Northwestern CS PhD Students Defend Dissertations in 2020

After years of research as a budding computer scientist, a PhD student’s dissertation defense is a significant milestone marking the end of their graduate career. Students move forward in many directions, whether it’s pursuing a role in academia, industry, or government, or taking some time to reflect on what’s next.   

Northwestern CS celebrates the following PhD students as they defend their dissertations. 

Mohammed Alam
Thesis: Harnessing Web Information Sources to Predict Events
Dissertation defense: July
Advisor: Doug Downey
Mohammed's Website

Mohammed Alam’s research focuses on artificial intelligence (AI), with an emphasis on machine learning (ML). His thesis shows how web information can be harnessed to predict events, from sports victories to stock prices to revolutions. To test his thesis, Alam researches ML methods that leverage the wisdom of crowds to predict sporting event outcomes using predictions crowdsourced from social media and to make financial predictions using those from a financial prediction platform. Prior to being a graduate student, Alam worked for Motorola as a software engineer for more than ten years and at a Chicago-area startup during his doctoral pursuit. Alam received a master’s degree in computer science from Northwestern University and a bachelor’s degree in computer engineering from the Illinois Institute of Technology, where he came to study from Bangladesh.

Johes Bater
Thesis title: Building a Private Data Federation: Security and Privacy Guarantees for Distributed Analytics
Expected dissertation defense: August
Advisor: Jennie Rogers
Johes's Website

Johes Bater received a bachelor's and master's degree in electrical engineering at Stanford University. Under the guidance of Assistant Professor Jennie Rogers, Bater researches how to implement privacy and security in federated databases. By investigating the intersection of security, privacy, and performance, Bater hopes to build fast, accurate database systems that support privacy-preserving analytics with provable security guarantees.

David Demeter
Expected Dissertation Defense: August
Advisor: Doug Downey

David Demeter's research focuses on the composition of neural models and symbolic models, and the closely related topic of analyzing the architectural limitations of neural network language models. Prior to returning to graduate studies, David worked as an investment banker focusing on financing transactions and international mergers and acquisitions, completing over 70 transactions totaling roughly $10 billion. He also cofounded a startup specializing in derivative securities. David has a master’s degree in applied mathematics and a bachelor’s degree in electrical engineering from Northwestern University, and an MBA from the University of Chicago Booth School of Business.

Spencer Florence 
Thesis title: A Constructive Calculus for Esterel 
Dissertation defense: June
Advisor: Robby Findler
Spencer's Website 

Spencer Florence is a Boston native who got addicted to programming languages early in his career. He has worked in and on the Racket programming language for about a decade, hacking on everything from code coverage tools to end user languages for physicians to libraries for proving equivalences between circuits. Florence’s research offers a new semantics for the programming language Esterel, a language designed to support safety-critical control systems used in industrial settings. Florence’s dissertation provides the first semantics for Esterel designed to help programmers reason about and work with the code. His semantics provide the theoretical underpinnings of program-development environment tool support, such as refactoring tools. In his dissertation he shows how to reason locally about fragments of Esterel programs, scaling up the ideas of replacing equals by equals. Florence received a bachelor’s degree in computer science from Northeastern University.

Aleck Johnsen
Working thesis title: Information Design and Inference in Auctions
Expected dissertation defense: August
Advisor: Jason Hartline
Aleck's Website

Aleck Johnsen’s research is in fundamentals of robust algorithm design for settings of incomplete information — relating to both mechanism design (private values) and online algorithms (uncertain future). For prior independent and prior free input settings, his main research includes the topics of algorithm design, benchmark design, adversarial algorithms, scalability of inputs, and inference in auctions. Johnsen previously served as the lecturer for one course of EECS 214 Data Science and Data Management. He has two bachelor’s degrees from University of Illinois (Urbana-Champaign) in mathematics and civil engineering: transportation.

