Work with thought leaders and academic experts in Software

Companies can benefit from working with an academic researcher in the field of Software in several ways. Firstly, researchers bring deep knowledge and expertise in the latest software technologies and methodologies. They can help companies stay ahead of the curve and adopt cutting-edge solutions. Secondly, researchers can provide valuable insights and analysis to solve complex software-related problems. They have the ability to conduct in-depth research, identify patterns, and propose innovative solutions. Thirdly, academic researchers often have access to state-of-the-art facilities and resources, which can be leveraged by companies for experimentation and prototyping. Lastly, collaborating with researchers can lead to valuable partnerships and networking opportunities, opening doors to new collaborations and potential funding sources.

Researchers on NotedSource with backgrounds in Software include Dr. Wolfgang Messner, Jerry Schnepp, Ph.D., IQRAM HUSSAIN, Ph.D., Daniel Milej, Ph.D., Stefano De Angelis, Ph.D., Vladimir Shapiro, Ph.D., Hector Klie, Edoardo Airoldi, Pranav Chandramouli, Dr. Aalok Thakkar, and David J. Lilja.

Dr. Wolfgang Messner

Columbia, SC
29 Years Experience
Professor in International Business with expertise in Data Analytics and Machine Learning
Education

University of Kassel

Dr. rer. pol., Economics and social sciences / 2004

Kassel

University of Wales

M.B.A., Financial management / 1998

Cardiff

Technical University Munich

B.Sc. & M.Sc. (Dipl.-Inform. Univ.), Computer science; artificial intelligence; computer graphics / 1995

Munich
Experience

University of South Carolina, Darla Moore School of Business | Columbia, SC, USA

Clinical Professor of International Business / 2016Present

• Developed novel algorithms for eXplainable Artificial Intelligence (XAI). Leveraged machine learning and deep learning techniques to address research questions in international business and marketing • Utilized advanced statistical approaches to assess cultural diversity and differences across regions and populations • Investigated variations in the impact of the COVID-19 pandemic on public health systems and consumer behavior • Taught under- and postgraduate courses in the #1-ranked international business department, as recognized by US News & World Report. Courses include data analytics, management consulting, and intercultural team management • Engaged in collaborative student consulting projects with companies such as Positec, SC SBDC, Seabin Australia, Thomson Reuters, UPS Global Supply Chain Solutions (Data & Innovation), and UPS International

MYRA School of Business | Mysore, India

Professor of International Management / 20132016

• Analyzed cultural differences in consumer behavior with a focus on the effectiveness of marketing strategies • Formulated strategic initiatives for conducting business in emerging markets • Taught postgraduate courses on customer service, business case analysis, and international business

GloBus Research | London, UK & Bangalore, India

Co-founder & Director / 20112017

• Developed customized learning solutions for executives • Created assessment tools to evaluate intercultural communication competence and team effectiveness • Led the design and delivery of the India module within the prestigious Leadership Excellence Program offered collaboratively by WHU, IDG, and DXC Technology

Most Relevant Research Expertise
Software
Other Research Expertise (14)
International Business
International Marketing
International Management
Strategy and Management
Business and International Management
And 9 more
About
Results-oriented and internationally experienced project manager, consultant, and researcher with a passion for leveraging machine learning and advanced statistical techniques to solve intricate challenges in international marketing and consumer behavior. Demonstrated track record of driving strategic initiatives, cultivating cross-border partnerships, and delivering tangible impacts on revenue generation. Highly adaptable to rapidly evolving technologies and market trends. Aiming to apply my expertise to lead transformative projects and elevate organizational success on a global scale. **Research and publication overview** · Authored 36 peer-reviewed journal publications (data analytics, international business, marketing) · Authored and edited 8 business books, published by *Palgrave Macmillan* and *Springer* · Published 5 teaching cases with *SAGE* and *Ivey* · Research impact (Google Scholar): h-index of 17 with 1,000+ citations **Competences in data analysis (selected)** · Supervised: Neural networks, deep learning · Unsupervised: Kohonen self-organizing maps · Frequentist and Bayesian regression analysis · Multilevel (hierarchical) modeling · Exploratory and confirmatory factor analysis · fs/QCA \| HLM \| SPSS \| JASP \| Python\, incl\. Keras\, Dalex
Most Relevant Publications (1+)

65 total publications

From black box to clear box: A hypothesis testing framework for scalar regression problems using deep artificial neural networks

Applied Soft Computing / Oct 01, 2023

Messner, W. (2023). From black box to clear box: A hypothesis testing framework for scalar regression problems using deep artificial neural networks. Applied Soft Computing, 146, 110729. https://doi.org/10.1016/j.asoc.2023.110729

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Jerry Schnepp, Ph.D.

