kc santosh

Artificial Intelligence Research Lab (Linkedin)

(News) On-going hiring: Faculty, PostDoc, PhD, and MS students. Join me at the Computer Science Department (USD).

(News, Fall 2024) U.S. Speaker: U.S. Speaker Program (U.S. Department of State)

(News, March 2024) AI Saftey Institute Conosortium, NIST: joined as a PI for USD for Task Forces: #1, #2, #4, and #5 (NIST and USD News).

(News, Fall 2023) Computer science enrollment. Record-setting graduate enrollment (in the state of SD): ~0 percent growth - from a low of 10-12 students, in 3 years.

(News, Summer 2023) ABET re-accreditation (22-23 cycle): Successful!

PhD in Data Science & Engineering. Click here.

AI programs (brochure): The first AI programs in the state: Specialization and Certificate (offline & online).

Bioinformatics graduate certificate. Click here (online).

Data science undergrad certificate for both CS and non-CS majors. Click here (online).

Professional membership & service

Meeting venues

Biography

Prof. KC (Casey) Santosh, a highly accomplished AI expert and TEDx Speaker, is the Chair of the Department of Computer Science at the University of South Dakota (USD). He is also the founding director of the AI Lab. He served the National Institutes of Health (NIH) as a research fellow. Before that, he worked as a postdoctoral research scientist at the LORIA research centre, Universite de Lorraine in direct collaboration with industrial partner, ITESOFT, France. He earned his PhD in Computer Science - Artificial Intelligence from the INRIA Nancy Grand Est research centre (France). With funding exceeding $8.7 million from sources like DOD, NSF, ED, and SDBOR, he has authored 12 books and more than 270 peer-reviewed research articles, including IEEE TPAMI, IEEE TMI, and IEEE TAI. He serves as an associate editor for esteemed journals such as IEEE Transactions on AI, IEEE Transactions on Medical Imaging, Int. J of Machine Learning & Cybernetics, and Int. J of Pattern Recognition & Artificial Intelligence.

As the founder of AI programs at USD, he has taken significant strides to increase enrollment in the graduate program, resulting in over 3,000% growth in just four years. His leadership has helped build multiple inter-disciplinary AI/Data Science related academic programs, including collaborations with Biology, Physics, Biomedical Engineering, Sustainability and Business Analytics departments. Prof. Santosh is highly motivated in academic leadership, and his contributions have established USD as a pioneer in AI programs within the state of SD.

To name a few, Prof. Santosh is the proud recipient of the Visionary Leadership Award (University of Derby - UK, 2023), the Cutler Award for Teaching and Research Excellence (USD, 2021), the President's Research Excellence Award (USD, 2019), and the Ignite Award from the US Department of Health & Human Services (HHS, 2014).

Effective from Spring 2024, he joined the NIST's AI Standards and Innovation (formerly known as AI Safety Institute Consortium) and, since December 2024, has been serving in the U.S. Speaker Program (U.S. Department of State), delivering talks on AI and AI education-being the only representative from South Dakota in both roles.

Recent grant proposals (funded):

#Grant — SD Biomedical Computation Collaborative (role: PI for AI)
Agency: Department of Education
Funding: $6.5 million (2024 - )
Project: https://sd-bcc.org (For more information: click USD News)
#Grant — Seed Grant - SD Biomedical Computation Collaborative (role: PI for AI)
Agency: South Dakota BOR
Funding: $0.745 million (2023 - )
Project: https://sd-bcc.org
#Grant — Research Infrastructure: CC* Campus Compute: Lawrence 2.0: Advancing Multi-Disciplinary Research and Education in South Dakota
Agency: National Science Foundation, NSF Award # 2346643 (role: Co-PI)
Funding: $0.499 million (2024 - )
#Grant — AI/ML Capacity Building at USD (role - AI Lead)
Agency: Department of Defense DOD News
Funding: $1.0 million (2023 - 2025)

Editor (journals, to name a few):

