Aotian Wu


Tania Banerjee

Research Scientist

Rahul Sengupta


Yash Ranjan


Nooshin Hosseini


Jaemoon Lee


Past Graduate Students

Unless listed explicitly as a co-advisor, I was the principal advisor

  1. Todd Heywood, (1991), A Practical Hierarchical Model of Parallel Computation. Technical Staff, IBM Poughkeepsie.
  2. Anand Rangachari, (1992), Efficient Neural Algorithms for Multiclass Problems. Technical Staff, IBM T. J. Watson Labs. (Co-advisor with Kishan G. Mehrotra).
  3. Yeh Chin Chung, (1992), Static Mapping and Scheduling Algorithms for Distributed Memory Multiprocessors. Associate Professor, Department of Computer Science, National Taiwan University, Taiwan R. O. C.
  4. Jhy Chun Wang, (1993), Load Balancing and Communication Support for Irregular Problems. Technical Staff, IBM Poughkeepsie.
  5. Harpal Maini, (1994), Incorporating Knowledge in Genetic Optimization. Technical Staff, Deutesche Morgan Bank. (Co-advisor with Kishan G. Mehrotra).
  6. M. C. Yang, (1994), 3-D Object Recognition and Description Using Parallel Geometric Hashing Algorithms.
  7. David Koester, (1995), Parallel Block-Diagonal-Bordered Sparse Linear Systems for Power Systems Applications.
  8. Chao-Wei Ou, (1996), Partitioning and Incremental Partitioning for Adaptive Irregular Problems. Technical Staff, Northeast Parallel Architecture Center.
  9. Ravi Shankar, (1996), Scalable Parallel Algorithms for Random Accesses and Shared Memory Simulation. Technical Staff, Bellcore.
  10. Maher Kaddoura, (1996), Parallel Computing in Non-uniform and Adaptive Computational Environments. Technical Staff, Architecture Technology Corporation.
  11. Seungjo Bae, (1997), Runtime Support for High Performance Fortran. Technical Staff, ETRI (Korea).
  12. Jang Sun Lee, (1997), User Controllable Parallel I/O. Technical Staff, ETRI (Korea).
  13. Khaled Alsabti, (1998), Efficient Algorithms for Data Mining Primitives, Assistant Professor, King Fahd University, Saudi Arabia.
  14. Ibraheem Al-furaih, (1998), Optimizing for Memory Hierarchy. Saudi Arabia.
  15. Hankil Yoon, (2000), Efficient Processing of Large Sparse Datasets. Oracle Corporation.
  16. Scott Winterstein, (2000), Efficient Association Mining for Data Warehousing and E-Commerce.
  17. Srijit Kamath, (2005), Efficient Algorithms for Sequencing Multileaf Collimators. (Postdoc at Stanford University College of Medicine; co-advisor with Sartaj Sahni).
  18. Jang Uk In, (2006), Policy-Based Scheduling for Grid Environments. Microsoft Corporation.
  19. Jun Liu, (Feb. 2008), Mining Comparative Genomic Hybridization Data. Google Corporation.
  20. Xiuyao Song, (2008), Novel Change Detection Techniques in Multidimensional Data Mining. Google Corporation.
  21. Laukik Chitnis, (2008). Fault Tolerance and Scalability of Data Aggregation in Sensor Networks. Google Corporation.
  22. Jaeyeon Kang, (2008), Energy Minimization Algorithms for Multicore Machines. Samsung Research.
  23. Parbati Manna, (2008), Detection, Propagation Modeling, and Designing of Advanced Internet Worms. Intel Corporation.
  24. Manas Somaiya, (2010), Novel Mixture Models to Learn Complex and Evolving Patterns in High Dimensional Data. EBay Corporation.
  25. Eunsung Jung, (2010), Network Resource Provisioning in Research Networks, Faculty, Hongik University, Korea.
  26. Yan Li, (2010), Data Structures and Algorithms for Resource Scheduling in High Speed Networks. (Co-advisee with Sartaj Sahni). Google Corporation.
  27. Bin Song, (2010), New in Silico Approaches for Metabolic Engineering (co-advisee with Tamer Kahveci). Google Corporation.
  28. Nirmalya Bandyopadhyay, (2011), Modeling Perturbations in Gene Regulatory and Signaling Networks. Broad Institute.
  29. Arslan Munir, (2012), Modeling and Optimization of Parallel and Distributed Embedded Systems (co-advisee with Ann Gordon Ross), University of Nevada, Reno.
  30. Abdullah Almutairi, (2012), Efficient Algorithms for Learning Correlations in Large-Scale Wireless Data, Kuwait University.
  31. Zhe Wang, (2012), Software and Algorithms for Energy and Temperature Minimization, Facebook.
  32. Saeed Moghhaddam, (2012), Large-Scale Mining of Mobile Online Behavior: Interest-Aware Modeling and Design, Samsung Corporation (co-advisee with Ahmed Helmy), Samsung Research.
  33. William Chapman, (2013), Multiresolution SAR Image Formation and Change Detection on High-Performance Heterogeneous Architectures.
  34. Junjie Li, (2013), GPU Computing for Bioinformatics (co-advisee with Sartaj Sahni), Snapchat Corporation.
  35. Yifan Wang, (2015), Energy Efficient and Thermal-Aware Task Scheduling on Multi-Core Processors.
  36. Hengxing Tan, (2016), Performance, Energy and Thermal Tradeoffs for Data Parallel Problems, Amazon Corporation.
  37. Manu Sethi, Postdoctoral Researcher, 2016-2017, Spatiotemporal Machine Learning (co-advisee with Anand Rangarajan).
  38. Mohamed Gadou, (2018), Performance Energy Tradeoffs for Iterative and Direct Sparse Matrix Solvers on Hybrid Multicore Architectures, Google Corporation.
  39. Chengliang Yang, (2018), Interpretable Machine Learning with Applications in Health Care, Uber Corporation.
  40. Yupeng Yan, (2018), Parallelizable Semi-Supervised Dense Labeling Framework for Very High Resolution Satellite Images (co-advisee with Anand Rangarajan), Airbnb corporation.
  41. Matin Kheirkhahan, (2018), Real-Time Data Monitoring and Machine Learning Methods for Activity Recognition using Wearable Devices, Google Corporation.
  42. Adeesha Pathirannahalage Wijayasiri, (2018), Dynamic Data Driven SAR Reconstruction on Hybrid Multicore Systems (co-advisee with Sartaj Sahni), Faculty in Computer Science, University of Moratuwa, Sri Lanka.
  43. Meng Tang, (2020), GPU Algorithms and Software for Sparse Matrix Factorization, Qualcomm
  44. Keke Zhai, (2020), Dynamic Load Balancing for Heterogenous and Exascale Machines, Facebook Corporation.
  45. Xiaohui Huang, (2020), Video-based Machine Learning for Intelligent Transportation Systems, Facebook Corporation.
  46. Dhruv Mahajan, (2021), Bigdata Analytics for Ground Sensor Data, Proctor and Gamble.
  47. Patrick Emami (2021), Neural algorithms for object­ centric scene understanding December 2021, National Renewable Energy Lab,.
  48. Sanaz Gheibi (2022), Speeding up Algorithms for Large Datasets, Intel Corporation.
  49. Yashaswi Karnati (2022), Machine Learning Algorithms for applications in Intelligent Transportation Systems, Nvidia Corporation.
  50. Pan He (2023), Deep Learning on Spatiotemporal Point Cloud Modeling for Motion and Correspondence, Auburn University