Chicago, Illinois, United States of America
22 Years Experience
Chair of Computer Science, Judson University
Education

Ph.D., Computer Science / June, 2012

Chicago, Illinois, United States of America

M.S., Human-computer Interaction / June, 2002

Chicago, Illinois, United States of America

University of Illinois at Chicago

B.A., Communication / December, 1999

Chicago, Illinois, United States of America
Experience

Judson University

Chair of Computer Science / August, 2022Present

Leading the Department of Computer Science with a focus on evolving curricula, growing enrollment, and post-graduate professional preparedness. Coordinating research on AI-supported individualized learning experiences using Retrieval Augmented Generation (RAG). Spearheading professional development activities among faculty members focused on innovative pedagogy through Learner Experience Design (LXD). Teaching courses in Software Design Patterns, Data Structures, Algorithms, Web Development, Database Systems, and a Capstone Senior Project. Serving as Chair of the Undergraduate Academic Policy Committee and the Degree Completion Academic Policy Committee. Supporting student internships and independent studies.

Bowling Green State University

Tenured Associate Professor / May, 2018August, 2022

Led a university initiative to build The Collab Lab, an innovation space on the BGSU campus. Sought and received support to initiate the project, oversaw its design and construction, and led its operations as the director. Designed and taught courses in User Experience, Interactive Media, Augmented and Virtual Reality, Interaction Design, Web Development, and Usability. Supported twenty-five undergraduate independent study projects and served on graduate committees for two master’s students and four Ph.D. students, one as the primary advisor. Coordinated research projects investigating novel educational technologies: EASEL (Education through application-supported experiential learning), a mobile platform that facilitates real-time reflection during experiential learning and Point Barter, an online testing system that allows students to equitably trade exam points for hints to a correct answer.

Assistant Professor / August, 20122018

Designed and taught courses in User Experience, Interactive Media, Augmented and Virtual Reality, Interaction Design, Web Development, and Usability. Coordinated research projects investigating novel educational technologies: EASEL (Education through application-supported experiential learning), a mobile platform that facilitates real-time reflection during experiential learning and Point Barter, an online testing system that allows students to equitably trade exam points for hints to a correct answer.

DePaul University

Adjunct Faculty in Computer Science / August, 20022012

Taught courses in Human-Computer Interaction, Computer Graphics Development, Real-time Rendering, Data Visualization, Computer Animation, Web Design, and Digital Photography.

Most Relevant Research Expertise
Software
Other Research Expertise (18)
Human Computer Interaction
User Experience
Interactive Media
Computer Graphics
Accommodations for the Deaf
And 13 more
About
As a technologist, designer, and creative problem-solver, I'm passionate about teaching people to embrace new technology and explore. I am the Chair of the Computer Science department at Judson University. Before my appointment, I served as an Associate Professor in the College of Technology, Architecture and Applied Engineering at Bowling Green State University (BGSU). I teach courses in Programming, Data Structures and Algorithms, Software Design Patterns, Interactive Media, Usability, User Experience, and Augmented/Virtual Reality. I was the founding director of the Collab Lab, a hands-on, creative space for students and faculty to engage in collaborative work. My research efforts are directed in several areas: AI Supported Individualized Learning, Learner Experience Design, Technology for Online Assessment, Interactive Mobile Learning, and Computerized Sign Language Synthesis. I enjoy collaborating on projects involving cutting-edge technology and new applications.
Most Relevant Publications (3+)

20 total publications

An automated technique for real-time production of lifelike animations of American Sign Language

Universal Access in the Information Society / May 14, 2015

McDonald, J., Wolfe, R., Schnepp, J., Hochgesang, J., Jamrozik, D. G., Stumbo, M., Berke, L., Bialek, M., & Thomas, F. (2015). An automated technique for real-time production of lifelike animations of American Sign Language. Universal Access in the Information Society, 15(4), 551–566. https://doi.org/10.1007/s10209-015-0407-2

Special issue: recent advances in sign language translation and avatar technology

Universal Access in the Information Society / Jun 02, 2015

Wolfe, R., Efthimiou, E., Glauert, J., Hanke, T., McDonald, J., & Schnepp, J. (2015). Special issue: recent advances in sign language translation and avatar technology. Universal Access in the Information Society, 15(4), 485–486. https://doi.org/10.1007/s10209-015-0412-5

An improved articulated model of the human hand

The Visual Computer / May 01, 2001

McDonald, J., Toro, J., Alkoby, K., Berthiaume, A., Carter, R., Chomwong, P., Christopher, J., Davidson, M. J., Furst, J., Konie, B., Lancaster, G., Roychoudhuri, L., Sedgwick, E., Tomuro, N., & Wolfe, R. (2001). An improved articulated model of the human hand. The Visual Computer, 17(3), 158–166. https://doi.org/10.1007/s003710100104

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IQRAM HUSSAIN, Ph.D.