#AssociateEditor of IEEE Transactions on Medical Imaging,
IEEE Transactions on Artificial Intelligence,
International Journal of Machine Learning & Cybernetics, Springer Nature,
International Journal of Pattern Recognition & Artificial Intelligence, World Scientific,
Annual Review of Artificial Intelligence, World Scientific
IET Image Processing,
IEEE Access,
SN Computer Science, Springer Nature,
#EditorialBoard of Discover AI, Springer Nature,
Discover Computing (formerly Information Retrieval Journal), Springer Nature,
Advances in Computational Intelligence, Springer Nature,
Human-Centric Intelligent Systems, Springer Nature
Associate #EditorInChief of Electronics, MDPI (resigned)
#AcademicEditor of PeerJ Computer Science (2021 - 2023)

Chair (conferences, to name a few):

#RTIP2R (2016, 2018, 2020, 2021, 2022, 2023, 2024, 2025): (Program, General and Honorary Chair + Founder)
IEEE #CAI 2026 (Program Chair), #CAI 2025 (Vertical Chair), #CAI 2024 (Publicity Chair)
#IHCI 2025 (Advisory Chair)
#GREC: Program Chair (2019), General Chair (2025)
IEEE #AI Engieering: General Chair + Co-founder (2026)
IAPR #ICDAR: Doctoral Consortium Chair (2024)
#AppliedAI: Honorary Chair + Founder (2024, 2025)
IEEE #CBMS: Industry Chair (2023), General Chair (2020, 2022), Special Track Chair (2021), Sponsorship Chair (2026), Steering Committee (2020 - present)

#ArtificialIntelligence Symposium: Chair + Founder (2021, 2022, 2023 [closing remarks: recording], 2024, 2025)
IEEE #CogMI 2024: Program Chair
IEEE #CVMI: General Chair (2022, 2023, 2024)
#icSoftComp: Chair (2022, 2023, 2024, 2025
#AICV: Chair (2023)
IEEE #ICMI: General Chair (2022)
#DataHarnessing symposium: Chair + Co-founder (2018, 2019)

Review panelist (research grant proposals, to name a few):

#NSF (+ GRFP, ERC, and SBIR/STTR); University of Michigan - Precision Health (USA); State of Louisiana Board of Regents (USA); Mitacs (Canada); NSERC (Canada); Fonds de recherche du Quebec (Canada); Swiss #NSF; Medical Research Council (UK); Medical Research Future Fund - Frontier Health and Medical Research Initiative (AUS); ZonMW - Health Research and Innovation (Netherland); and Wallenberg AI, Autonomous Systems and Software Program - Humanities and Society (Sweden)

Honors, Awards/recognitions & scholarships

U.S. Speaker, (U.S. Speaker Program) U.S. Department of State (2024 -)
Member, AI Safety Institute Consortium, NIST (2024 -)
Visionary Leadership Award, University of Derby, UK (2023)
Cutler (Richard and Sharon) Faculty Award in Liberal Arts, College of Arts and Sciences, USD (2021)
The Choice #Outstanding Academic Title (OAT) of the year for a book titled "#MedicalImaging: Artificial Intelligence, Image Recognition, and Machine Learning Techniques," Association of College and Research Libraries (2020) Follow links: OAT award, 2020 (Book); Certificate, Taylor & Francis Group; and OAT award, Taylor & Francis Group (Engineering).
President's #Award for Research Excellence, USD (2019)
#Professor of the Game: Certificate of recognition (academic achievement), Academic Affairs, USD (2019, 2020)
Belbas-Larson #Award for Excellence in #Teaching (Nomination), USD (2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023)
Senior Member, #IEEE (2018)
Best Paper #Awards (5 Conferences)
U.S. Department of Health and Human Services (#HHS) Ignite #Award (2014)
INRIA-CORDI #Fellowship for Fresh FP-6 Strep, European Project (2008-2011)
Asian Development Bank-Japan #Scholarship (2005-2007)

Publications (research, samples only)

