younger women pursuing CS at Brown. Outside Brown, I have been an instructor at Inspirit AI (Summer 2020, Winter 2021), an outreach program to teach AI to high school students worldwide.
Education
Ph.D in Computer Science Boston, MA
Sept 2022 - Present
-
Lead Author Publications:
- Future Lens: Anticipating Subsequent Tokens from a Single Hidden State
- Generative Benchmark Creation for Table Union Search
- Model Lakes
-
Coursework:
- Empirical Research Methods for Human Computer Interaction
- Special Topics in Data Science
- Seminar in Human-Computer Interaction
- Seminar in Database Systems
- Readings
M.Sc and B.Sc in Computer Science (Honors) Providence, RI
Sept 2017 - May 2022
Master Thesis:
Summarization and Generation of Discharge Summary Medical Reports
Undergraduate Thesis:
The Effect of Multi-Document Summarizations on User SERP Experience
Graduate-Level Coursework:
- Computer Systems Security
- Topics in Software Security
- Privacy-Conscious Computer Systems
- Advanced Topics in Deep Learning
Undergraduate Coursework:
- Computer Science: An Integrated Introduction
- Introduction to Engineering
- Honors Calculus
- Principle of Economics
- Discrete Structures and Probability
- Cybersecurity and International Relations
- Linear Algebra
- Statistical Inference
- Introduction to Computer Systems
- Theory of Computation
- Introduction to Software Engineering
- Machine Learning
- Financial Accounting
- Intermediate Microeconomics
- Deep Learning
- Design and Analysis of Algorithms
- Software Security Exploitation
- Distributed Computer Systems
- Logic for Systems (Formal Methods and Verification)
- Entrepreneurial Process
- Social Pyschology
- Introduction to Video Game Studies
- CS for Social Change
- User Interface and User Experience
- Computer Graphics
- Computer Vision
International Baccalaureate (IB) Diploma Singapore
July 2015 - May 2017
Higher-Level Coursework:
- Physics
- Chemistry
- Math
Standard-Level Coursework:
- Economics
- English Literature
- French Ab Initio
Photo Gallery
NEMI 2025
I also led the organization of the 2nd New England Mechanistic Interpretability (NEMI) workshop @ Northeastern, Boston.
NEMI 2024
I led the organization of the 1st New England Mechanistic Interpretability (NEMI) workshop @ Northeastern, Boston.
Daebak Kpop Dance Group at Brown
Fun photo taken with my dance crewmates in the dance group that I was part of for all 4 years of my undergraduate program. Click any of the following links below to see some of our dance covers:
Piano
Sometimes, I play the piano during my free time. I professionally learned and
completed all levels of Piano ABRSM certification. Feel free to click the
following link to see a song I covered for fun!
Summer Love, One Direction
Akamai Internship 2019
A classic photo of an intern in front of her company logo.
Akamai Intern Picture
A group picture of all the 2019 interns at Akamai after a phenomenal BBQ dinner with the CEO.
Akamai Internship 2020
Due to COVID-19, our 2020 internship was held remotely. Here is the picture of us ,i.e., the InfoSec interns, meeting virtually in one of our many weekly meetups.
Brown Master's Graduation 2022
Family picture in post-COVID pandemic in-person graduation for my Master's degree.
Lab Retreat Spring 2023
Bau@NEU and Torralba@MIT lab meetup for a mini-conference/retreat at Cape Cod.
Bau Lab Group Photo 2024
Bau@NEU Group Photo starring main advisor, visiting researchers, phd students, and collaborators.