New York City, New York, United States of America
7 Years Experience
Weill Cornell Medicine, Cornell University, NY, USA
Education

Korea University of Science and Technology

Doctor of Philosophy, Medical Physics / February, 2022

Daejeon

Khulna University of Engineering and Technology

Bachelor of Science, Mechanical Engineering / April, 2007

Khulna
Experience

Weill Cornell Medicine

Postdoctoral Associate / March, 2023Present

Seoul National University

Postdoctoral Fellow / March, 2022February, 2023

Korea Research Institute of Standards and Science

PhD Researcher / September, 2017February, 2022

Most Relevant Research Expertise
Software
Other Research Expertise (32)
Biomedical & Medical Physics
AI (Machine & Deep Learning)
Anesthesiology
Sleep Medicine
Human Gait & brain
And 27 more
About
Iqram Hussain works at the Department of Anesthesiology, Weill Cornell Medicine, Cornell University, NY, USA. Earlier, he was a postdoctoral researcher at the Medical Research Center, Department of Biomedical Engineering, Seoul National University. He pursued a Ph.D. degree in Medical Physics from the University of Science and Technology (UST), South Korea. He worked as a Research Associate with the Korea Research Institute of Standards and Science (KRISS), Daejeon, South Korea. He worked on the Knowledgebase Super Brain (KSB) project at the Electronics and Telecommunication Research Institute (ETRI), Daejeon. He received a B.Sc. degree in mechanical engineering from the Khulna University of Engineering & Technology, Bangladesh, in 2007. He has ten years of work experience in power plant operation and maintenance and power plant project management. His research interests include wearable sleep monitoring, neuroscience, medical physics, human factors, and ergonomics. He has experience in healthcare research, project management, power plant operation, and maintenance. He is a reviewer in IEEE Access, Sensors, Applied Sciences, Biomedical Signal Processing and Control, IEEE Transactions, Science of the Total Environment, Neuroscience Informatics, Brain Sciences, etc. He is a guest editor in special issues of several Journals. Website: https://sites.google.com/view/iqram/home
Most Relevant Publications (1+)

43 total publications

Tracking Trajectory Planning of Space Manipulator for Capturing Operation

International Journal of Advanced Robotic Systems / Sep 01, 2006

Huang, P., Xu, Y., & Liang, B. (2006). Tracking Trajectory Planning of Space Manipulator for Capturing Operation. International Journal of Advanced Robotic Systems, 3(3), 31. https://doi.org/10.5772/5735

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Daniel Milej, Ph.D.

London, Ontario, Canada
15 Years Experience
Ph.D. in biomedical engineering
Education

Western University

Post-doctorate fellowship, Department of Medical Biophysics / June, 2019

London

Polish Academy of Science

PhD, Nalecz Institute of Biocybernetics and Biomedical Engineering / June, 2014

Warsaw

Military Univeristy of Technology

MSc, Department of Electronics / June, 2008

Warsaw
Experience

Lawson Research Institute

Research Associate / July, 2019July, 2025

Scientist / August, 2024Present

Western University

Postdoctoral fellow / September, 2014June, 2019

Assistant Professor / September, 2024Present

Polish Academy of Science

Researcher/PhD Student / June, 2008September, 2014

Most Relevant Research Expertise
Software
Other Research Expertise (31)
Biomedical Optics
NIRS
fNIRS
Diffuse Correlation Spectroscopy
CBF
And 26 more
About
Dr. Daniel Milej is a multidisciplinary researcher with experience in medical biophysics, electronics, biocybernetics, biomedical optics and engineering. He is highly knowledgeable and experienced in a range of research techniques. He is a Scientist at the Lawson Research Institute, leading the transition of multimodal optical imaging systems from a research setting to clinical use in an ICU and OR environment, working closely with teams of nurses, surgeons, doctors and respiratory therapists. Previously, he was a Postdoctoral Fellow and Research Associate working on developing noninvasive modalities for brain activity monitoring in the Department of Medical Biophysics at Western University. Before that, Dr. Milej worked as a Researcher at the Nalecz Institute of Biocybernetics and Biomedical Engineering. He obtained his Ph.D. in 2014 from the Polish Academy of Science, specializing in Biocybernetics and Biomedical Engineering. He received his MSc in Electronics/Optoelectronics from the Military University of Technology, Warsaw, Poland, in 2008.
Most Relevant Publications (1+)

91 total publications

Analysis of estimation of optical properties of sub superficial structures in multi layered tissue model using distribution function method

Computer Methods and Programs in Biomedicine / Jan 01, 2020

Żołek, N., Rix, H., & Botwicz, M. (2020). Analysis of estimation of optical properties of sub superficial structures in multi layered tissue model using distribution function method. Computer Methods and Programs in Biomedicine, 183, 105084. https://doi.org/10.1016/j.cmpb.2019.105084

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Stefano De Angelis, Ph.D.