A Jain, S Dubey, S Singh, KC Santosh, BB Chaudhuri and KC Santosh. Non-Uniform Illumination Attack for Fooling Convolutional Neural Networks, IEEE Transactions on Artificial Intelligence (2025)
A Vettoruzzo, MR Bouguelia, J Vanschoren, T Rognvaldsson and KC Santosh. Advances and Challenges in Meta-Learning: A Technical Review, IEEE Transactions on Pattern Analysis & Machine Intelligence (2024)
KC Santosh S Rajaraman, and S Antani: Advances in Deep Learning for Tuberculosis Screening using Chest X-rays: The last 5-Year Systematic Review, Journal of Medical Systems, Springer (2023)
KC Santosh and S Antani: Multimodal Learning in Medical Imaging and Informatics, IEEE Journal of Biomedical & Health Informatics (2023)
Md S Kamal, L Chowdhury, S Hasan, N Dey, and KC Santosh: Explainable AI for Glaucoma Prediction Analysis to Understand Risk Factors in Treatment Planning, IEEE Transactions on Instrumentation & Measurement (2022)
KC Santosh and S Ghosh, D GhoshRoy: Deep Learning for Covid-19 Screening using Chest X-rays in 2020: A Systematic Review, International Journal of Pattern Recognition & Artificial Intelligence, World Scientific (2022)
KC Santosh and S Ghosh: Covid-19 versus Lung Cancer: Understanding chest CT images through Deep Ensemble Neural Networks, International Journal of Artificial Intelligence Tools, World Scientific (2022)
KC Santosh and S Ghosh: Covid-19 medical imaging tools: how big data is big? Journal of Medical Systems, Springer (2021)
KC Santosh: COVID-19 Prediction Models and Unexploited Data, Journal of Medical Systems, Springer (2020)
KC Santosh: AI-driven tools for coronavirus outbreak: Need of active learning and cross-population train/test models on multitudinal/multimodal data, Journal of Medical Systems, Springer (2020)
S Ghosh, A Pal, S Jaiswal, KC Santosh, N Das, and M Nassipuri: segFast-02: Semantic-based image segmentation using encoder-decoder compression architecture, International Journal of Machine Learning & Cybernetics, Springer (2019)
KC Santosh and S Antani: Automated chest X-ray screening: can lung section symmetry help detect pulmonary abnormalities? IEEE Transactions on Medical Imaging (2018)
KC Santosh and L Wendling: Angular relational signature-based chest radiograph image view classification, Medical & Biological Engineering & Computing, Springer (2018)
KC Santosh and P Roy: Arrow detection in biomedical images using sequential classifier, International Journal of Machine Learning and Cybernetics, Springer (2018)
M Bouguelia, S Nowaczyk, and KC Santosh: Antanas Verikas. Agreeing to disagree: active learning with noisy labels without crowdsourcing, International Journal of Machine Learning & Cybernetics, Springer (2018)
KC Santosh, L Wendling, S Antani, and G Thoma: Overlaid Arrow Detection for Labeling Biomedical Image Regions, IEEE Intelligent Systems, (2016)

Recent talks

Important note. I delivered more than 80 plenary/keynote talks at the international conference/university events. If you are looking at me for a talk, click ACM Distinguished Speaker and submit your request.