Bonjun Kim 
Thesis title: Sound Event Annotation and Detection with Less Human Effort 
Dissertation defense: April 
Advisor: Bryan Pardo
Bongjun's Website

Bongjun Kim received a BS/MS in industrial engineering from Ajou University and a master’s degree in culture technology from Korea Advanced Institute of Science and Technology. His research interests include computational analysis of sound scenes and events (e.g., sound event detection), human-in-the-loop interfaces for audio annotation, interactive machine learning, and multimedia information retrieval. Kim's work develops a new approach to machine learning (learning from point labels) that reduces human effort that lets an algorithm learn from less-precise labeling, while maintaining high-quality learning. He further builds a mixed-initiative apprentice system where a machine labeler works interactively with the human labeler. Kim accepted a job working in the research division of 3M. 

Fengqiang Li 
Thesis title: Computational 3D imaging with high temporal, lateral, and depth resolution 
Dissertation defense: June 
Advisor: Oliver Cossairt
Fengqiang's Website

Fengqiang Li received a master’s degree in electrical engineering from Lehigh University, where he worked on optical coherence microscopy, and a bachelor’s degree in optoelectronic information engineering from Huazhong University of Science and Technology. Li is interested in image processing and various optical imaging techniques. He is currently working on time-of-flight imaging systems. For his thesis, Li proposes to couple a 3D camera together with a high-resolution RGB camera to produce a high-resolution, full-color, 3D scan with microscopic depth resolution. Li will formalize a model that poses fusion between high resolution RGB video and SH-ToF 3D scans as an inverse problem and then optimize results using iterative optimization and deep learning methods. Li will demonstrate how his new 3D scanning system can be used to improve the accuracy of computer vision tasks such as object detection and face recognition. Li accepted a position at Apple and starts in July.  

Mmachi Obiorah 
Thesis title: Technology Assisted Communication Devices for People with Aphasia 
Expected dissertation defense: September 
Advisor: Michael Horn
Mmachi's Website

Mmachi Obiorah received a bachelor’s degree from the University of Jos, Nigeria, and a master’s degree from Northwestern University. Their interests include building technology tools for interactive and collaborative learning of computer science in communities with infrastructural deficit as well as investigating and designing ways to create opportunities for learning in such communities. Obiorah works with people with aphasia to develop technologies to promote autonomy and increased quality of life. 

Irina Rabkina
Thesis title: Analogical Theory of Mind: Computational Model and Applications
Dissertation defense: July
Advisor: Kenneth Forbus
Irina's Website

Irina Rabkina received a bachelor’s degree in neuroscience from Scripps College and a master’s degree in computer science from Loyola University Chicago. Her research is on social reasoning for AI systems. She wants to build AIs that reason about others the way that humans do. Rabkina will be starting as an Assistant Professor of Computer Science at Occidental College this fall.

Zihao (Winston) Wang 
Thesis title: Synergy of Physics and Learning based Models in Computational Imaging and Display 
Expected dissertation defense: August 
Advisor: Oliver Cossairt
Winston's Website

Zihao (Winston) Wang received a bachelor’s degree in optics from Zhejiang University with honors from Chu KoChen Honors College in China. His current research interests include computational imaging and photography, computer vision, and color science (appearance). Wang is building a high frame-rate video frame synthesis (VFS) framework, which takes hybrid input data from a low-speed, frame-based sensor and a high-speed, event-based sensor using a differentiable physical model that incorporates a deep learning residual denoiser. He is also building a 3D holographic display applying a similar technique in modeling and solving the coherent light transport for holographic printing and display process. Wang accepted a job offer at Apple and will start in the fall. 

Chia-Kai Yeh 
Thesis title: Robust and portable apparatus based on the mobile device for 3D and appearance modeling 
Dissertation defense: June 
Advisor: Oliver Cossairt

Chia-Kai Yeh received a bachelor’s degree in electronics engineering from Chang Gung University in Taiwan. Afterwards, Yeh worked in the computational camera industry. His current research interest includes light field and reflectance field acquisition, appearance measurement, and modeling. Yeh has proposed to build and evaluate a robust and portable apparatus based on the mobile device for 3D and appearance modeling. 

Xiaofeng Zhu
Thesis title: Large Scale Knowledge Management in Complex Technical Ecosystems
Dissertation defense: January
Advisor: Diego Klabjan

Xiaofeng received a master’s degree in computer science from Northwestern University.. Her research interests include machine learning, natural language processing, learning-to-rank, and deep learning.