Rome
6 Years Experience
Ph.D. computer scientist with interest in blockchains, cyber security, and applied cryptography. Strong expertise in secure protocols design and assessment, wirh publications on blockchains and distributed consensus security.
Education

Università degli Studi di Roma "La Sapienza"

Ms.C., Computer Science / January, 2018

Rome

University of Southampton

Ph.D., Computer Science and Cyber Security / May, 2022

Southampton
Experience

NATO

CIS Security Researcher / March, 2018September, 2018

Definition of IoT and blockchain cybersecurity policy for NATO enterprice applications

University of Southampton

Postdoctoral Researcher / October, 2020February, 2022

Design and assessment of secure scalable blockchain systems, with focus on their consensus protocols and fault tolerance.

Algorand Inc.

Solution Architect / March, 2022January, 2023

Principal Scientists / January, 2023March, 2024

Most Relevant Research Expertise
Software
Other Research Expertise (7)
Cybersecurity
Blockchain
IoT
Distributed Systems
Computer Networks and Communications
And 2 more
About
Dr. Stefano De Angelis is a computer scientist with interest in distributed systems, blockchain, security, and verifiable computing. Currently, he is a visiting researcher at the University of Southampton, working on formal verification methods for smart contracts, and a researcher at the University of Salerno, working on privacy-preserving solutions for blockchain applications. Over his career, Dr. De Angelis worked for NATO HQ as security research scientist and for Algorand, a layer-1 blockchain, as principal scientist and solution architect. He holds a PhD in Computer Science and Cyber Security awarded in 2022 from the University of Southampton, with a thesis about methodologies and benchmarking procedures for assessing blockchain-based systems in realistic adversarial environments, and an MSc in Engineering of Computer Science awarded in 2018 from the University “Sapienza” of Rome. He is the author of several research papers in the field of blockchain and security published in peer-reviewed journals, international conferences and workshops.
Most Relevant Publications (1+)

3 total publications

Security and dependability analysis of blockchain systems in partially synchronous networks with Byzantine faults

International Journal of Parallel, Emergent and Distributed Systems / Oct 24, 2023

De Angelis, S., Lombardi, F., Zanfino, G., Aniello, L., & Sassone, V. (2023). Security and dependability analysis of blockchain systems in partially synchronous networks with Byzantine faults. International Journal of Parallel, Emergent and Distributed Systems, 1–21. https://doi.org/10.1080/17445760.2023.2272777

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Vladimir Shapiro, Ph.D.

Boston, Massachusetts, United States of America
30 Years Experience
PRINCIPAL AI/COMPUTER VISION DATA SCIENTIST; EXPERIENCED SOFTWARE (PYTHON, C/C++, R) DEVELOPER; ADJUNCT UNIVERSITY PROFESSOR
Education

Technical University of Sofia

Electrical & Computer Engineering / January, 1991

Sofia
Experience

Northeastern University

Adjunct Professor / September, 2019Present

Developed and taught numerous courses in AI, Machine Learning, Statistics, Programming, etc., at the graduate and undergraduate levels

Avitas Systems (Baker Hughes from 2019, General Electric Venture from 2016),

Principal Computer Vision Data Scientist / November, 2016May, 2023

● Research, prototyping, designing, and efficiently implementing image and video analytics algorithms with Deep Learning frameworks, e.g., TensorFlow/Keras. ● Agile development in Python, C++, in Linux, including on Amazon AWS. ● Design of the Machine Learning pipelines and workflows, including the entire dataset and model lifecycle. Management of the data annotation and curation operation, including directing the team.