(December 28-29, 2024) The Push and Pull Between Healthcare Professionals and Data Scientists. 3rd International Conference on Data Analytics & Learning (DAL), MGM Engineering, India
(December 19-20, 2024) Green Computing is all what you need! 7th International Conference on Recent Trends in Image Proc & Patt Recog (RTIP2R), IIIT Bhopal, India
(October 19-20, 2024) Sustainable AI Solutions. IEEE SPS Distinguished Lecture - IEEE Conference on CVMI, IIIT Allahbad, India
(August 26-30, 2024) Sustainable AI solutions for medical imaging informatics. Computational Neuroscience, Neurotechnology and Neuro-inspired AI Summer School, Ulster university, UK
(August 15-16, 2024) Human-in-loop machine learning - how big data is big to begin with? International Conference on Multimedia Analysis and Pattern Recognition, Vietnam
(June 12, 2024) #AI and #GenerativeAI - Ethical Concerns. South Dakota State Bar Annual Convention, Pierre, South Dakota
(June 11-12, 2024) Chips and Science Act, Sustainable AI, and the Future. IEEE-USA Innovation, Workforce, and Research Conference, South Dakota
(April 07, 2024) Building sustainable AI for all, TEDx Talk - USD
(March 15-16, 2024) Explainable AI (xAI): who to blame - data or model? 6th International Conference on Computational Intelligence and Pattern Recognition, odisha, India
(December 07-08 2023) #AIforGood, but how about carbon footprint? 6th International Conference on Recent Trends in Image Processing & Pattern Recognition, University of Derby, UK
(Nov 8-10, 2023) Human-in-loop machine learning - how big data is big to begin with? 15th International Conference on Intelligent Human-Computer Interaction, South Korea
(September 20, 2023) Machine learning in healthcare - let us go beyond one-way test or automation? The University of Chicago Medicine
(August 12-13, 2023) Big data issue, no worries - active learning is the must! 9th IEEE International Conference on Cloud Computing and Intelligence Systems, Dali, Yunnan Province of China
(July 24-26 2023) Responsible AI or human? MGM's Health Sciences Institute, Mumbai, India
(July 22-23, 2023) Explainable AI model or data? Applied AI Workshop, Central University of Karnataka, India
(July 20, 2023) Machine learning for medical imaging informatics - deep or shallow? Summer School of IEEE Computational Intelligence Society on Computational Advances in Deep Learning and Applications, Indian Institute of Information Technology (IIIT), Allahabad, India
(July 16, 2023) Trust me, AI is not for computer scientists! Banasthali University, India
(June 01, 2023) AI & Ethics Panel. Grreat Plains Network Annual Meeting, Kansas City, MO (May 31 - 02, 2023) [recording - address, YouTube]
(May 25, 2023) The Human Connection - Artificial Intelligence (people, governance, and tooling). South Dakota Hunamnities Council, SD
(May 09, 2023) AI/Data Science - from Healthcare to Housing Industry? Mountain Plains Housing Summit, SiouxFalls, SD (May 08 - 10, 2023) [recording - address, YouTube]
(May 02, 2023) AI is the dealbreaker, and so is active learning! APEC symposium on ICT Skill Standards for Artificial Intelligence, Bangkok, Thailand
(March 28, 2023) AI is dealbreaker - #activelearning, #bigdata, #carbonfootprint, #sustainableAI, and #greencomputing. USD's third AI symposium, Vermillion, SD [recording - YouTube]
(Feb 07, 2023) Few-shot Learning in an #Activelearning Framework to Understand Future #Epidemics. SDSU Data Science Symposium, Brookings, SD
(Feb 07, 2023) #AIforgood - Utopia or dystopia? USD Utopia/Dystopia Symposium, Vermillion, SD
(Feb 07, 2023) Few-shot Learning in an #Activelearning Framework to Understand Future #Epidemics. SDSU Data Science Symposium, Brookings, SD
(Nov 21, 2022) #Activelearning to Minimize the Possible Risk from Future #Epidemics. IEEE Computer Science Society - Hyderabad section, JNTU, Hyderabad, India
(Nov 18, 2022) #MedicalImagingInformatics - #eXplainableAI. 6th International Conference on Intelligent Comput- ing and Communication, GNITS, Hyderabad, India
(Aug 13, 2022) #eXplainableAI for #healthcare in #activelearning framework.
23rd New Frontiers in Computing Conference (NFIC 20222), IEEE Computer Society Santa Clara Valley Chapter, Silcon Valley
(Aug 12, 2022) #Activelearning in healthcare - infectious disease outbreak.
International Conference on Computer Vision and Machine Intelligence (CVMI) - IIIT, Allahabad, India
(July 23, 2022) #AI for Medical Imaging Informatics - Where have We Missed #Explainability?
IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS 2022), Shenzhen, China
(July 28, 2022) #eXplainableAI for Medical Imaging Informatics.
9th International Conference on Machine Vision and Machine Learning (MVML 2023), Prague, Czech Republic
(June 20-28, 2022) #AIforGood and so does #machinelearning - #machinelearning for #physics and/or #physicists (case study - neutrino classification).
PIRE-GEMARDAC, Queen's University, Kingston, Canada
(May 17, 2022) #AI for infrastructure secrity - Time to think about Critical Infrastructure Security
VIT, Bhopal, India
(March 25, 2022) #AI for Medical Imaging Informatics - Where have We Missed #Explainability?
College of Engineering and Technology (Seminar), East Carolina University

Books

Contact: Department of Computer Science
The University of South Dakota
414 E. Clark Street
Office #201, Arts & Sciences (Building)
Vermillion, SD 57069