Most Relevant Research Expertise
Software
Other Research Expertise (14)
Computer Vision and Pattern Recognition
Hardware and Architecture
Computer Science Applications
Signal Processing
Artificial Intelligence
And 9 more
About
• Expertise in image and video processing, machine vision, machine learning, digital signal processing, deep learning and pattern recognition algorithm development. • Expertise of production quality C/C++, Python language implementation including for real-time and multiple including embedded platforms. • Experience of working for start-ups and global companies. • Over 50 scientific publications and patents. Specialties: AI, image/video processing, computer vision, machine vision, deep learning, pattern recognition, machine learning, data science, software engineering, embedded software, real-time systems, motor control, Python, C/C++, R and MATLAB programming, software development, object oriented, Linux, Windows, algorithms, Agile development.
Most Relevant Publications (5+)

37 total publications

Towards a Multinational Car License Plate Recognition System

Machine Vision and Applications / May 25, 2006

Shapiro, V., Gluhchev, G., & Dimov, D. (2006). Towards a Multinational Car License Plate Recognition System. Machine Vision and Applications, 17(3), 173–183. https://doi.org/10.1007/s00138-006-0023-5

Handwritten document image segmentation and analysis

Pattern Recognition Letters / Jan 01, 1993

Shapiro, V., Gluhchev, G., & Sgurev, V. (1993). Handwritten document image segmentation and analysis. Pattern Recognition Letters, 14(1), 71–78. https://doi.org/10.1016/0167-8655(93)90134-y

Accuracy of the straight line Hough Transform: The non-voting approach

Computer Vision and Image Understanding / Jul 01, 2006

Shapiro, V. (2006). Accuracy of the straight line Hough Transform: The non-voting approach. Computer Vision and Image Understanding, 103(1), 1–21. https://doi.org/10.1016/j.cviu.2006.02.001

On the hough transform of multi-level pictures

Pattern Recognition / Apr 01, 1996

A. Shapiro, V. (1996). On the hough transform of multi-level pictures. Pattern Recognition, 29(4), 589–602. https://doi.org/10.1016/0031-3203(95)00116-6

On the reconstructive matching of multidimensional objects

IEEE Transactions on Image Processing / Apr 01, 1996

Shapiro, V. A. (1996). On the reconstructive matching of multidimensional objects. IEEE Transactions on Image Processing, 5(4), 653–661. https://doi.org/10.1109/83.491342

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Hector Klie

Houston, Texas, United States of America
21 Years Experience
CEO @ DeepCast.ai | AI-driven Industrial Solutions, Technical Innovation
Education

Ph.D., Computational Science and Engineering / May, 1997

Houston, Texas, United States of America

Master of Arts, Computational and Applied Mathematics / May, 1995

Houston

Simón Bolívar University

Master of Science, Computer Science / May, 1991

Caracas
Experience

DeepCast, LLC

CEO / May, 2017Present

ConocoPhillips Company

Staff Data Scientist / March, 2008April, 2016

Sanchez Oil and Gas

Director of Enterprise Data Solutions / March, 2016March, 2017

Design corporate data science platform, lead R&D in machine learning and AI to generate highly predictive models for field applications

Most Relevant Research Expertise
Software
Other Research Expertise (23)
Artificial Intelligence
Machine Learning
Data Science
optimization
Computational Theory and Mathematics
And 18 more
About
**Results-driven AI leader with 20+ years of success spearheading model development and optimization initiatives in the energy industry and academia. Proven track record in leveraging computational data science, scientific machine learning, and AI to drive breakthrough physics-data solutions and deliver tangible business value. Adept at translating complex scientific concepts into robust AI models. Skilled in numerical simulation, scientific machine learning, and bilingual communication to optimize project outcomes.**
Most Relevant Publications (6+)

81 total publications

Computational Geosciences / Jan 01, 1997

Dawson, C. N., Klíe, H., Wheeler, M. F., & Woodward, C. S. (1997). Computational Geosciences, 1(3/4), 215–249. https://doi.org/10.1023/a:1011521413158

An Autonomic Reservoir Framework for the Stochastic Optimization of Well Placement

Cluster Computing / Oct 01, 2005

Bangerth, W., Klie, H., Matossian, V., Parashar, M., & Wheeler, M. F. (2005). An Autonomic Reservoir Framework for the Stochastic Optimization of Well Placement. Cluster Computing, 8(4), 255–269. https://doi.org/10.1007/s10586-005-4093-3

Models, methods and middleware for grid-enabled multiphysics oil reservoir management

Engineering with Computers / Sep 16, 2006

Klie, H., Bangerth, W., Gai, X., Wheeler, M. F., Stoffa, P. L., Sen, M., Parashar, M., Catalyurek, U., Saltz, J., & Kurc, T. (2006). Models, methods and middleware for grid-enabled multiphysics oil reservoir management. Engineering with Computers, 22(3–4), 349–370. https://doi.org/10.1007/s00366-006-0035-9

Towards a rigorously justified algebraic preconditioner for high-contrast diffusion problems

Computing and Visualization in Science / Mar 27, 2008

Aksoylu, B., Graham, I. G., Klie, H., & Scheichl, R. (2008). Towards a rigorously justified algebraic preconditioner for high-contrast diffusion problems. Computing and Visualization in Science, 11(4–6), 319–331. https://doi.org/10.1007/s00791-008-0105-1

A neural stochastic multiscale optimization framework for sensor-based parameter estimation

Integrated Computer-Aided Engineering / May 13, 2007

Banchs, R. E., Klie, H., Rodriguez, A., Thomas, S. G., & Wheeler, M. F. (2007). A neural stochastic multiscale optimization framework for sensor-based parameter estimation. Integrated Computer-Aided Engineering, 14(3), 213–223. https://doi.org/10.3233/ica-2007-14302

Application of Grid-enabled technologies for solving optimization problems in data-driven reservoir studies

Future Generation Computer Systems / Jan 01, 2005

Parashar, M., Klie, H., Catalyurek, U., Kurc, T., Bangerth, W., Matossian, V., Saltz, J., & Wheeler, M. F. (2005). Application of Grid-enabled technologies for solving optimization problems in data-driven reservoir studies. Future Generation Computer Systems, 21(1), 19–26. https://doi.org/10.1016/j.future.2004.09.028

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Pranav Chandramouli

5 Years Experience
Graduate Student with expertise in Computer Vision, Deep Learning, and its applications, specifically autonomous remote sensor systems for object detection.
Education

University of Saskatchewan

M.S, COMPUTER VISION & DEEP LEARNING / May, 2024 (anticipated)

Saskatoon, Saskatchewan, Canada
Experience

UNIVERSITY OF SASKATCHEWAN

RESEARCH ASSISTANT / August, 2022Present

My research experience includes semantic segmentation of aerial imagery, synthetic image generation, multispectral image analysis, audio classification using sound event detection and optimizing ML workflows with GPU clusters.

FolioWiz LLC

Data Science Intern / June, 2021August, 2021

Set up a PostGRES server and SQL database for a financial trading system. Used this data to create a pipeline for an algorithmic trading toolkit.Developed a module to assess portfolio performance and associated risks. Performed backtesting to evaluate different trading strategies.

Most Relevant Research Expertise
Software
Other Research Expertise (3)
Computer Vision
Deep Learning
Computer Science Applications
About
I am an M.S. student specializing in Computer Vision for Remote Sensing for Wildlife Conservation. I am passionate about leveraging CV, Perception, and DL to build products and solutions that improve the world around us. I am a self-starter and collaborative problem-solver with a strong work ethic. Beyond technology, I spend my time on photography, bird watching, or in the great outdoors.
Most Relevant Publications (1+)

1 total publications

analyzeR: A SonarQube plugin for analyzing object-oriented R Packages

SoftwareX / Jul 01, 2022

Chandramouli, P., Codabux, Z., & Vidoni, M. (2022). analyzeR: A SonarQube plugin for analyzing object-oriented R Packages. SoftwareX, 19, 101113. https://doi.org/10.1016/j.softx.2022.101113

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Dr. Aalok Thakkar

Seattle, Washington, United States of America
1 Years Experience
Research Scientist focussed on integrating formal methods and artificial intelligence.
Education

Chennai Mathematical Institute

Bachelor's of Science, Mathematics

Siruseri

University of Pennsylvania

Ph.D., Computer and Information Science / May, 2023

Philadelphia, Pennsylvania, United States of America
Experience

Movement Labs

Research Engineer / February, 2024Present

Aptos Labs

Research Scientist / July, 2023January, 2024

Most Relevant Research Expertise
Software
Other Research Expertise (8)
programming languages
verification
logic
synthesis
Computer Science Applications
And 3 more
About
My research focuses on integrating **formal methods** and **artificial intelligence**. In particular, I have worked on applying formal methods in the context of programming-by-examples (PBE) for relational queries, synthesis of reactive programs, bounded model checking, and verification of smart contracts. Currently, I work with Movement Labs on designing the Fractal interpreter will allow users to deploy Solidity smart contracts directly on Movement's M1 blockchain. Previously, I have worked with Aptos Labs, Amazon AWS, Nokia Bell Labs, and Adobe India.
Most Relevant Publications (2+)

12 total publications

Mobius: Synthesizing Relational Queries with Recursive and Invented Predicates

Proceedings of the ACM on Programming Languages / Oct 16, 2023

Thakkar, A., Sands, N., Petrou, G., Alur, R., Naik, M., & Raghothaman, M. (2023). Mobius: Synthesizing Relational Queries with Recursive and Invented Predicates. Proceedings of the ACM on Programming Languages, 7(OOPSLA2), 1394–1417. https://doi.org/10.1145/3622847

Synthesis of coordination programs from linear temporal specifications

Proceedings of the ACM on Programming Languages / Dec 20, 2019

Bansal, S., Namjoshi, K. S., & Sa’ar, Y. (2019). Synthesis of coordination programs from linear temporal specifications. Proceedings of the ACM on Programming Languages, 4(POPL), 1–27. https://doi.org/10.1145/3371122

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David J. Lilja

Minneapolis, Minnesota, United States of America
40 Years Experience
Professor Emeritus of Electrical and Computer Engineering, University of Minnesota
Education

University of Illinois Urbana-Champaign

Ph.D., Electrical Engineering

Urbana, Illinois, United States of America

University of Illinois Urbana-Champaign

M.S., Electrical Engineering

Urbana, Illinois, United States of America

Iowa State University

B.S., Computer Engineering

Ames, Iowa, United States of America
Experience

University of Minnesota - Twin Cities

Professor

Department Head

University of Canterbury, Christchurch, New Zealand

Visiting Professor

University of Western Australia, Perth, Australia

Visiting Professor

Most Relevant Research Expertise
Software
Other Research Expertise (15)
Computer architecture
high-performance parallel processing
computer systems performance analysis
approximate computing
Hardware and Architecture
And 10 more
About
**Research Expertise** Computer architecture, high-performance parallel processing, computer systems performance analysis, approximate computing, computing with emerging technologies, and storage systems. **Biographical summary** David J. Lilja received a Ph.D. and an M.S., both in Electrical Engineering, from the [University of Illinois at Urbana-Champaign,](http://www.uiuc.edu/) and a B.S. in Computer Engineering from [Iowa State University](http://www.iastate.edu/) in Ames. He is Professor Emeritus of [Electrical and Computer Engineering](http://www.ee.umn.edu/) at the [University of Minnesota](http://www.umn.edu/) in Minneapolis. He previously served as a member of the graduate faculties in [Computer Science](http://www.cs.umn.edu/), [Scientific Computation](http://www.scicomp.umn.edu/), and [Data Science](http://datascience.umn.edu//).  He served ten years as the head of the ECE department at the University of Minnesota, worked as a research assistant at the Center for Supercomputing Research and Development at the [University of Illinois,](http://www.uiuc.edu/) and as a development engineer at [Tandem Computers Incorporated](http://www.tandem.com/) in Cupertino, California.  He received a [Fulbright](http://www.fulbright.org/) Senior Scholar Award to visit the University of Western Australia and was a visiting Professor at the University of Canterbury in Christchurch, New Zealand. He has chaired and served on the program committees of numerous conferences.  He was elected a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and a Fellow of the American Association for the Advancement of Science (AAAS) for contributions to the statistical analysis of computer performance. He also is a registered Professional Engineer.
Most Relevant Publications (13+)

99 total publications

An Architecture for Fault-Tolerant Computation with Stochastic Logic

IEEE Transactions on Computers / Jan 01, 2011

Qian, W., Li, X., Riedel, M. D., Bazargan, K., & Lilja, D. J. (2011). An Architecture for Fault-Tolerant Computation with Stochastic Logic. IEEE Transactions on Computers, 60(1), 93–105. https://doi.org/10.1109/tc.2010.202

Computation on Stochastic Bit Streams Digital Image Processing Case Studies

IEEE Transactions on Very Large Scale Integration (VLSI) Systems / Mar 01, 2014

Li, P., Lilja, D. J., Qian, W., Bazargan, K., & Riedel, M. D. (2014). Computation on Stochastic Bit Streams Digital Image Processing Case Studies. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 22(3), 449–462. https://doi.org/10.1109/tvlsi.2013.2247429

The superthreaded processor architecture

IEEE Transactions on Computers / Jan 01, 1999

Jenn-Yuan Tsai, Jian Huang, Amlo, C., Lilja, D. J., & Pen-Chung Yew. (1999). The superthreaded processor architecture. IEEE Transactions on Computers, 48(9), 881–902. https://doi.org/10.1109/12.795219

Simulation of computer architectures: simulators, benchmarks, methodologies, and recommendations

IEEE Transactions on Computers / Mar 01, 2006

Yi, J. J., & Lilja, D. J. (2006). Simulation of computer architectures: simulators, benchmarks, methodologies, and recommendations. IEEE Transactions on Computers, 55(3), 268–280. https://doi.org/10.1109/tc.2006.44

Logical Computation on Stochastic Bit Streams with Linear Finite-State Machines

IEEE Transactions on Computers / Jun 01, 2014

Li, P., Lilja, D. J., Qian, W., Riedel, M. D., & Bazargan, K. (2014). Logical Computation on Stochastic Bit Streams with Linear Finite-State Machines. IEEE Transactions on Computers, 63(6), 1474–1486. https://doi.org/10.1109/tc.2012.231

Performing Stochastic Computation Deterministically

IEEE Transactions on Very Large Scale Integration (VLSI) Systems / Dec 01, 2019

Najafi, M. H., Jenson, D., Lilja, D. J., & Riedel, M. D. (2019). Performing Stochastic Computation Deterministically. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 27(12), 2925–2938. https://doi.org/10.1109/tvlsi.2019.2929354

Low-Cost Sorting Network Circuits Using Unary Processing

IEEE Transactions on Very Large Scale Integration (VLSI) Systems / Aug 01, 2018

Najafi, M. H., Lilja, David. J., Riedel, M. D., & Bazargan, K. (2018). Low-Cost Sorting Network Circuits Using Unary Processing. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 26(8), 1471–1480. https://doi.org/10.1109/tvlsi.2018.2822300

Time-Encoded Values for Highly Efficient Stochastic Circuits

IEEE Transactions on Very Large Scale Integration (VLSI) Systems / May 01, 2017

Najafi, M. H., Jamali-Zavareh, S., Lilja, D. J., Riedel, M. D., Bazargan, K., & Harjani, R. (2017). Time-Encoded Values for Highly Efficient Stochastic Circuits. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 25(5), 1644–1657. https://doi.org/10.1109/tvlsi.2016.2645902

Performance analysis of single‐phase, multiphase, and multicomponent lattice‐Boltzmann fluid flow simulations on GPU clusters

Concurrency and Computation: Practice and Experience / Sep 24, 2010

Myre, J., Walsh, S. D. C., Lilja, D., & Saar, M. O. (2010). Performance analysis of single‐phase, multiphase, and multicomponent lattice‐Boltzmann fluid flow simulations on GPU clusters. Concurrency and Computation: Practice and Experience, 23(4), 332–350. Portico. https://doi.org/10.1002/cpe.1645

JaViz: A client/server Java profiling tool

IBM Systems Journal / Jan 01, 2000

Kazi, I. H., Jose, D. P., Ben-Hamida, B., Hescott, C. J., Kwok, C., Konstan, J. A., Lilja, D. J., & Yew, P.-C. (2000). JaViz: A client/server Java profiling tool. IBM Systems Journal, 39(1), 96–117. https://doi.org/10.1147/sj.391.0096

Extending value reuse to basic blocks with compiler support

IEEE Transactions on Computers / Apr 01, 2000

Huang, J., & Lilja, D. J. (2000). Extending value reuse to basic blocks with compiler support. IEEE Transactions on Computers, 49(4), 331–347. https://doi.org/10.1109/12.844346

Improving Computer Architecture Simulation Methodology by Adding Statistical Rigor

IEEE Transactions on Computers / Nov 01, 2005

Yi, J. J., Lilja, D. J., & Hawkins, D. M. (2005). Improving Computer Architecture Simulation Methodology by Adding Statistical Rigor. IEEE Transactions on Computers, 54(11), 1360–1373. https://doi.org/10.1109/tc.2005.184

Exploring Performance Characteristics of the Optane 3D Xpoint Storage Technology

ACM Transactions on Modeling and Performance Evaluation of Computing Systems / Feb 04, 2020

Yang, J., Li, B., & Lilja, D. J. (2020). Exploring Performance Characteristics of the Optane 3D Xpoint Storage Technology. ACM Transactions on Modeling and Performance Evaluation of Computing Systems, 5(1), 1–28. https://doi.org/10.1145/3372783

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Example Software projects

How can companies collaborate more effectively with researchers, experts, and thought leaders to make progress on Software?

Optimizing Software Performance

A company in the gaming industry can collaborate with a software academic researcher to optimize the performance of their gaming software. The researcher can analyze the code, identify bottlenecks, and propose optimizations to enhance the gaming experience for users.

Cybersecurity Solutions

A financial institution can partner with a software academic researcher to develop robust cybersecurity solutions. The researcher can conduct research on emerging threats, develop algorithms for threat detection, and propose strategies to mitigate risks.

Machine Learning Algorithms

An e-commerce company can work with a software academic researcher to develop machine learning algorithms for personalized product recommendations. The researcher can analyze customer data, build predictive models, and optimize the recommendation engine for better conversion rates.

Software Testing Automation

A software development company can collaborate with a software academic researcher to automate their testing processes. The researcher can develop testing frameworks, design automated test cases, and improve the overall efficiency and reliability of the software testing phase.

Data Analytics and Visualization

A healthcare organization can partner with a software academic researcher to leverage data analytics and visualization techniques. The researcher can analyze large healthcare datasets, develop algorithms for predictive analytics, and create interactive visualizations to aid in decision-making and patient care.